Ocean Circulation and Air-Sea Interaction in the South China Sea (Springer Oceanography) 9811962618, 9789811962615

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Springer Oceanography

Dongxiao Wang

Ocean Circulation and Air-Sea Interaction in the South China Sea

Springer Oceanography

The Springer Oceanography series seeks to publish a broad portfolio of scientific books, aiming at researchers, students, and everyone interested in marine sciences. The series includes peer-reviewed monographs, edited volumes, textbooks, and conference proceedings. It covers the entire area of oceanography including, but not limited to, Coastal Sciences, Biological/Chemical/Geological/Physical Oceanography, Paleoceanography, and related subjects.

Dongxiao Wang

Ocean Circulation and Air-Sea Interaction in the South China Sea

Dongxiao Wang School of Marine Sciences Sun Yat-sen University Zhuhai, China

ISSN 2365-7677 ISSN 2365-7685 (electronic) Springer Oceanography ISBN 978-981-19-6261-5 ISBN 978-981-19-6262-2 (eBook) https://doi.org/10.1007/978-981-19-6262-2 Jointly published with Science Press The print edition is not for sale in China mainland. Customers from China mainland please order the print book from: Science Press. © Science Press and Springer Nature Singapore Pte Ltd. 2022 This work is subject to copyright. All rights are reserved by the Publishers, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publishers, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publishers nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publishers remain neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Contents

1 Overview of the Atmosphere and Hydrological Environment of the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Three-Dimensional Structure of the South China Sea Circulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 General Characteristics of the South China Sea Circulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.2 Western Boundary Current of the South China Sea . . . . . . . . 1.1.3 South China Sea Warm Current and Northern Upwelling Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.4 Deep South China Sea Circulation . . . . . . . . . . . . . . . . . . . . . . 1.2 Dynamic and Thermal Effects of the South China Sea Circulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 South China Sea Throughflow . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.2 Influence of South China Sea Eddy . . . . . . . . . . . . . . . . . . . . . 1.2.3 Impacts on Sea and Atmosphere . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 The Characteristics of Large-Scale Circulation Dynamics in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Luzon Strait Water Exchange . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 Volume Transport in the Luzon Strait . . . . . . . . . . . . . . . . . . . 2.1.2 Interannual Variation Characteristics of Water Flux at 120° E Section of the Luzon Strait . . . . . . . . . . . . . . . . . . . . 2.1.3 Possible Connection Between Water Exchange in the Luzon Strait and Coastal Kelvin Wave . . . . . . . . . . . . . 2.2 South China Sea Through Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Variation Characteristics of the South China Sea Throughflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 The Dynamic Mechanism of the Variation in the South China Sea Through Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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2.2.3 The Thermal Dynamics and Climate Effects of the South China Sea Throughflow on the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 South China Sea Western Boundary Current . . . . . . . . . . . . . . . . . . . . 2.3.1 Interannual Variation of the Western Boundary Current of the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 The Formation Mechanism of the West Boundary Current of the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . 2.3.3 Vietnam Offshore Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.4 Response of Summer Cold Eddy to Monsoon on the Western Boundary of South China Sea . . . . . . . . . . . . 2.3.5 The Relationship Between the Intraseasonal Variation of SST and the Intraseasonal Variation of Wind Stress in Vietnam Nearshore in Summer . . . . . . . . . . . . . . . . . . . . . . 2.4 Southern South China Sea Circulation . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Seasonal Succession of Circulation in the Southern South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.2 Interannual Differences in Spring Hydrological Elements in the Southern South China Sea . . . . . . . . . . . . . . . 2.5 Summary and Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 The Northern Shelf and Slope Currents of the South China Sea . . . . . 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1 The Continental Slope Current in the Northern South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2 Upwelling in Eastern Guangdong . . . . . . . . . . . . . . . . . . . . . . 3.1.3 Pearl River Diluted Water Plume . . . . . . . . . . . . . . . . . . . . . . . 3.2 South China Sea Warm Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Numerical Simulation of the South China Sea Warm Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Momentum Balance of the South China Sea Warm Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3 Vorticity Balance of the South China Sea Warm Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.4 The Source Driving Force of the South China Sea Warm Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Upwelling of East Guangdong in South China Sea . . . . . . . . . . . . . . 3.3.1 The Spatial Distribution Characteristics of the East Guangdong Upwelling in the South China Sea . . . . . . . . . . . 3.3.2 Response of Eastern Guangdong Upwelling to Variable Wind Field in the South China Sea . . . . . . . . . . . 3.3.3 Contributions of Wind and Topography to the Upwelling in Eastern Guangdong, South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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3.4 The Pearl River Diluted Water Plume . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.1 Seasonal Characteristics and Interannual Variability of the Pearl River Diluted Water . . . . . . . . . . . . . . . . . . . . . . . . 3.4.2 Rapid Response of the Pearl River Diluted Water and Its Front to Changes in Physical Driving Factors Such as Wind, Tide and Fresh Water Runoff . . . . . . . . . . . . . 3.4.3 Impact of Diluted Water Expansion of the Pearl River Estuary on the Northern South China Sea Coastal Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Summary and Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Middle and Deep Waters Mass and Circulation in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Intermediate Waters and Circulation in the South China Sea . . . . . . 4.1.1 Annual Average and Seasonal Variation Characteristics of the Intermediate Water in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.2 Characteristics of Changes in South China Sea Intermediate Water on a Long-Time Scale . . . . . . . . . . . . . . . 4.1.3 The Current Deflection Around Dongsha Islands . . . . . . . . . 4.1.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Deep Water Mass and Circulation in the South China Sea . . . . . . . . 4.2.1 Characteristics of Intermediate Circulation and Deep Circulation in the South China Sea Simulated by Various Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Sensitivity Test of the Deep Circulation in the South China Sea to Topography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 Diagnostic Model of the South China Sea Bottom Circulation in Condition of Tidal Mixing, Eddy-Induced Mixing and Topograph . . . . . . . . . . . . . . . . . . . 4.3 Deep Meridional Overturning Circulation in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.1 South China Sea Meridional Overturning Circulation Streamfunction Simulated by Multiple Models . . . . . . . . . . . 4.3.2 Diagnostic Analysis of Meridional Overturning Circulation in the South China Sea Based on TRACMASS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.3 High-Frequency Variability of the Deep Meridional Overturning Circulation in the South China Sea . . . . . . . . . . 4.4 Summary and Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea . . . . . 231 5.1 General Characteristics and Individual Case Studies of Mesoscale Eddies in the South China Sea . . . . . . . . . . . . . . . . . . . . 231

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5.1.1 General Characteristics of Mesoscale Eddies in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.2 Individual Mesoscale Eddies in the South China Sea Observed by Satellites and Cruise . . . . . . . . . . . . . . . . . . . . . . 5.2 Physical and Ecological Effects of Mesoscale Eddy in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1 Thermal and Dynamic Effects of Mesoscale Eddy . . . . . . . . 5.2.2 The Ecological Effect of Eddy . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Near-Inertial Energy Characteristics of the South China Sea Under the Influence of Mesoscale Eddies . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Near-Inertial Energy Characteristics of the Xisha Islands Under the Influence of Mesoscale Eddies and Typhoons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.2 Strong Near-Inertial Oscillations Caused by the Onset of Monsoon and Mesoscale Eddies in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Summary and Prospect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Air-Sea Interaction in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . 6.1 Variation Characteristics of Sea Surface Temperature for the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.1 Diurnal and Intra-seasonal Variations of Sea Surface Temperature for the South China Sea . . . . . . . . . . . . . . . . . . . 6.1.2 Interannual and Longer Time Scales . . . . . . . . . . . . . . . . . . . . 6.1.3 Upper Mixing Layer/Barrier Layer and Sea Surface Temperature Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 The Sea-Atmosphere Interface and Boundary Layer in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.1 Research on the Fluxes at the Sea-Air Interface . . . . . . . . . . . 6.2.2 Temporal and Spatial Variation of the Marine Atmospheric Boundary Layer in the South China Sea . . . . . 6.3 Characteristics and Analysis of Tropical Cyclone Activity in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.1 Influencing Factors of Tropical Cyclone Formation in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.2 Formation, Intensity and Track of Tropical Cyclones in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.3 Interannual and Interdecadal Variability of Tropical Cyclone Formation Frequency Over the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 Intra-seasonal Signals of Upper Ocean and Atmospheric Anomalies in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.1 Northward Propagation Characteristics of the South China Sea Intra-seasonal Oscillation . . . . . . . . . . . . . . . . . . . .

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6.4.2 Sources of Intra-seasonal Oscillation in the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.3 The Basic Characteristics of ISO Affecting the South China Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 Summary and Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 South China Sea Observation and Data Assimilation . . . . . . . . . . . . . . 7.1 Ocean Observation in the South China Sea . . . . . . . . . . . . . . . . . . . . . 7.1.1 Large-Scale Observation of Voyage . . . . . . . . . . . . . . . . . . . . . 7.1.2 Offshore and Station Observation Network . . . . . . . . . . . . . . 7.2 South China Sea Mooring Observing Network . . . . . . . . . . . . . . . . . . 7.2.1 South China Sea Observation Database . . . . . . . . . . . . . . . . . . 7.3 South China Sea Data Assimilation and Reanalysis Products . . . . . . 7.3.1 Application of Optimal Interpolation Method to Assimilate SST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.2 Application of Ensemble Karman Filter and Ensemble Karman Smooth Assimilation in the SCS . . . . . . . . . . . . . . . . 7.3.3 Redos Reanalysis Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Summary and Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Chapter 1

Overview of the Atmosphere and Hydrological Environment of the South China Sea

The South China Sea is located in tropical and subtropical low latitudes (0~23°N, 99°~121°E) with an area of about 3.5 million km2 , surrounded by mainland China, Taiwan, Philippine, Malaysia Island and Indo-China Peninsula. It is the largest open sea in China, about three times the total area of the Yellow Sea, Bohai Sea and East China Sea. It is also the world’s third continental marginal sea, second only to the Coral Sea and the Arabian Sea. As the largest semi-closed sea in the western Pacific, the South China Sea is an important passage connecting the Pacific and Indian oceans. The northern part of the South China Sea is connected to the East China Sea through the Taiwan Strait, and the eastern part is connected to the Western Pacific through the Luzon Strait, the southeast is connected to the Sulu Sea through the Mindoro Strait and Balabac Strait, and the south is connected to the Java Sea and the Indian Ocean through the Karimata Strait and the Malacca Strait (Yang and Liu 1998). Among them, the Luzon Strait is the only deep water channel connecting the South China Sea and the ocean, and its threshold depth is about 2500 m. The seafloor of the South China Sea is complex (Fig. 1.1), mainly composed of three parts: continental shelf, continental slope and central sea basin. The average depth of the South China Sea is about 1212 m, and the deepest part is the abyssal plain in the central part, which is about 5567 m. The continental shelf is composed of continental margins and island arcs sloping toward the ocean basin with different slopes. The northern and southern continental shelf areas are broad and the depth is mostly less than 100 m. The central basin is located in the east of the central part of the South China Sea, with a depth of more than 1000 m. It is a long and narrow basin bounded by the continental slope with a northeast to southwest trend. The middle part of the basin is enclosed by the contour line of 3000 m depth in a diamond shape, occupying about half of the area of the deep sea basin. Between the central basin and the continental shelf is a steep continental slope, divided into east, south, west, north four areas. The deep-sea basin formed in the long-term crustal change process, most of which is relatively flat, can be regarded as “abyssal plain”. Although it is called

© Science Press and Springer Nature Singapore Pte Ltd. 2022 D. Wang, Ocean Circulation and Air-Sea Interaction in the South China Sea, Springer Oceanography, https://doi.org/10.1007/978-981-19-6262-2_1

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1 Overview of the Atmosphere and Hydrological Environment …

Fig. 1.1 Topographic map of the South China Sea (based on topographic data of ETOPO5)

“plain”, its topography is very complicated with large and small seamounts and sea hills (Zhang 2010). In addition to the complex topography, the South China Sea is surrounded by a series of narrow mountain ranges. Annan Mountain is the main mountain range on Indo-China Peninsula, which is the western boundary of the South China Sea. It is about 1100 km long and trending northwest to southeast. In the eastern of South China Sea, there are long, narrow and towering mountains on the islands of Taiwan, Luzon, the Philippine Islands and Kalimantan. The topographic effect of mountains has an important influence on the air—sea coupling system of the South China Sea, and there are significant differences in climate effects on the windward and leeward sides of mountains (Xie 2003; Xie et al. 2006). There are many rivers around the South China Sea, mainly the Mekong, Red and Pearl rivers, which supply a large amount of fresh water to the South China Sea. The Mekong River, known in China as the Lancang River, is the longest river in Southeast Asia with a total length of about 4909 km. The Pearl River is the largest river system in southern China with an average annual runoff of about 336 billion m3 . The runoff of the Pearl River varies significantly with the seasons, accounts for about 80% of the annual runoff during the wet season (April to September) and reachs more than 50% of the annual runoff from June to August.

1.1 Three-Dimensional Structure of the South China Sea Circulation

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1.1 Three-Dimensional Structure of the South China Sea Circulation 1.1.1 General Characteristics of the South China Sea Circulation Located in the East Asian monsoon region, the South China Sea belongs to the typical East Asian monsoon climate system and its circulation is driven by stable and strong monsoon atmospheric circulation (Wyrtki 1961). The climate of the South China Sea presents a semiannual cycle characteristic with significant difference between winter and summer months, and the transition season is very short. The feature of winter monsoon is the northeast monsoon, and the average wind speed is 9 m/s. The summer monsoon is a weak southwest monsoon with an average wind speed of 6 m/s (Yang et al. 2002). Therefore, the sea surface wind in winter monsoon period is stronger than that in summer monsoon period, and the average wind speed in spring and autumn transition season is smaller than that in winter and summer. The upper ocean circulation of the South China Sea is mainly driven by monsoon in the background of the Southeast Asian monsoon system. In winter, the northeast monsoon controls the South China Sea, and the South China Sea circulation generally presents as a large cyclonic circulation (Lu and Chan 1999; Dippner et al. 2007). In summer, southwest monsoon is prevailing in the South China Sea, and the general circulation is generally dipolar characterized by cyclonic in the north and anticyclonic in the south (Wu et al. 1998; Fang et al. 2002; Chern and Wang 2003). Wind field drive and topographic features determine that the upper Marine circulation in the South China Sea presents seasonal circulation characteristics driven by monsoon, and the circulation in the northern part of the South China Sea is mainly affected by the invasion of the Kuroshio in the Luzon Strait (Yang et al. 2002). The water exchange in the Luzon Strait will transmit the El Nino Southern Oasis (ENSO) signals in the Pacific Ocean to the South China Sea, which plays an important role in the circulation and heat budget of the South China Sea (Qu et al. 2004). On the one hand, the ocean changes the density field of the South China Sea through water exchange (thermo-salt exchange), and then affects the circulation of the South China Sea. On the other hand, it acts directly on the circulation of the South China Sea through momentum exchange (Kuroshio invasion, Kuroshio separation current ring, etc.). Mesoscale eddies in the South China Sea, mainly driven by monsoon, are very active, and the existence of mesoscale eddies leads to a multi-eddy structure in the South China Sea circulation (Su et al. 1999). The circulation in the South China Sea has obvious features of eddies with cyclonic eddies in winter, in summer, cyclonic eddies in the north accompanied by anticyclonic eddies in the south (Xu et al. 1982; Hu et al. 2000). The evolution of mesoscale eddies is response to the seasonal adjustment of large-scale circulation. The formation and evolution of multi-eddy structure and the energy conversion between large-scale circulation are an important aspect of the energy balance in the South China Sea.

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1.1.2 Western Boundary Current of the South China Sea The westward strengthening phenomenon of the circulation in the South China Sea is reflected in Wyrtki (1961), which is the west boundary current of the South China Sea. Whether it is winter or summer, the strengthening trend of the western boundary of the South China Sea circulation is very obvious. The thermocline changes caused by wind stress curl adjust the ocean to achieve a quasi-steady-state Sverdrup equilibrium, and establish a seasonally averaged large-scale circulation and the corresponding western boundary current of the South China Sea (Liu et al. 2000; Liu et al. 2001b). The west boundary current of the South China Sea is a major component of the South China Sea circulation (Li et al. 2000; Li 2002). This strong current flows southward in winter and northward in summer, which is the most obvious seasonal variation characteristic of the large-scale circulation in the surface of the South China Sea. The West Boundary Current is an important transport channel through the South China Sea, which has an important influence on the heat, salt and volume budget of the South China Sea. The path, morphology and changes of the western boundary current of the South China Sea in winter indicate that the surface layer of the south China sea in the west boundary current originated in the northern south China sea and current, velocity to strengthen after arrived in Vietnam’s central coast, narrow flow convergence, to exceed 0.8 m/s southward along the east coast of Vietnam (He and Wang 2009) to Vietnam southeastern coast, to reached the southeast coast of Vietnam, the maximum velocity of the West Boundary Current of the South China Sea exceeded 1.4 m/s (He and Sui 2010) (Fig. 1.2). The temporal changes of the West South China Sea boundary current, especially the Vietnam offshore current, is mainly controlled by the variation of the sea basin scale wind field in the South China Sea, and the buoyancy drive can strengthen or weaken the West South China Sea boundary current in summer or winter. The Luzon Kuroshio invasion is very important to the circulation changes north of 18°N and

Fig. 1.2 Distribution characteristics of surface circulation velocity (vector) and temperature (shadow) in the South China Sea obtained by drifting buoys (He and Wang 2009; He and Sui 2010) a In December 2003, b In December 2004, c In December 2005 The two contour lines are 200 and 1000 m isobath

1.1 Three-Dimensional Structure of the South China Sea Circulation

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the WSCS boundary current, and it can ultimately determine the appearance of the WSCS boundary current in winter (Yang et al. 2002). The β effect is also crucial for the westward strengthening of the South China Sea circulation (Zhai et al. 2004). The influence of sea surface heat flux on the seasonal evolution of circulation is secondary (Chu et al. 1999; Yang et al. 2002). Non-linear Vorticity transport is very important for the generation of double eddy structure in the western boundary current region of the South China Sea (Wang et al. 2006b), and the interaction between bottom topography and wind-generated coastal current is the key factor that leads to the offshore movement of the western boundary jet in winter and summer (Gan and Qu 2008). Moreover, the western boundary current of the South China Sea has obvious interannual variation, such as the interaction between offshore circulation and eddy in southeast Vietnam (Fang et al. 2002).

1.1.3 South China Sea Warm Current and Northern Upwelling Current In addition to large-scale circulation, there are many fine circulation structures similar to the South China Sea Warm Current and the northern upwelling of the South China Sea. The South China Sea Warm Current is a current flowing from the coastal area of eastern Guangdong and the deep water area off the coast of Guangdong to the northeast all the year round. Because it flows against the northeast wind in winter, it is called the “winter upwind ocean current” (Guan 1978, 1985, 1998). The South China Sea Warm Current runs from the east of Hainan Island to the offshore of eastern Guangdong along the isobath, and its velocity and amplitude increase along the east of Dongsha Islands, but its stability, durability and continuity are weak, showing significant seasonal and interannual variation characteristics (Guo et al. 1985). There have been many discussions on the formation mechanism of the South China Sea warm current, such as the Kuroshio invasion and the topographical interaction of the northern South China Sea (Su and Wang 1987; Ma 1987; Zhong 1990; Huang et al. 1992; Yuan and Deng 1996; Hsueh and Zhong 2004), wind stress relaxation provides transient forces (Chao et al. 1996; Chiang et al. 2008). Slope change along continental shelf isobath strike and downstream sea surface (Zeng et al. 1989; Li et al. 1993; Fang and Zhao 1988), perennial northward current in the Taiwan Strait, etc., (Yang et al. 2008). The coastal area of eastern Guangdong in the northern part of the South China Sea is a typical upwelling area, which includes the Qiongdong upwelling and the eastern Guangdong upwelling system. The upwelling in the northern South China Sea is widely considered to be wind-driven upwelling (Shaw 1992; Li 1993; Su 1998; Hu et al. 2001). The spatial distribution of upwelling is modulated by topography, coastal current, Pearl River diluted water and other factors (Gan et al. 2009a, b; Shu et al. 2011; Wang et al. 2012a, 2014). Up to now, summer coastal southwest winds have been considered to be the main mechanism for the upwelling of eastern

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Guangdong in the northern South China Sea (Guan and Chen 1964; Yu 1987; Zeng 1986; Gan et al. 2009b; Jing et al. 2011; Gu et al. 2012). In addition, topographical effects will also have an important impact on upwelling. In the wind-driven upwelling area, the distribution of the coastal topography controls the direction of the coastal current, and then modulates the mass transport perpendicular to the shore through the geostrophic balance, thereby affecting the spatial distribution of upwelling intensity (Gan and Allen 2002).

1.1.4 Deep South China Sea Circulation Scholars speculate that under the influence of the “sandwich” structure of the net momentum flux of the Luzon Strait and the strong mixing of the deep layers of the South China Sea, the meridional overturning circulation in the South China Sea has the following structure: in the upper layer of the Luzon Strait, tropical Pacific subsurface water flows into the South China Sea and forms the South China Sea Throughflow (SCSTF) (Qu et al. 2005, 2006; Wang et al. 2006a; Yu et al. 2007); In the Luzon Strait, the deep Pacific water flows into the South China Sea and drives the deep overturning circulation of the South China Sea (Qu et al. 2006; Liu et al. 2008; Fang et al. 2009). Afterwards, the deep and subsurface water of the Pacific Ocean met and mixed in the middle layer of the South China Sea and flowed out of the middle layer of the Luzon Strait, thus forming the meridional overturning circulation in the middle layer of the South China Sea (Fig. 1.3). Fig. 1.3 Conceptual map of the South China Sea circulation

1.2 Dynamic and Thermal Effects of the South China Sea Circulation

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Observations of deep-sea flow in the Luzon Strait and related observations of marine geology have confirmed the invasion of deep-water overflows in the Pacific Ocean. According to the theory of deep-sea circulation (Stommel and Arons 1959a, b), cyclonic circulation exists in the deep sea basin of the South China Sea (Chao et al. 1996). Li and Qu (2006) proposed a conceptual map of the thermohaline circulation in the South China Sea based on the data of deep dissolved oxygen in the South China Sea. Wang et al. (2011a) diagnosed the deep central seamount area of the South China Sea as cyclonic circulation with strong deep sea western boundary current and weak cyclonic circulation in the south. The Luzon Strait, as the only channel of deep communication between the South China Sea and the Pacific Ocean, has a significant influence on the deep circulation and meridional overturning circulation of the South China Sea (Qu et al. 2006). The results show that the thickness of the middle water mass in the South China Sea is about 650 m, and there are obvious seasonal, interannual and interdecadal variations. The interaction between the deep sea circulation and the upper and middle layer circulation can affect the distribution of the water mass in the South China Sea. In addition, the middle-level current has a significant separation current in the Dongsha sea area: in the middle-level current field near the Dongsha (about 500 m) in autumn, there is an obvious phenomenon of flowing across the isobath to the deep sea.

1.2 Dynamic and Thermal Effects of the South China Sea Circulation 1.2.1 South China Sea Throughflow The large-scale circulation in the South China Sea has an open “through-through” feature. After the Pacific water enters the South China Sea through the Luzon Strait, part of the water flows out of the South China Sea through the Taiwan Strait in the northern part of the South China Sea, in addition, a considerable part of it will pass through the Karimata Strait in the southern part of the South China Sea, the Mindoro Strait flows out of the South China Sea. This branch of the South China Sea of the Pacific-Indian Ocean water body is collectively called the South China Sea throughflow (Wang et al. 2006a; Qu et al. 2006; Yu et al. 2007) (Fig. 1.4). The South China Sea throughflow is an important form of water exchange between the South China Sea and its adjacent oceans. The Luzon Strait flow is out of the South China Sea through the Taiwan Strait, the Karimata Strait and the Minduro Strait, which plays a pivotal role in the Indonesian throughflow (ITF), a major water and heat transport channel between the Pacific and Indian oceans, which can have a significant impact on global ocean circulation and climate change (Hirst and Godfrey 1993; Verschell et al. 1995). In terms of the climatology, the fundamental reason why the South China Sea has not continued to warm and fade is that the perforation of the South China Sea

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Fig. 1.4 Schematic diagram of South China Sea throughflow and Indonesia throughflow distribution characteristics of climate state circulation in January (ORAS4)

Through Flow (SCSTF) transports this heat and fresh water to the adjacent sea area, thereby acting as a cold advection (Qu et al. 2006, 2009; Liu et al. 2012). The cold advection of SCSTF will not only affect the OHC of the South China Sea (Wang 2010), but also affect the characteristics of SST and OHC in the surrounding waters. If the South China Sea basin is closed, the internal SST of the South China Sea will rise by more than 1 °C, and the most obvious area of warming is the downstream area of the western boundary current (Tozuka et al. 2009). The closure of SCSTF will lead to significant differences in southward heat transfer in the Makassar Strait (Tozuka et al. 2009; Wang 2010; Wang et al. 2011b). Therefore, the South China Sea through-flow has important potential significance in the climate change system. There are important dynamic and thermal effects in the South China Sea throughflow, and the output of the Kalimata Strait, one of the main channel channels for its outlet, is southward with 3.6 Sv in winter (Fang et al. 2010), which is equivalent to the flow of the Indonesian throughflow. Surface circulation in the Makassar Strait is not driven by local wind, but is the result of large-scale wind field (Qu et al. 2005; Wang et al. 2011b; Gordon et al. 2012). The presence of SCSTF will lead to a decrease in the southward velocity of the Makassar Strait in El Niño years (Tozuka et al. 2009; Wang 2010) and it will also generate dynamic feedback on the current on the western border of the Philippine Sea: in addition to affecting the Kuroshio and Mindanao Outside the upper-layer current field, the north–south movement of the north equatorial current (NEC) bifurcation will also be changed.

1.2 Dynamic and Thermal Effects of the South China Sea Circulation

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1.2.2 Influence of South China Sea Eddy There are mesoscale eddies with significant seasonal characteristics in the South China Sea, which are called seasonal eddies. The mesoscale eddies leads to the multi-eddy structure of the circulation in the South China Sea (Su et al. 1999), and the evolution of mesoscale eddies is responded to the seasonal adjustment of largescale circulation. Ocean eddy activities in the South China Sea has been reflected in all previous hydrological surveys of the South China Sea (Huang et al. 1992). The circulation pattern east of Vietnam has an obvious double eddy structure (Fang et al. 2002; Shaw et al. 1999). In addition, the anticyclonic separation eddy from Kuroshio is located in the northeastern part of the South China Sea (Li et al. 1998), there are also the Luzon cold eddy located in the northwest of Luzon (Yang and Liu 1998) and the Luzon warm vortex located in the northwestern waters of Luzon. Guo et al. (Yuan et al. 2007; Wang et al. 2008a, b and 2012b). The boundary area of South China Sea is a typical active area of eddies, especially the western boundary current area of the South China Sea (Wang et al. 2003). The occurrence area of internal eddies in the South China Sea is mainly from east of Vietnam to southwest waters of Taiwan (Lin et al. 2007), and the life cycle of nearly half of the eddies is 30–60. By the approximate propagation trajectory of eddies in the South China Sea (Fig. 1.5), Combined with relevant studies, it can be seen that cyclonic eddies and anticyclonic eddies have different seasonal variation characteristics, cyclone eddies are prone to occur in winter and anticyclonic eddies are prone to occur in summer. The life of the anticyclonic eddy is longer than that of the cyclonic eddy (Chen et al. 2011; Wang et al. 2013). In addition to the obvious seasonal variation characteristics, the SCS eddy has the characteristics of inter-annual variation (Wang et al. 2003; Xiu et al. 2010; Cheng et al. 2005; Lin et al. 2007; Chen et al. 2011; Li et al. 2014; Chu et al. 2014). The squares and dots represent the generation and dissipation positions of eddies, while red and blue lines represent the propagation paths of anticyclonic and cyclonic eddies, z1-z4 representing four regions. Previous studies have shown that wind drive is the main factor leading to multiple eddies in the South China Sea. In addition, factors such as Kuroshio intrusion and the interaction between currents and topography also have a certain influence on the generation of eddies in the South China Sea (Li et al. 1998; Yang and Liu 2003; Jia and Liu 2004; Wang et al. 2006b; Yuan et al. 2006; Gan and Qu 2008; Hu et al. 2012). Mesoscale eddies have significant thermodynamic and dynamic characteristics, which can influence the South China Sea thermocline and its thickness (Liu et al. 2001a), thermal and salt transport (Chen et al. 2012; Wang et al. 2012b). Changes in ocean eddies are closely related to local upper ocean heat content and seaair interaction, which further affect ocean circulation (Frenger et al. 2013; Chelton 2013).

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Fig. 1.5 Propagation trajectory of eddy in the South China Sea Chen et al. (2011)

1.2.3 Impacts on Sea and Atmosphere SST is an important indicator of the thermal state of the upper ocean and an important factor in the sea-atmosphere coupled system. The SST of the South China Sea has the characteristics of all time scales of the tropical ocean. The changes in the thermal structure of the upper ocean in the South China Sea have an extremely important impact on the atmospheric circulation, especially on the East Asian monsoon and the weather and climate in southern China. The changes in the thermal structure of the upper ocean in the South China Sea have an extremely important impact on the atmospheric circulation, while the momentum flux is the power source of the ocean current and waves. Latent heat flux is a key term for evaluating air-sea heat flux (Yan 1997; Zeng and Wang 2009), the South China Sea Institute of Oceanology, Chinese Academy of Sciences used voyage sounding observation data to carry out related work on latent heat flux inversion of oceanic atmospheric ducts over the South China Sea and the eastern Indian Ocean. The influence of SST changes caused by ocean fronts and mesoscale eddies on the atmosphere, as well as the subsequent feedback effect of the atmosphere on the ocean, have increasingly become important scientific issues in the study of air-sea interaction (Nonaka and Xie 2003). The northern front of the South China Sea has significant characteristics, such as hot salt fronts, tidal fronts, and upwelling fronts (Wang et al. 2001), and studies have shown that the South China Sea front has a significant impact on the local changes in the surface wind field (Shi et al. 2014).

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Tropical cyclone activity and SST in the South China Sea have obvious interdecadal variations, and the number of eastbound and westbound tropical cyclone paths in the South China Sea has obvious interdecadal or even interdecadal variations. The variation of SST also has an important influence on the formation and evolution of tropical cyclones.

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Chapter 2

The Characteristics of Large-Scale Circulation Dynamics in the South China Sea

The Luzon Strait is the only deep-water channel connecting the South China Sea and the Pacific Ocean. The characteristics of water exchange in this area have been studied by many scholars (Hu et al. 2000; Su 2004). Huang (1983), using historical hydrological data, showed that the spatially alternating east–west currents in the Luzon Strait are characterized by a 4 Sv Luzon Strait transport (LST) in summer, with a direction from the South China Sea to the Pacific Ocean. Guo and Fang (1988) pointed out by analyzing the hydrological observation data in September 1985 that there was a consistent westward invading Kuroshio current (KC) branch in the South China Sea, and the westward volume transport of the branch reached − 11 Sv (0– 1200 m). The research of Shaw and Chao (1994) showed that the water exchange between the Pacific and the South China Sea was mainly concentrated in the upper 300 m of the Luzon Strait, where the surface currents from the South China Sea to the Pacific Ocean occupied the entire strait in August, while alternating north-eastward and south-westward currents occurred in the region deeper than 300 m. Xu et al. (2004) analyzed the hydrological observation data in 1994 and concluded that the water transport from the Pacific Ocean to the South China Sea in summer is about 2 Sv. Tian et al. (2006) analyzed the conductivity-temperature-depth system (CTD) and acoustical Doppler current profiler (ADCP) data in October 2005 and concluded that the westward volume transport was (6 ± 3) Sv. Bao et al. (2009) analyzed the CTD data of the 120° E section from July to August 2007 and concluded that the LST was 3.15 Sv, oriented from the South China Sea to the Pacific Ocean. Zhou et al. (2009) indicated that the LST was 3.25 Sv in September 2006, oriented from the Pacific Ocean to the South China Sea. The above-mentioned different results indicate that LST is quite complex and shows significant seasonal and interannual variability. Due to limited observational data, many authors use models to study LST. Metzger and Hurlburt (1996) showed that the annual average LST is 3.9–4.5 Sv, showing a large seasonal variation. Qu et al. (2004) used the oceanic general circulation model (OGCM) to show that the annual average LST was 2.4 Sv (westward), with the LST reaching a maximum in winter (6.1 Sv, westward) and a minimum in summer (0.9 Sv, eastward). By integrating the LICOM (LASG/IAP Climate system Ocean © Science Press and Springer Nature Singapore Pte Ltd. 2022 D. Wang, Ocean Circulation and Air-Sea Interaction in the South China Sea, Springer Oceanography, https://doi.org/10.1007/978-981-19-6262-2_2

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2 The Characteristics of Large-Scale Circulation Dynamics …

Model) global model over 900 years, Cai et al. (2005) obtained the water exchange characteristics between the South China Sea and its connecting sea and concluded that the annual average LST was 4.063 Sv (westward) and the summer LST is 3.5 Sv (westward). Wang et al. (2009) concluded that the annual average LST was 4.5 Sv (westward), with the maximum flow occurring in December at approximately 7.6 Sv (westward) and the minimum flow occurring in June at approximately 2.1 Sv (westward). The numerical model results can be found to be more in favor of the westward transport of LST all year round. It is well known that the Indonesian Through Flow (ITF) is a major carrier of water and heat transport carrier between the Pacific and Indian Ocean, and is one of the key factors in maintaining the global oceanic heat balance and freshwater equilibrium state. ITF plays an important role in the changes in the global thermohaline circulation. The ITF and its variability have important implications for the heat content of the Pacific warm pool, the pattern of the East Indian Ocean circulation and the overall oceanic thermohaline balance (Verschell et al. 1995), and may have implications for global ocean circulation and climate (Hirst and Godfrey 1993). The South China Sea, as a semi-enclosed basin, is connected to the western Pacific Ocean in the east through the Luzon Strait, to the Indonesian Archipelago waters in the southeast through the Sulu Sea, and to the Indonesian waters in the southwest through the Sunda Shelf and Karimata Strait. Studies have shown that the water transport in the South China Sea is very important to the ITF, with the Luzon Strait inlet flowing out of the South China Sea through the Taiwan Strait, the Karimata Strait and the Mindoro Strait respectively, playing a pivotal role in the ITF. On a seasonal scale, Lebedev and Yaremchuk (2000) showed that the ITF is closely related to the pressure gradient difference between the northern end of the Luzon Strait and the western Banda Sea, with the contribution of the volume transport in the Luzon Strait to the volume transport of the ITF averaging up to about 50%. In winter, the (6.3 ± 1.5) Sv of water in the Luzon Strait injects into the South China Sea and exists through Karimata Strait [(4.4 ± 0.5) Sv] and the Mindoro Strait [(1.9 ± 1.5) Sv], respectively; in summer, the Karimata Strait closes and exists through the Mindoro Strait with a net flow of (4.7 ± 0.6) Sv. When the Mindoro Strait is open, a net cyclonic circulation is formed in the Philippine Islands (Metzger and Hurlburt 1996) and this cyclonic circulation can actually be seen as an extension of the northern equatorial circulation. Fang et al. (2002) used a global oceanic variable grid circulation numerical model and found that the volume and heat transport through the South China Sea into the ITF was 5.3 Sv and 0.57 PW, accounting for about a quarter of the volume and heat transport of the ITF itself. The results of the winter buoy data also confirmed the existence of the South China Sea branch of the Pacific-Indian Ocean during the winter peak period (Fang et al. 2005), which further indicates that the South China Sea is one of the important channels connecting the Pacific and Indian Ocean. The water exchange in the surrounding South China Sea not only plays a very important role on the seasonal scale, but also plays an important role on the interannual scale. The Luzon Strait water exchange will transmit ENSO signals from the Pacific to the

2 The Characteristics of Large-Scale Circulation Dynamics …

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South China Sea, thus playing an important role in the circulation and heat budget (Qu et al. 2004). In general, most studies on the contribution of the South China Sea circulation system to the ITF have been largely based on the climate-averaged or seasonalaveraged aspects, with little attention paid to the long-term scale. Does the South China Sea Circulation participate in the water exchange process in the ITF region as a branch of the Indonesian throughflow, both on average and at long-term scale? What is the extent of its contribution to the ITF? What is the mechanistic process of its dynamical connection? What are the climatic implications? These questions have gradually attracted attention and a series of research results have been obtained as the research progresses. Through continuous research and accumulation, the basic characteristics of the large-scale circulation in the South China Sea have been more clearly understood. Figure 2.1 shows the distribution of large-scale circulation in the South China Sea in winter and summer. One of the most obvious seasonal features of the South China Sea large-scale circulation is the change in the flow direction of the western boundary current. In winter, there is a western boundary current that flows southwest from the northern part of the South China Sea along the South China Sea land slope and turns in the Xisha region to continue flowing south along the land slope. The currents are an important transport channel connecting the North and South China Sea in winter and have an important impact on the heat, salt and volume balance of the South China Sea. In summer, the western boundary current reverses direction and flows northwards from the southern Karimata Strait through the mouth of the Gulf of Thailand and along the coast of Vietnam to the northern part of the South China Sea, and separates into a strong offshore current off the southeast coast of Vietnam. Numerical experiments have shown that the strong western boundary currents in the South China Sea are mainly due to a combination of the strong monsoon and the throughflow (Chen and Xue 2014). While the β effect causes a westward intensification of the marginal sea, strong western boundary current requires a reasonable configuration of winds, currents and topography to be generated. This is also confirmed in other marginal seas: although the Gulf Stream transports a large volume of water into the Gulf of Mexico, the existence of the Florida Strait prevents the inflow from intensifying the western boundary current and the wind stress in the Gulf of Mexico is the smallest among the three marginal seas. The meridional ridge of the Sea of Japan prevents the entire basin from participating in the westward intensification process, and the inflow plays a negative role in the formation of the western boundary current.

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Fig. 2.1 Schematic diagram of South China Sea circulation patterns (Fang et al. 1998). 1. Kuroshio, 2. Loop current, 3. SCS Branch of Kuroshio, 4. NW Luzon Cyclonic Gyre, 5. NW Luzon Cyclonic Eddy, 6. NW Luzon Coastal Current, 7. SCS Warm Current, 8. Guangdong Coastal Current, 9. SCS Southern cyclonic Gyre, 10. Natuna Off-Shelf Current, 11. SCS Southern Anticyclonic Gyre, 12. SE Vietnam Off-Shore Current

2.1 Luzon Strait Water Exchange 2.1.1 Volume Transport in the Luzon Strait Table 2.1 compares the results of volume transportation in the Luzon Strait in summer. In general, numerical models tend to assume that water exchange in the Luzon Strait is transported from the Pacific Ocean to the South China Sea throughout the year, with a transport volume of about 3 Sv. However, hydrological observations are significantly difference. Huang (1983) and Bao et al. (2009) suggest that the water is mainly transported from the South China Sea to the Pacific Ocean in summer, while Xu et al. (2004) and Zhou et al. (2009) show the opposite result. The reason for the inconsistency in volumetric transport may be due to some interannual variability in transport in the region, and also to differences in the estimated profiles. The analysis of Chen et al. (2011) showed that the net transport in the 19°–21.5° N area of the 120° E section in the summer of 2009 was 4.37 Sv, while the net transport in the 19°–21.5° N area of the 120.5° E section was − 2.68 Sv. The significant inconsistency between the two adjacent sections is the result of the complex circulation structure in the Luzon Strait. A similar phenomenon also existed in 1994: the current direction of the 120° E section was significantly different from that of the 120.3° E section (Xu et al. 2004). Therefore, before studying the regional transport in the Luzon Strait, it

2.1 Luzon Strait Water Exchange

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Table 2.1 Comparison of volume transport in the Luzon Strait in summer Research methods

Literature

Time

Volume transportation (Sv)

Calculation area

Numerical mode

Liu et al. (2000)

Climatology

− 2.9

18.8°–22° N along 120.75° E section

Qu et al. (2004)

Climatology

0.9

–

Hydrological observation

Cai et al. (2005)

Climatology

− 3.5

120.5° E section

Wang et al. 2009

Climatology

− 2.1

120.5° E section

Huang (1983)

1966

4

19°–21.5° N along 121° E section

Xu et al. (2004)

1994

−2

18°–22° N along 120° E section

Bao et al. (2009)

2007

3.15

19°–21.2° N along 120° E section

Zhou et al. 2009

2006

− 3.25

19.1°–21.3° N along 120° E section

Chen et al. (2011)

2009

4.37

19°–21.5° N along 120° E section

Chen et al., (2011)

2009

− 2.68

19°–21.5° N along 120.5° E section

is necessary to distinguish the currents that actually contribute to the water exchange between the South China Sea and the Pacific Ocean. Chen et al. (2011) investigated the water exchange characteristics and circulation structure in the observation area from 21 June to 5 July 2009 using large-area CTD observations in the Luzon Strait. The results show that the Kuroshio shows a “ε” shaped curved path in the upper region east of the 121° E section and the main axis of the Kuroshio gradually moves away from the Luzon Strait as the depth increases. The northern part of the South China Sea shows the northern flank of a cyclonic circulation, while varies considerably due to local eddies. There are three main channels through which South China Sea water enters the Pacific Ocean: the upper region south of Taiwan Island, the upper region north of Luzon Island and the deep region north of Luzon Island (Fig. 2.2). Water entering the Pacific Ocean from the South China Sea is mainly located above 400 m in the 21°–21.5° N region, above 100 m in the 19°–20° N region and below 240 m in the 19°–19.5° N zone, with volume transport of 3.02, 1.07 and 3.43 Sv, respectively. Volume transport from the Pacific Ocean into the South China Sea is − 6.39 Sv, mainly in the 100–500 m layer in the 19.5°–20° N region (4.40 Sv).

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Fig. 2.2 Schematic diagram showing the circulation structure in the Luzon Strait area (Chen et al. 2011). The red line represents the Kuroshio and the Pacific water invading the South China Sea; the blue line represents the South China Sea circulation and the eastward flow into the Pacific

2.1.2 Interannual Variation Characteristics of Water Flux at 120° E Section of the Luzon Strait There is obvious uneven depth distribution in the 120° E section volume transport (Fig. 2.3a): In the three years of 2005, 2007 and 2011, the volume transport direction was west (the positive value was east) and the direction did not change with depth, so the total transport positive pressure structure was significant, showing quasi-positive pressure characteristics; in 2008 and 2013, the volume transport direction of surface water was westward, with a depth of about 200 m, and the volume transport direction of middle layer water changed to east, so the total transport baroclinicity of the section in these two years was significant. While in 2006 and 2009, the surface water volume transport direction was eastward, and at a depth of about 50 m, it changed to

2.1 Luzon Strait Water Exchange

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westward transport and extended to the calculated depth. The overall water transport also showed baroclinicity. Furthermore, the volume transport per unit depth is vertically integrated to obtain the net volume transport of the section. The net volume transport exhibits significant interannual variability (Fig. 2.3b). Among them, the total flow in 2005 was − 11.2 Sv, which was the year with the largest volume transport in the west; the total flow in 2013 was 9.1 Sv, which was the year with the largest volume transport in the east; the volume transport in 2009 was the smallest, only − 1.2 Sv. In 7 years of observations, only 2008 and 2013 showed eastward volume transport occurred in the middle layer. Among them, the formation of eastward transport in 2008 may be

Fig. 2.3 Distribution of volume transport along the depth and total volume transport in each year (Hou et al. 2016) (in Chinese)

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caused by the intrusion of the Kuroshio in the Luzon Strait in that year as a streamjacket invasion (Chen et al. 2011), which produced a large eastward volume transport in the southwestern of Taiwan Island.

2.1.3 Possible Connection Between Water Exchange in the Luzon Strait and Coastal Kelvin Wave The annual average volume transport of the Luzon Strait is 4.81 Sv, and the annual average volume transport of the Taiwan Strait, Karimata Strait and Mindoro Strait is − 1.44, − 1.42 and − 2.27 Sv, respectively. Among them, the annual average discharge of the Mindoro Strait is similar to the estimation result of Qu et al. (2009), and their result is 2.4 Sv. The average discharge of the Balabac Strait is − 0.01 Sv and the Strait of Malacca is 0.27 Sv. Because of their small magnitude and lack of comparability, the flow of the Balabac Strait and the Strait of Malacca is not further discussed later. The seasonal variation of the volume transport of the four strait channels obtained by using BRAN (Bluelink Reanalysis) data are shown in Fig. 2.4. The volume transport of the Luzon Strait enters the South China Sea all year round, with the strongest in December. The maximum outflow from the Karimata Strait occurs in the mid-winter and flows northward into the South China Sea in summer. The Taiwan Strait flows out of the South China Sea all year round, with the strongest in summer and weaker in winter. The maximum outflow of Mindoro Strait also occurs in October to December in autumn and winter. In terms of interannual variation, the sea surface height anomalies obtained using BRAN data are basically consistent with the satellite altimeter data. The results show that the anomalous wind field in the equatorial western Pacific will stimulate the oceanic Rossby wave response before El Niño occurs. Six months before El Niño, there was a negative anomaly in the sea surface height in the western Pacific, implying that the depth of the thermocline began to shrink (Fig. 2.5a). Four months before El Niño, the sea surface height along the west coast of the Philippines and throughout the western Pacific and eastern Indian Ocean began began to adjust simultaneously. On the west coast of the Philippines, that is, the sea surface height in the near-shore area of the southeastern of the South China Sea will be adjusted quickly. The adjustment of the negative anomaly seems to be in the form of a Pacific Rossby wave excited coastal Kelvin wave from the southern part of the Philippine islands (Mindoro Strait) into the Southeastern part of the South China Sea (Fig. 2.5b). 0–2 months before the occurrence of El Niño, the adjustment of the negative sea surface height anomaly in the southeastern part of the South China Sea was completed. In addition, the adjustment of the negative sea surface height anomaly could affect the vicinity of the mouth of the Luzon Strait (Fig. 2.5c, d). At the latitude where the Mindoro Strait is located, the width of the strait is half the deformation radius of the average baroclinic Rossby wave (about 100 km). The theoretical model indicates that the coastal Kelvin wave can pass effectively. After

2.1 Luzon Strait Water Exchange

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Fig. 2.4 The volume transport characteristics of the four strait channels in the South China Sea averaged from January to December (Liu et al. 2011). Positive values represent volume transport into the South China Sea

entering the South China Sea, the Kelvin wave signal can be traced northward along the west coast of the Philippines to the mouth of the Luzon Strait (Fig. 2.5b). At the same time, the coastal Kelvin wave can further stimulate the Rossby wave to adjust the dynamic process in the South China Sea (Fig. 2.5c, d). The distribution of the contemporaneous correlation coefficient between the temperature anomaly of the 15.5° N section of the South China Sea and the Niño3.4 index can be used as an indirect evidence for the intrusion of the coastal Kelvin fluctuation into the southeast of the South China Sea through the Mindoro Strait (Fig. 2.6). Numerical experiments on the dynamic process of the Kelvin wave affecting the South China Sea through the Mindoro Strait using the half-reduced gravity model (Fig. 2.7) show that the anomaly of the equatorial Pacific wind field will excite the thickness anomalies on both sides of the equator and propagate westward in the form of Rossby waves. When the Rossby wave reaches the western boundary, it will excite the coastal Kelvin wave, thus entering the eastern Indian Ocean and the southeastern part of the South China Sea. In addition, the energy above about 50 × 109 cm3 /s2 enters the South China Sea through the Mindoro Strait, and its energy is more than 5% of the energy entering the Indian Ocean. In addition to affecting the interior of the South China Sea, its fluctuation process may further affect the dynamic process at the mouth of the Luzon Strait. But the problem is that the Mindoro Strait channel is relatively narrow, and the resolution of the model is low, so the energy entering the South China Sea may be underestimated.

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Fig. 2.5 The advanced correlation between the BRAN sea surface height anomaly and the Niño3.4 index (Liu et al. 2011). a–d respectively represent the height anomaly of the sea surface ahead of the Niño3.4 index by 6, 4, 2, 0 months

Although on the seasonal scale, the Karimata Strait is an important outflow channel, on the interannual scale, the Mindoro Strait is the channel with the most pronounced interannual variability in outflow (Fig. 2.8). In terms of interannual variability, the temporal variability of the Mindoro Strait is in good agreement with that of the Luzon Strait. The consistency of the interannual variability of the two strait channels can be explained by the coastal Kelvin wave theory. Because during El Niño, the near-equatorial upper layer Rossby wave excited by the anomalous easterlies in the Pacific equator reach the western boundary, that is, the east coast of the Philippines, and will excite coastal Kelvin wave. The excited Kelvin wave follow the west coast of the Philippines from the Sulawesi Sea to Sulu. The sea spreads northward and enters the South China Sea via the Mindoro Strait (Fig. 2.9). The propagation of the coastal Kelvin wave may have an impact on the negative sea surface height in the southeastern of the South China Sea during El Niño and the large volume transport in the Mindoro and Luzon Straits (Liu et al. 2011). Thus, the importance of the coastal Kelvin wave to the communication between the South China Sea and the Pacific Ocean is clarified. Zhuang et al. (2013) once again confirmed that the consistent low-frequency variation in the Pacific Ocean, Mindoro Strait, and the eastern South China Sea is not caused by the role of local wind fields, but is closely connected

2.1 Luzon Strait Water Exchange

27

Fig. 2.6 Correlation coefficient distribution of temperature anomalies at 15.5° N section and Niño3.4 index over the same period (Liu et al. 2011)

Fig. 2.7 The thickness anomaly distribution characteristics of a first-level semi-reduced gravity model driven by the equatorial Pacific wind anomaly in October 1997 (unit m) (Liu et al. 2011)

through a fluctuating process. If the Mindoro Strait is closed, the north–south movement of the North Equatorial Current bifurcation point and the time variability of the Kuroshio Current will be weakened accordingly.

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Fig. 2.8 Interannual anomalies of the volume transports through the Luzon, Mindoro and Karimata Straits (Liu et al. 2011)

Fig. 2.9 Schematic diagram of the topographic characteristics and fluctuation process of the South China Sea and its surrounding waters from the Pacific Ocean through the Mindoro Strait and affecting the South China Sea (Liu et al. 2011). Dark gray represents land; lightly shaded areas denote water depth shallower than 200 m as derived from the ETOPO5 dataset. The bold lines are chosen for estimating the respective volume transports through Luzon, Taiwan, Karimata, Mindoro, Balabac, and Malacca Straits from BRAN

2.2 South China Sea Through Flow

29

2.2 South China Sea Through Flow 2.2.1 Variation Characteristics of the South China Sea Throughflow 2.2.1.1

Island Circulation Theory

Godfrey (1989) proposed the Island rule by using the Sverdrup theory of continuous pressure and linear inviscidity. And by using HR (Hellerman & Rosenstein) wind stress data, a reasonable magnitude estimate of ITF is given. The ITF obtained by Godfrey (1989) using the circum-island circulation theory is related to the integration of the zonal wind stress in the equatorial Pacific and South Pacific and the coastal wind stress components on the western border of South America and Australia along their respective paths. Wajsowicz et al. (1993) further perfected and improved the theory of circulation around islands, and gave a modified expression for the theory of circulation around the islands under the conditions of seabed topography and friction. Using Godfrey (1989)’s inviscid, depth-integrated Sverdrup theory, we diagnose the volumetric transport through the Luzon Strait, the main inflow channel flow of the South China Sea throughflow. The volume transport of the Luzon Strait is an important part of the variation of the South China Sea throughflow, so the volume transport at the Luzon Strait can be used as an important index indicating the South China Sea throughflow. The specific expression is as follows:  T0 =

τ (l) dl/[ρ0 ( f D − f A )]

(2.1)

ABCD

In the formula, T0 is the island circulation volume transport; ρ0 = 1035 kg/m2 is the average density of seawater; ABCD is the integrated path of the wind fields, see Fig. 2.10; τ (l) is the wind stress component along the integrated path of the wind fields; f D is the Coriolis parameter at the northernmost end of the integral loop (taken as 18.75° N); f A is the Coriolis parameter at the southernmost end of the integral loop (taken as 4.75° N). In order to verify the rationality of the SCSTF obtained by the theoretical integration of the circulation around the island, the simulation results obtained by the SODA_1.4.2 (from 1958 to 2001, using ERA40 wind farm drive) and SODA_1.4.3 models (from 2002 to 2004, using QuickSCAT wind farm drive) were compared (Carton and Giese 2008). Integrating the east–west velocity along the profile (17.25°– 23.25° N, 120.25° E) from the surface to the bottom layer yields the magnitude of the SCSTF simulated by the model. The results show that the average SCSTF value obtained by SODA (Simple Ocean Data Assimilation Ocean) is 1.5 Sv, which is in a reasonable range of SCSTF estimation. According to the theory of circulation around the island, the South China Sea throughflow is mainly controlled by the linear integral effect of basin-scale wind

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2 The Characteristics of Large-Scale Circulation Dynamics …

Fig. 2.10 ABCD schematic diagram of the synthetic wind stress anomaly field during El Niño period and the theoretical wind stress integral path of the circulation around the island (Wang et al. 2006). The selection criteria for anomalous fields are that the volume transport value of the Luzon Strait obtained by theoretical integration of the island circulation is greater than 1.5 Sv and the value of the Niño3.4 index is greater than 0.4 °C. The red vector part represents that the wind stress composite field has passed the significance test with 95% confidence. The numbers 1, 2 and 3 represent the Luzon Strait, Karimata Strait and Mindoro Strait respectively

stress (Fig. 2.10). If the influence of friction in the Taiwan Strait (about 2 Sv), Bering Strait (about 0.8 Sv) and the Philippine Islands are not considered (Qu et al. 2000), the integral of wind stress along the ABCD path can roughly represent the volumetric transport of the South China Sea throughflow quantity. However, the theory of circulation around the island is only applicable in the case of static equilibrium and ideal fluid. For a strait as narrow as the Luzon Strait, friction effects and other dynamic effects cannot be completely ignored. Factors such as strait width and bottom topography can affect the average magnitude and variation of the South China Sea throughflow. But this paper mainly discusses the adjustment effect of the dynamic process of wind stress at the basin scale on the interannual and interdecadal variation characteristics of the South China Sea throughflow. It should be pointed out that the source of wind stress data will have a certain impact on the diagnosis results of the South China Sea throughflow. Comparing the wind stress data provided by the old SODA product (Carton and James 2005) with the HR wind stress product, it can be seen that the value of the South China Sea throughflow obtained by SODA wind stress integral is smaller than the volumetric transport estimated by HR. The large volume transport calculated from HR wind stress may be related to the large HR wind stress itself (Hellerman and Rosenstein 1983). Meng et al. (2004) applied the theory of circulation around the island, combined with SODA data, and made a mechanistic discussion on the variation characteristics of ITF.

2.2.1.2

The Interannual Variation of the South China Sea Throughflow and Its Relationship with ENSO

We obtained the interannual variation characteristics of SCSTF from 2 to 7.5 years using band-pass filtering. Whether it is the original time series or the time series after band-pass filtering, the variation characteristics show that the South China Sea throughflow anomaly obtained by the SODA model integration is basically consistent

2.2 South China Sea Through Flow

31

with the South China Sea throughflow anomaly obtained by the theoretical integration of the circulation around the island (Fig. 2.11). The correlation coefficient for the same period can reach 0.32 (passed the significance test with a confidence level of 90%). The mean square deviations of the South China Sea throughflow after bandpass filtering are 2.3 (the theory of circulation around the island) and 0.4 (SODA model). Although the friction effect is not considered in the theory of the circumisland circulation, the magnitude of the South China Sea throughflow will be slightly larger, but basically, its interannual peaks and troughs are basically consistent with the results of SODA model. Of course, there are some differences between the two years, such as 1965–1966, 1979–1980, 1981, 1982–1984, 1992–1994, 1998–1999. The difference may be related to some approximate processes adopted by the theory of circulation around the island, such as the neglect of friction effects and nonlinear effects.

Fig. 2.11 The South China Sea throughflow anomaly obtained from the theoretical integration of the island circulation (a), the South China Sea throughflow anomaly obtained from the SODA model integration (b), and the South China Sea throughflow anomalies obtained from the theoretical integration of the circulation around the island after filtering for 2–7.5 years (c, thick solid line), and the anomalous components of the South China Sea throughflow obtained from the integrated wind stress at the southern end (c, thin solid line) and the integrated wind stress at the northern end (c, thin dashed line) (Wang et al. 2006). The thin solid lines in the figures a and b represent the original abnormal signals, and the thick solid lines are the 2–7.5 years part obtained after band-pass filtering

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2 The Characteristics of Large-Scale Circulation Dynamics …

Fig. 2.12 The volumetric transport of the South China Sea throughflow output by LICOM and SODA (Wang 2010). The seasonal cycles are subtracted for each time series, and then band-pass filtering is used to extract the interannual variation characteristics of 2–7.5 years

At the same time, we also simulated the interannual variation characteristics of the South China Sea throughflow using the climate system ocean model (LASG/IAP climate system ocean model, LICOM) (Liu 2002) developed by the State Key Laboratory of Atmospheric Sciences and Geophysical Fluid Dynamics (LASG) Numerical Simulation, Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP). The results show that the annual average South China Sea throughflow volume transport anomaly obtained by using LICOM is 1.82 Sv, which is smaller than the previous simulation results using LICOM (Cai et al. 2005), which may be related to the different forcing fields used in the model. The average South China Sea throughflow simulated by LICOM is very close to the result simulated by SODA, and its interannual variation characteristics are basically similar (Fig. 2.12). The correlation coefficient of the two at the same time period is 0.34, and both pass the significance test with a confidence level of 95%. The simulation results of the LICOM model before 1975–1976 were in good agreement with the SODA assimilation data (only the model from 1964 to 1967 could not obtain a result consistent with the trend of the assimilation data), and the consistency after is relatively poor, which may be related to the data difference before and after the climate abrupt change (Wang 2010). Previous studies have shown that ENSO in the Pacific Ocean can enter the South China Sea through the water exchange of the Luzon Strait, thereby affecting the dynamic and thermal variation characteristics of the interior of the South China Sea (Qu et al. 2004). During El Niño, the South China Sea throughflow is abnormally high, and during La Niña, the South China Sea throughflow is abnormally low. Qu et al. (2006) pointed out that when the South China Sea throughflow is 4 months ahead of the Southern Oscillation Index (SOI), its correlation coefficient reaches the maximum at 0.48. The abnormal maximum (small) value of the South China Sea throughflow leads (lags) El Niño (La Niña) by about one month. Our research results show that the South China Sea throughflow anomaly obtained using SODA assimilation data is about 6 months ahead of the Niño3.4 index (Fig. 2.10). The specific reason is not particularly clear and it may be related to the adjustment process of monsoon changes on the South China Sea throughflow.

2.2 South China Sea Through Flow

2.2.1.3

33

The Interdecadal and Long-Term Characteristics of the South China Sea Throughflow

In addition to the significant interannual variation, the South China Sea throughflow also has significant interdecadal and long-term trends. The interdecadal variation of the South China Sea throughflow and the interdecadal variation of the ITF have significant antiphase characteristics. When the ITF is at a low value stage, the South China Sea throughflow is at a high value stage, and vice versa, which is similar to the variation characteristics of the two on the interannual time scale (Fig. 2.12). However, there is a certain phase difference between the interdecadal changes, which may be related to the different responses of wind fields and currents in different sea areas to the Pacific decadal oscillation (PDO) (Liu et al. 2007). On this basis, Yu and Qu (2013) further explored the relationship between the South China Sea throughflow and PDO changes. They pointed out that the contemporaneous correlation coefficient between the South China Sea throughflow and the PDO index is 0.6 (passing the significance test with a 95% confidence level), which suggests that the SCSTF increases when the PDO is in positive phase. PDO had a significant climate abrupt change around 1977, and this abrupt change was also obvious in the South China Sea throughflow (Figs. 2.13, and 2.14). In addition to the obvious interdecadal changes, the SCSTF also has a certain linear trend. The SCSTF showed an overall increasing trend from 1958 to 2006, and the most obvious in autumn and winter (Liu et al. 2007, 2010, 2012a).

Fig. 2.13 The interdecadal characteristics and linear trend characteristics of SCSTF (a) and ITF (b) after the 8-year cycle are filtered out from the model (solid line) and the theory of circling the island (dotted line) (Liu et al. 2007) (in Chinese). The SCSTF value obtained by the model integration has been multiplied by 3 times; the 9-point average time series correlation coefficients for the same period reached 0.23 (a) and 0.5 (b) respectively

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Fig. 2.14 Time series of Niño3.4 index, upper 465 m heat content (1021 J) and regional integral average sea surface dynamic height (Liu et al. 2012a)

Figure 2.15 shows the probability distribution function of SCSTF anomaly estimated from the circum-island circulation theory and SODA assimilation products. The results show that the SCSTF average anomaly shifted in a positive direction after 1975, indicating an increase in net westward volumetric transport through the Luzon Strait into the South China Sea. And the probability distribution characteristics of SCSTF anomalies obtained from SODA assimilation products (Fig. 2.15b), the positive offset after 1975 is larger than the result obtained from the theory of circulation around the island (Fig. 2.15a). Both Vecchi et al. (2006) and Alory et al. (2007) pointed out that the equatorial easterlies would weaken after the 1976/1977 abrupt climate change. Therefore, the anomaly of the Pacific wind field is also an important reason for the abrupt climate change of SCSTF. On the interdecadal time scale, the advection effect caused by the South China Sea throughflow is closely related to the interdecadal variation of the heat content in the inner South China Sea (Song et al. 2014). Using the temperature data of the World Ocean Dataset (WOA09) expendable Bathythermograph (XBT), the changes in ocean heat content above 400 m in the South China Sea (0°–25° N, 90°–121° E) were calculated. Before using the XBT data, we first performed a quality control analysis of the XBT temperature profile, excluding data flagged as poor and out

2.2 South China Sea Through Flow

PDF of the LST estimated by "IR" Number of Observations

Fig. 2.15 SCSTF probability distribution function graph (Liu et al. 2010)

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of standard deviation control. Through step-by-step quality control, the geographic distribution of XBT data including 23,356 temperature sections in the South China Sea is shown in Fig. 2.16. Figure 2.17 shows the vertical profile of the average temperature anomaly in the South China Sea and the variation of the upper layer heat content with time. The results show that there are two typical peaks and troughs in heat content from 1958 to 2007. The interdecadal variation characteristics of the vertical temperature profile displayed by the SODA data are more obvious than those of XBT data. In 1964 and 2000, there were very obvious cold and warm anomalies. In addition, there was a clear upward trend in temperature in the last ten years. The temporal variation of the upper heat content of the upper layer obtained by XBT and SODA is basically the same. Therefore, SODA products will be used for heat content diagnostic analysis later. In the Luzon Strait (Area 1), neither the net heat flux nor advection can explain the variation characteristics of the upper ocean heat content here (Fig. 2.18a), which is mainly affected by the Kuroshio, and its dynamic process is very complex (such as the strong Kuroshio accompanied by complex mesoscale eddy and diffusion features, etc.). For Area 2 and 3, they are both located inside the South China Sea and are also

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Fig. 2.16 Geographical distribution of XBT data of 23,356 temperature sections in the South China Sea (Song et al. 2014). Select 3 regions in the figure (frames in the figure) for spatial difference analysis. The rightmost box represents the Luzon Strait; the middle box represents the sea west of Luzon Island; the leftmost box represents the Xisha warm vortex area

affected by the Pacific inflow. Region 3, located at the location of the Xisha warm vortex, is the upstream of the western boundary current and the possible source of the South China Sea warm current. The change in heat content here is mainly affected by the advection effect (Fig. 2.18c). Region 2, located west of Luzon Island, is connected to the Pacific Ocean through the Mindoro Strait, so the influence of advection effects is also very pronounced (Fig. 2.18b).

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Fig. 2.17 The average temperature anomaly of the South China Sea (excluding seasonal average) and the time series of upper heat content obtained from this (Song et al. 2014). a XBT; b SODA. Four time periods are marked at the same time: P1 is from 1958 to 1968; P2 is from 1969 to 1981; P3 is from 1980 to 1990; P4 is from 1993 to 2003

2.2.2 The Dynamic Mechanism of the Variation in the South China Sea Through Flow 2.2.2.1

Pacific Large-Scale Wind Field

In order to explore the relationship between the Pacific wind field and SCSTF, the distribution characteristics of the Pacific zonal wind and SCSTF over the same period are given (Fig. 2.19). From the correlation coefficients of the same period, it can be seen that the tropical Pacific wind anomaly is an important factor affecting the interannual variation characteristics of the two. Figure 2.11c shows the 2–7.5-year filtering characteristics of the volume transport components along the ABCD total integral path obtained by using the circum-island circulation theory and the volumetric transport components obtained by integrating the wind stress at the north and south ends of each path, so as to evaluate the contribution of each integral link to the SCSTF. Compared with the contributions of the AB and CD segments of the ocean, the contributions of the BC and DA segments are basically negligible. The analysis results show that the magnitudes of volumetric transport changes obtained by integrating wind stress along the southern (AB) and northern (CD) ends of the Philippine

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Fig. 2.18 The average heat content change, net heat flux and advection anomalies in the South China Sea (Song et al. 2014). Area 1 is the Luzon Strait; area 2 is the sea west of Luzon Island; area 3 is the Xisha warm vortex area. HCC stands for abnormal heat content change; QNET stands for net heat flux abnormality; ADV stands for advection abnormality

islands are roughly equivalent, and they are the main factors controlling the interannual variation in overall volumetric transport. During El Niño, the equatorial Pacific showed westerly anomalies (Fig. 2.10), and the volume transport through the Luzon Strait into the South China Sea increased, driven by zonal westerly anomalies.

Fig. 2.19 Correlation distribution characteristics of Pacific zonal wind and SCSTF over the same period

2.2 South China Sea Through Flow

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The mean square deviation of the volume transport component integrated along the south end was 1.78, and the mean square deviation of the volume transport component integrated along the north end was 1.23. From the point of view of correlation in the same period, the correlation coefficient between volume transport and total volume transport obtained by integration at the southern end can reach 0.82, which is higher than the correlation coefficient between volume transport and total volume transport obtained by integration at the north end (0.63). In some years, the integrated volume transport at the north end will increase the variation of the total volume transport, while in some years, the variation of the total volume transport will be weakened. In general, the SCSTF anomalies derived from the circum-island circulation theory mainly contribute to the wind stress anomalies in the Pacific equatorial region. Of course, the zonal wind in the subtropical region west of 160° E on the east side of the Luzon Strait is also an important factor affecting its changes (Fig. 2.19). The average anomaly of SCSTF obtained from the theory of circulation around the island was − 0.42 Sv before 1975, and the average anomaly after 1975 was 0.29 Sv, an overall increase of 0.71 Sv. According to the integral analysis of each segment of the circulation theory around the island, the southern boundary has increased by − 0.17 Sv, and the northern boundary has increased by 0.81 Sv. This indicates that, on a long-term scale, the integral of wind stress along the northern end is the main contributor to the overall increase in SCSTF. In addition to the anomalous easterly component in the eastern Luzon Strait, the abnormal northerlies in the interior of the South China Sea also causes the SCSTF to increase after 1975. Previous studies have shown that the driving of local wind fields and the propagation of Rossby waves in the western Pacific also play a very important role in the variation of SCSTF (Wyrtki 1961; Liu et al. 2000; Hu et al. 2000). To this end, the next section focuses on the influence of the monsoon system on the variation characteristics of SCSTF.

2.2.2.2

Monsoon System

Liu et al. (2000) discussed the variation characteristics of cross-section discharge in the Luzon Strait using the measured data of oceanographic surveys, sea level height data and models. They pointed out that during the prevailing northeast monsoon (from October to February), the flow into the South China Sea through the Luzon Strait is much larger than the flow out of the South China Sea, and the difference between the two can reach 8 Sv. This shows that when the northeast monsoon prevails, more water will flow out of the South China Sea from other straits in the southern part of the South China Sea. In summer, under the influence of the local southwest monsoon, the surface water flows from the South China Sea to the Pacific Ocean, and the local wind field has an obvious effect on the volume transport of the Luzon Strait (Wyrtki 1961). Previous studies have also showed that, in addition to the large-scale wind field in the Pacific Ocean, which will affect the variation of SCSTF, the variation of wind stress in the interior of the South China Sea will also have an impact on the SCSTF (Liu et al. 2010). The monsoon affects the seasonal variation of the Kuroshio intrusion into the South China Sea by changing the distribution characteristics of the

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sea surface height field in the South China Sea (Metzger and Hurlburt 1996; Chao et al. 1996). To further explore the relationship between the monsoon system and SCSTF variation, we separately analyzed the SCSTF characteristics in summer (average from June to August) and autumn (average from September to November). The results showed that the SCSTF obtained by SODA showed positive anomalies from December to April of the following year before 1976, and negative anomalies after 1976. The May–November period was negative anomalies before 1976 and positive anomalies after 1976. The seasonal variation characteristics of SCSTF based on the theory of circulation around the island are similar to the results obtained from SODA assimilation products except that the result of May is inverse to that of SODA. In general, the average SCSTF anomaly showed a continuous decreasing trend in winter and spring, and a continuous increasing trend in summer and autumn. Figure 2.20 shows the SCSTF abnormal time series and its linear trend change using SODA assimilation products. The results showed that the SCSTF anomalies had a decreasing trend in winter and spring, but the decreasing trend did not pass the 95% confidence level significance test (Fig. 2.20a, b). The average SCSTF anomalies in summer and autumn showed an increasing trend, and the increasing trend passed the significance test with a confidence level of 95% (Fig. 2.20c, d). According to the SCSTF anomaly results based on the theory of circulation around the island, the same conclusion was also obtained. The average SCSTF anomaly obtained by SODA is − 0.33 Sv before the climate abrupt change in summer and 0.20 Sv after the climate abrupt change; the average value before the climate abrupt change in autumn is − 0.61 Sv, and after the climate abrupt change is 0.37 Sv. The average values of SCSTF anomalies obtained from the circum-island circulation theory before and after the abrupt climate change were − 0.29 and 0.18 Sv in summer, and − 0.50 and 0.31 Sv in autumn, respectively. The SCSTF variation trends obtained by SODA and the circum-island circulation theory are 0.17 Sv/10a and 0.18 Sv/10a in summer, and 0.27 Sv/10a and 0.19 Sv/10a in autumn (Liu et al. 2012b). Previous studies have shown that the intensity of the South China Sea summer monsoon is closely related to ENSO events (Zhou and Chan 2007). Therefore, the increasing trend of the summer seasonally averaged SCSTF anomaly may be related to the weakening of the summer monsoon. In summer, the southeasterly stress in the South China Sea weakened after the abrupt climate change; in autumn, the northeast monsoon in the South China Sea strengthened after the abrupt climate change. Therefore, in summer and autumn, the wind stress inside the South China Sea shows the northeasterly anomaly after the abrupt climate change, and the interior of the South China Sea shows the center of positive wind stress curl anomaly. This shows that with the abnormal northeasterly in the South China Sea after the abrupt climate change, more and more Pacific water bodies enter the South China Sea through the Luzon Strait. There may be doubts here. Since the circum-island circulation theory mainly reflects the impact of large-scale Pacific wind field on the SCSTF, why does the June–August SCSTF derived from the circum-island circulation theory also show an increasing trend in the past 50 years? Further analysis shows that in summer,

2.2 South China Sea Through Flow

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Fig. 2.20 The four seasons average time series (bar) and long-term trend (oblique straight line) of the SCSTF obtained from SODA assimilation products (Liu et al. 2012b). Thin solid lines denote linear trend and 3-point running mean of LST. Correlation and significance test for regression (Pvalue) are given by ‘R’ and ‘P’, respectively. If the P value is marked with * (that is, the P value is less than 0.05), it indicates that the linear regression is significant

when the northeasterly stress is anomalous in the interior of the South China Sea, the southeast of the Philippines is characterized by southwesterly stress anomalies, and the northwest Pacific (east side of Luzon Strait) is characterized by easterly anomalies. These associated Pacific wind field anomalies are the main reasons for the theory of circum-island circulation to reflect that the SCSTF shows an increasing trend from June to August.

2.2.2.3

Adjustment of Ocean Circulation Force Process

During El Niño, the equatorial Pacific exhibits westerly anomalies (Fig. 2.10). Driven by the westerly anomalies, more Pacific water will enter the South China Sea through the Luzon Strait. Then, what is the adjustment process of ocean circulation driven by the wind field? It is well known that changes in the equatorial Pacific trade winds are closely related to changes in the North equatorial current (NEC), North equatorial countercurrent (NECC) and South equatorial current (SEC) (Wyrtki 1974) (Fig. 2.21). During El Niño, the positive wind stress curl in the Northwest Pacific leads to an increase in the westward flow of the NEC through the Sverdrup dynamic process (Qiu and Lukas 1996), an increase of the eastward flow of NECC, and a decrease of the westward flow of SEC. The correlation coefficient between SCSTF and NEC index obtained from the theory of circum-island circulation is 0.16. When SCSTF leads is NEC index by 6 months, the correlation coefficient is the largest, which is 0.62; the contemporaneous correlation coefficient with NECC index is 0.55, and the contemporaneous correlation coefficient with the SEC index north of the equator is − 0.67. There is a close relationship between the changes of Kuroshio current, the flow change of North Equatorial Current and the north–south movement of the bifurcation

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Fig. 2.21 Time series of the North Equatorial Current (NEC) Index, the North Equatorial Countercurrent (NECC) Index and the South Equatorial Current (SEC) Index Anomalies on the North and South Sides of the Equator obtained from sea surface observation data (Liu 2005). Positive/negative values represent increased/weakened circulation

point of North Equatorial Current (NEC). The equatorial circulation system driven by the large-scale wind field in the Pacific Ocean can make the ENSO signal at low latitudes affect the mid latitude circulation system through the western boundary current (Qiu et al. 1996). Kim et al. (2004) pointed out that there is a close relationship between the north–south movement of the NEC bifurcation point and ENSO on the interannual time scale, and the contemporaneous correlation coefficient between the NEC bifurcation point near the thermocline depth and the Southern Oscillation Index can reach 0.8. The movement of NEC position is mainly related to the westward propagation of the ascending (descending) Rossby wave. In addition, the change of the Kuroshio current will have a certain impact on how much the Pacific Ocean enters the South China Sea through the Luzon Strait. The theoretical study by Sheremet (2001) showed that the variation of the western Pacific boundary current will produce a phenomenon similar to the “teapot” effect, which will have an impact on the SCSTF. That is, when the inertial boundary flow crosses a gap at the western boundary, if the strength of north–south advection term of the potential vortex can overcome the β effect, it will be difficult for the fluid to flow into this gap under the action of inertia; and when the north–south advection transport is lower than a certain critical value (depending on the channel width, β effect and the horizontal and vertical scale of the jetted fluid), some fluid flows into the gap along the edge. This phenomenon similar to the “teapot” effect is called “overshooting”. The analysis of the model results of Yaremchuk and Qu (2004) shows that when the Kuroshio volume transport is in the range of 15–20 Sv, the inertial force is difficult to overcome the β effect, which is favorable for the water body of the Pacific to flow into the South China Sea along the boundary., which is confirms the theoretical

2.2 South China Sea Through Flow

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results of Sheremet (2001) on a seasonal scale. Yuan and Wang (2011) used a quasigeostrophic reduced gravity model to further diagnose the effect of the western boundary current on strait flow when it flows through a strait under the influence of a vortex. Therefore, there is an overshoot in the ocean, that is, overshoot at the Luzon Strait is an intrinsic factor that causes the SCSTF to strengthen or weaken in ENSO years. The classification of vortices by Wang et al. (2003) indicated that the generation of vortices in the northwestern water of Luzon Island is closely related to the intrusion of the Kuroshio.

2.2.3 The Thermal Dynamics and Climate Effects of the South China Sea Throughflow on the South China Sea There is a branch of the Indonesian throughflow (ITF) in the South China Sea, and SCSTF, as an important branch of ITF, has been included in the relevant indications of international research framework (Gordon et al. 2012). Relevant studies have confirmed that SCSTF plays an important role in the generation of the maximum subsurface velocity in the Makassar Strait, and the existence of SCSTF is an important factor in the vertical structure change of ITF. During El Niño, the difference in freshwater pressure gradient between the South China Sea and Sulawesi Sea due to SCSTF enhancement will cause the maximum southward velocity of the Makassar Strait to occur in the subsurface or deeper. During La Niña, however, its pressure gradient difference disappears, so its maximum southward velocity layer becomes shallow. Therefore, it is of great scientific significance to study the South China Sea throughflow. In order to clearly understand the influence of the South China Sea throughflow on the circulation system in and around the South China Sea, we give a schematic diagram of the South China Sea throughflow (Fig. 1.4). In terms of climatic average, the net volume flux of seawater entering the South China Sea through the Luzon Strait is 1–2 Sv, the net heat flux entering the South China Sea through the ocean surface is 0.1–0.2 PW, and the net volume of freshwater entering the South China Sea through the sea surface is 0.1–0.3 Sv. The fundamental reason why the South China Sea has not continued to warm and lighten is that the perforation of the South China Sea transports this heat and freshwater to adjacent sea areas, thus acting as a cold advection (Qu et al. 2006, 2009; Liu et al. 2012a). In addition to the role of cold advection, the South China Sea throughflow also transports the incoming freshwater of about 0.1 Sv to the surrounding waters, and also plays the role of salinity transport (Qu et al. 2006). Numerical experiments by Tozuka et al. (2007) show that the South China Sea throughflow plays an important role in regulating the heat content transport in the Makassar Strait (there will be a difference of 0.18 PW). In the following, we will discuss the interaction between the South China Sea throughflow and the surrounding waters and their impacts on the circulation system from four aspects.

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2 The Characteristics of Large-Scale Circulation Dynamics …

Thermodynamic Effects of the South China Sea Throughflow on the Inner Region of the South China Sea

For the basin-scale average, the South China Sea will receive a net heat flux of 10– 50 W/m2 from the atmosphere, the net heat flux estimated by OA Flux is 49 W/m2 (Yu and Weller 2007), the one estimated by COADS is 23 W/m2 (Oberhuber 1988), and the one obtained by NCEP obtained 18 W/m2 (Qu et al. 2006). Using SODA assimilation products and the dynamical height data provided by Ishii, we further analyzed the correlation between the South China Sea throughflow and the upper heat content (HC) in the interior of the SCS, and the results confirmed the cold advection effect from the South China Sea throughflow on an interannual scale. (Fig. 2.22). In November, when El Niño occurred at its peak, except for the Vietnam Offshore Current, all others showed cold heat content anomalies (Fig. 2.22a); by September of the recession period, the upper ocean heat content began to be dominated by warm anomalies (Fig. 2.22b). The synthetic field characteristics of the dynamic height anomalies during El Niño are basically the same as the synthetic field characteristics of the heat content anomalies (Fig. 2.22c, d), but because the resolution of SODA assimilation products is relatively high, the vortex characteristics reflected by the synthetic field will be more obvious. The sensitivity test for the closure of the South China Sea shows that after the closure of the South China Sea, the sea surface temperature inside the South China Sea will rise by more than 1 °C. The areas with the most obvious warming are the downstream area of the western boundary current of the South China Sea and the area to the east and south of Vietnam (Tozuka et al. 2009). On this basis, we used the LICOM model of the Institute of Atmospheric Physics, the Chinese Academy of Sciences to further calculate the correlation coefficient between the SCSTF anomaly in the 222 m layer on the model and the heat content anomaly at the same depth at each grid point in the South China Sea (through the significance test with a 95% confidence level) (Fig. 2.23). The negative correlation between the two reflects the cold advection of the South China Sea throughflow (here, the SCSTF flow into the SCS is defined as positive). In terms of time scale, when the upper heat content lags behind the SCSTF for 1–2 months, the significant negative correlation area between the two reaches the maximum, which shows that the response to cold advection is very rapid. The upper heat content lags the SCSTF by 0 months, or even 1–2 months ahead, and there is a significant negative correlation, which may be the red noise when calculating the correlation coefficient. If two time series are highly correlated at a certain moment, the correlation coefficient cannot be immediately reduced to the lowest value when the correlation coefficient is dislocated 1–2 moments. As the lead-lag months further increase, the high-correlation area gradually disappears (Wang 2010). In terms of spatial distribution, the area with significant negative correlation between the two mainly appear in the deep-water basins of the eastern South China Sea. There may be two reasons for this phenomenon: First, the upper heat content of the northern shelf area and the western boundary current area is not significantly correlated with SCSTF, which is probably due to the very complex thermodynamic

2.2 South China Sea Through Flow

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Fig. 2.22 The combined field of heat content anomalies and dynamic height anomalies obtained from the 0–465 m integration of the upper ocean during El Niño. [0] means the first year of the El Nino event; [+ 1] means the second year of the El Nino event

process in this area, and the upper layer heat content is affected by many factors, such as local atmospheric forcing, and the western boundary current is mainly the result of westward strengthening rather than the driving force of Kuroshio intrusion; second, the nearshore physical process is complex. Although the model does not incorporate land runoff, the air-sea heat flux and sea surface temperature (SST) forcing field and lateral boundary effect used in the model forcing site will also become important influencing factors. To this end, we conducted a set of model sensitivity tests with the same forcing field, closing the Luzon Strait, Taiwan Strait, Mindoro Strait, and Kalimata Strait connecting the South China Sea to the outer seas. Figure 2.24 shows the distribution of contemporaneous correlation coefficient of heat content anomalies in the upper layer of the South China Sea (0–222 m layer) in the control test (the South China Sea channel is opened) and the South China Sea channel closed test, thus

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Fig. 2.23 The SCSTF anomaly output by the model is related to the hysteresis of the abnormal heat content in the South China Sea (Wang 2010)

2.2 South China Sea Through Flow

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Fig. 2.24 Contemporaneous correlation coefficient of abnormal heat content in the South China Sea between the control test and the South China Sea channel closure test (Wang 2010)

reflecting the influence of other factors other than the South China Sea throughflow on it. The results show that, compared with Fig. 2.23, significant correlation (positive correlation) areas appear at the outer edge of the deep-water basins, except that for areas there is no data with water depth less than 222 m and the correlation coefficients of some slopes with steep terrain cannot pass the significance test, indicating that the heat content in the upper layers of these areas is affected by many factors, so the influence caused by the South China Sea throughflow is relatively weak. The significant negative correlation area in Fig. 2.23 is also concentrated in the eastern sea area, which may also be due to the influence of advection through the Mindoro Strait and Balabac Strait. These two straits, especially the Mindoro Strait, are also the main channels of the SCSTF. This further shows the overall effect of the South China Sea throughflow on the heat content of the upper layers of the South China Sea. In addition, when the calculation increases to a deeper level, the correlation coefficient between the two will decrease, that is, the South China Sea throughflow mainly affects the upper heat content of the inner South China Sea, and the influence on the middle and lower layers weakens with the increase of depth. The complex dynamic form in which the deep-water waterfalls in the Luzon Strait will affect the thermal changes in the South China Sea needs to be further studied. Calculating the correlation coefficient between the SCSTF anomaly of the control test and the anomaly of the South China Sea upper layer heat content of the South China Sea channel closure test found that the correlation coefficients at each grid

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point were all below 0.05, or failed the significance test. This is because the South China Sea is a semi-enclosed basin, and its multi-time scale changes mainly come from three aspects: local atmospheric forcing, external Pacific forcing, and internal changes in the South China Sea. We closed all channels between the South China Sea and the northwest Pacific Ocean, that is, blocking the Pacific forcing. At this time, the changes in the upper layer heat content of the South China Sea are basically derived from the local atmospheric forcing and internal changes in the South China Sea, which led to the disappearance of the significant negative correlation between the SCSTF anomaly in the control experiment and the heat content of the upper layer of the South China Sea layer in the South China Sea channel closure experiment. The significant negative correlation between the SCSTF anomaly of the control experiment itself and the upper layer heat content of the South China Sea does reflect the cold advection contribution of the South China Sea throughflow, not just a spurious correlation between the two under the same climatic background field. The model experiment of closing the South China Sea channel further confirmed the cold advection contribution of the South China Sea throughflow. The waters of the South China Sea and Indonesian are located in the typical oceanic continental belt of the Indo-Pacific confluence area. The abnormally active atmospheric convection activities make the slight SST and upper-layer heat content changes in this area may lead to severe weather and climate variability. The important climatological significance of the South China Sea throughflow is evident (Qu et al. 2006, 2009; Tozuka et al. 2009; Wang 2010). Further studies show that the changes in the upper layer heat content obtained from SODA data during the six El Niño events (Fig. 2.25a), the heat content changes obtained from the XBT data of the World Ocean Dataset (Fig. 2.25b), and the dynamic height field changes obtained from the Ishii06 data (Fig. 2.25c) are basically the same. Therefore, SODA can be used for quantitative diagnostic analysis of the upper layer heat content. Quantitative diagnosis shows that the cold advection of the South China Sea throughflow during El Niño does play a very important role in the upper heat content of the South China Sea (Liu et al. 2012b) (Fig. 2.26). The time series is a 3-month moving average. The thick black line represents the average characteristics of the remaining five El Niño events after deducting the El Niño from 1965 to 1966. [0] means the first year of the El Nino event; [+ 1] means the second year of the El Nino event. Based on the Aquarius salinity satellite launched by the National Aeronautics and Space Administration (USA, NASA), on-site observation and Argo observation data carried out by the South China Sea Institute of Oceanology, Chinese Academy of Sciences (Zeng et al. 2014), the extreme desalination event in the South China Sea in 2012 was first discovered (Fig. 2.27). The salinity of the upper layer was the lowest in the past 50 years (salinity desalination can reach 0.4 psu and affect the 100 m layer). For the salinity of the South China Sea, the main influencing factors are net freshwater flux, estuarine freshwater outflow, and strait water exchange dominated by the South China Sea throughflow. Different from the local freshwater flux and estuarine freshwater outflow, the South China Sea throughflow brings a large amount of high temperature and high salt water into the South China Sea, and its impact

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Fig. 2.25 The average heat content anomalies from 0 to 465 m in the upper ocean floor obtained from SODA data in the South China Sea during the six El Niño periods, the heat content anomalies obtained from XBT, and the dynamic height anomalies obtained from Ishii06 data (Liu et al. 2012b)

on the salinity of the South China Sea cannot be ignored. In order to evaluate the possible factors that caused the desalination phenomenon in 2012, we simplified the quantitative calculation to give the salinity changes caused by the above factors (Table 2.2), and found that sufficient freshwater flux and less South China Sea throughflow were the main reasons for the desalination of the upper ocean in the South China Sea in 2012. At the same time, it was found that in 2011, when the freshwater flux was more abundant, the salinity of the upper ocean in the South China Sea was significantly higher than in 2012, which means that the influence of the South China Sea throughflow on this interannual variation is particularly important. By comparing the contribution of each influencing factor to the salinity change in 2011 and 2012, the dominant role of the South China Sea throughflow in this interannual difference was further confirmed (Zeng et al. 2014).

2.2.3.2

The Connection Between the South China Sea Throughflow and ITF

After the Pacific waters enter the South China Sea, most of them flow southward along the western boundary of the South China Sea. After flowing out through the Karimata Strait, some of them flow out as surface currents in the Makassar Strait, which play an important role in the interannual variability of ITF heat transport (Qu et al. 2006). Since the water entering the South China Sea is colder, while the water flowing out of the South China Sea is warmer, the oceanic circulation in the South China Sea itself has the effect of cold advection, which also contributes to the meridional circulation in the North Pacific (Qu et al. 2006). On the one hand, based on wind stress estimates and analysis of ocean assimilation data, the interannual variability of SCSTF and ITF are in opposite phase (Liu et al. 2007). The contemporaneous correlation coefficient of the two volume transports

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2 The Characteristics of Large-Scale Circulation Dynamics …

Fig. 2.26 During the six El Niño events, a horizontal advection, vertical advection and total advection composite characteristics, b surface heat flux, surface heat flux and horizontal advection combined and the upper layer 0–465 m heat content change rate composite characteristics (shaded); c is similar to a, and d and b are similar, but there are only two El Niño events from 1982 to 1983 and 1997 to 1998. A positive value represents heat transport into the South China Sea (Liu et al. 2012b). hA represents horizontal advection; vA represents vertical advection; Q represents surface heat flux; HCC represents abnormal heat content change. [0] means the first year of the El Nino event; [+ 1] means the second year of the El Nino event

obtained by SODA model is − 0.67, and the contemporaneous correlation coefficient obtained by the circum-island circulation theory is − 0.57 (Liu et al. 2006). Although the wind field changes in the South Pacific play a certain role in the interannual variability of the ITF and the eastern Luzon Strait, the equatorial wind field variability is the most important factor leading to the inversion of the interannual variability of the ITF and SCSTF. On the other hand, its results further show that ITF and SCSTF are closely related to ENSO events. The contemporaneous correlation coefficients between Niño3.4 index and ITF obtained from the circum-island circulation theory and the ocean model are − 0.77 and − 0.62, respectively, while the contemporaneous correlation coefficients with SCSTF are 0.33 and 0.45, respectively. That is to say, during El Niño, the equatorial Pacific westerly broke out, and the change of the wind

2.2 South China Sea Through Flow

51

Fig. 2.27 The 2012 extreme desalination event in the South China Sea confirmed by the Aquarius salinity satellite, field observations conducted by the South China Sea Institute of Oceanology, Chinese Academy of Sciences, and Argo observation data (Zeng et al. 2014). a The red dots in the figure are the observations of the August 2012 voyage, and the black dots are all observations within 2° around the trajectory of this voyage in the SCSPOD dataset. b, c is similar. In figure d, the thick red and black lines are the observed average profiles of the three voyages in August, October, and December 2012 and the three-month average profile of SCSPOD. The thin red and black lines are the SCSPOD 2012 average profile and the total average profile a. The red dots in the figure are the observation data of the voyage in August 2012, and the black dots are all observations within 2° around the trajectory of this voyage in the SCSPOD dataset. b, c are similar. In figure d, the thick red and black lines are the observed average profiles of the three voyages in August, October, and December 2012 and the three-month average profile of SCSPOD. The thin red and black lines are the SCSPOD 2012 mean profile and the total mean profile

field would lead to a decrease in ITF and an increase in SCSTF, which is the opposite in La Niña years. The above results indicate that the variation of the equatorial Pacific wind field is the main factor leading to the antiphase of SCSTF and ITF on the interannual time scale. So how does the wind field change affect the interannual variation characteristics of SCSTF and ITF through the process of circulation adjustment? Fig. 2.21 shows the equatorial Pacific circulation index defined by Wyrtki (1961). The following will discuss the adjustment of the circulation by combining the circulation index with the results of ocean assimilation. The contemporaneous correlation coefficient between

Salinity variation

Runoff difference

Salinity variation

− 0.41

− 0.34

+ 0.01 − 1397 + 0.03

+ 0.02 − 1730 + 0.03

+ 0.04

− 1877

− 0.01

358

Salinity variation

Flux difference

Salinity variation

Flux difference

− 583

− 1044

Runoff difference

+ 0.14

− 1.12

− 0.10

0.87

CPC

Data sources

GPCP

CPC

Data sources

TRMM

Net freshwater flux (mm/d)

Freshwater outflow from the Pearl River (m3 /s)

2012–2011

2012-Climatology

Changes in salinity in the northern South China Sea

+ 0.19

− 1.49

− 0.07

0.60

GPCP

+ 0.18

− 1.43

− 0.21

1.72

TRMM

Salinity variation

Difference in transport volume

Salinity variation

Difference in transport volume

Data sources

− 0.52

− 1.74

− 0.26

− 0.86

ROMS

Luzon Strait transport volume (Sv)

Table 2.2 Net freshwater flux, freshwater outflow from the estuary, and the change in salinity of the South China Sea caused by the South China Sea throughflow (Zeng et al. 2014)

52 2 The Characteristics of Large-Scale Circulation Dynamics …

2.2 South China Sea Through Flow

53

NEC index and NECC index is 0.74, and the contemporaneous correlation coefficient with the SEC index (the sum of the south equatorial current and north equatorial current) is − 0.48. The correlation coefficient between NECC index and SEC index (the sum of south equatorial current and north equatorial current) can reach − 0.82. As mentioned earlier, the Pacific NEC, NECC, and SEC are closely related to the equatorial Pacific trade wind variation (Wyrtki 1961). During El Niño, the positive wind stress curl in the northwestern Pacific will lead to an abnormal increase in the westward current velocity of the NEC through the Sverdrup dynamic process (Qiu et al. 1996), which is further confirmed by the variation of the NEC bifurcation point simulated by the SODA model (Fig. 2.28). The eastward current of NECC is enhanced, and the westward current of SEC is weakened. The correlation coefficient between SCSTF and NEC index obtained from the theory of circulation around the island is the largest at 6 months, which is 0.62, while the correlation coefficient between ITF and NEC index is − 0.52; the correlation coefficient of SCSTF and ITF and NECC are 0.55 and − 0.78 (Liu et al. 2006). It can be seen that SCSTF (ITF) has a certain positive (negative) phase relationship with the NEC/NECC index, while there is a negative (positive) phase relationship with the SEC index. That is, during El Niño, NEC and SCSTF will increase, while the corresponding NECC/SEC and ITF will decrease.

Fig. 2.28 Normalized time series of NEC bifurcation point, Kuroshio Current (KC) and SCSTF, Mindanao Current (MC) and ITF (Liu et al. 2006). A positive value represents enhanced circulation and northward shift of NEC bifurcation point

54

2 The Characteristics of Large-Scale Circulation Dynamics …

It has been pointed out above that the Kuroshio boundary is prone to the phenomenon of “overshooting” similar to the “teapot” effect. When the Kuroshio volume transport is between 15 and 20 Sv, it is difficult for inertial force to overcome the β effect, which facilitates the flow of water from the Pacific into the South China Sea along the boundary (Yaremchuk and Qu 2004). From the SODA assimilation product, we calculated the average Kuroshio current (KC, 16.75° N) in the range of 2 grid points offshore from 0 to 465 m (Fig. 2.28b). The results show that the contemporaneous correlation coefficients between NEC bifurcation point and the Niño3.4 index and KC are 0.54 and − 0.60, respectively, which are in phase and antiphase, respectively; the contemporaneous correlation coefficient of SCSTF obtained by the same model simulation with KC is − 0.59 (Liu et al. 2006). When the El Niño event occurs, wind field changes lead to the northward shift of the NEC bifurcation point through the Sverdrup dynamic process (Kim et al. 2004), and the baroclinic Rossby wave adjustment leads to the weakening of KC (Tozuka et al. 2002). Based on the nonlinear hysteresis theory of Sheremet (2001), the weak northward transport of the Kuroshio is beneficial for Pacific waters to enter the South China Sea through the Luzon Strait (Yaremchuk and Qu 2004; Qu et al. 2004). Similar to the process of the Kuroshio boundary affecting the SCSTF, when the KC “enters the gap” in the Luzon Strait, a “cross-gap” may appear at the SulawesiMindanao channel (0.75°–6.25° N, 124.5° E). The results of the average Mindanao Current (MC, 7.25° N) in the range of 0–465 m offshore 2 grid points obtained by SODA model show that the correlation coefficient is the largest when the change is 6 months ahead of the NEC bifurcation point, which is 0.31. The NEC bifurcation point and KC are in antiphase, and the same MC is roughly in the same phase although there is a certain time lag in the phase. The MC is negatively correlated with the ITF obtained from the theory of circulation around the island, with a correlation coefficient of − 0.52. This indicates that, on the one hand, the antiphase characteristics of SCSTF (ITF) are closely related to in-gap/transgap process, on the other hand, the antiphase characteristics of both KC and MC are related to the different phase velocities of baroclinic Rossby waves at corresponding latitudes (Qiu et al. 1996), which results in the SCSTF and ITF being out of phase on the interannual scale. Figure 2.29 shows the distribution of synthetic current field anomalies averaged at depths from 0 to 465 m during the abnormal event (the red vectors represent current fields with more than 95% confidence). This clearly shows that during El Niño, the change of the equatorial Pacific wind field through the Sverdrup dynamic process leads to a northward shift of the NEC bifurcation point (Kim et al. 2004), while the NEC is enhanced (Wyrtki 1961; Qiu et al. 1996). Baroclinic Rossby wave adjustments corresponding to different phase velocities lead to an enhancement in MC (Masumoto and Yamagata 1991) and a decrease of KC (Tozuka et al. 2002). Based on the theoretical inference of Sheremet (2001), the weakening of KC is favorable for the Pacific water body to enter the South China Sea through the Luzon Strait, and SCSTF strengthens; the enhancement of MC is unfavorable for the water body to enter the Indian Ocean through the Indonesian channel, and the ITF weakens. When MC increases, NECC increases, but SEC decreases. The change in La Niña years is just the opposite, that is, the NEC bifurcation point moves southward, and the

2.2 South China Sea Through Flow

55

stronger KC leads to the weakening of the SCSTF, while the weakening of the MC leads to the enhancement of the ITF. All in all, the change of the equatorial Pacific wind field causes the adjustment of ocean circulation, which leads to the occurrence of in-gap or cross-gap phenomena in the Luzon Strait and the Sulawesi-Mindanao channel. The interaction of this dynamic process makes the SCSTF anomalies and the ITF anomalies show antiphase on the interannual scale. Based on the assimilation product and diagnosis theory, the anti-phase characteristics mechanism of SCSTF and ITF was discussed in the previous article. However, after SCSTF enters the South China Sea and flows out through the Karimata Strait in the southern part of the South China Sea, what effect does it play on the circulation and heat transport of ITF? What? Studies have shown that the perforation of the South China Sea throughflow transports this heat and freshwater to adjacent sea areas, thereby acting as a cold advection (Qu et al. 2006, 2009). The interannual variation of the heat transport in the SCSTF is in good agreement with the variation in the surface heat content of the South China Sea, but there are still significant differences (Qu et al. 2006). The cold advection of SCSTF will not only affect the heat content of the South China Sea, but also affects the SST and heat content characteristics of

Fig. 2.29 Distribution characteristics of synthetic current field anomalies averaged at a depth of 0–465 m during an abnormal event (Liu et al. 2006). Criteria for selection of abnormal events: the monthly anomaly value of SCSTF obtained from the theory of island circulation is higher than 1.5 Sv, the monthly anomaly value of ITF is lower than 1.5 Sv, and the Niño3.4 sea temperature index is higher than 0.4 °C. The red line represents the significance test with a 95% confidence level. Using the terrain data that comes with Matlab, the sea areas shallower than 100 m are marked with contour lines

56

2 The Characteristics of Large-Scale Circulation Dynamics …

the surrounding waters. The surface circulation in the Makassar Strait is not driven by local winds, but is the result of large-scale wind fields. Tozuka et al. (2007) conducted a simulation experiment using an oceanographic numerical model, and the results showed that the SCSTF had a significant impact on the maximum subsurface velocity in the Makassar Strait. Control experiments show that the maximum southward flow velocity occurs at the subsurface 110 m, while the maximum southward velocity occurs in the surface layer after the South China Sea is closed, indicating that the SCSTF will reduce the maximum southward flow velocity on the surface of the Makassar Strait. The closing and opening of the SCSTF will cause a difference of 0.18 PW in the southward heat transport of the Makassar Strait, which means that the SCSTF has played a very important role in climate change in the Indo-Pacific region. After the SCSTF is turned off, the temperature of the control experiment volume delivery weight is changed from 19.3 to 21.4 °C, and the volume delivery is changed from 4.6 to 6.1 Sv. In addition, the greatest impact of SCSTF occurs in winter, and the existence of SCSTF explains the reason for the strengthening of subsurface flow velocity in the Makassar Strait. At the same time, SCSTF intensified in El Niño years, resulting in a decrease of 0.37 Sv and 0.05 PW in the southward volume transport and heat transport in the Makassar Strait, respectively (Tozuka et al. 2009). Figure 2.30a shows the difference of the circulation anomalies between the 0– 50 m layer of the SCSTF closed and the control experiment (SCSTF open) in El Niño years (1982, 1991, 1997, 2002, 2006). The most obvious difference lies in the clockwise circulation anomalies around the Philippine Islands and Kalimantan. This further shows that when the SCSTF is closed, the southward current velocity in the Makassar Strait is enhanced during El Niño, and the difference is about 34 and 36% of the Makassar Strait volume transport and heat transport control experiments, respectively. The existence of SCSTF will lead to the decrease of the southward flow velocity in the Makassar Strait in El Niño years. The simulation results of the LICOM ocean model give a similar conclusion (Fig. 2.30b) (Wang 2010), and the results further confirm the good performance of the LICOM model in simulating the circulation in the Indo-Pacific Ocean. Fang et al. (2010) used the observation data of the Karimata Strait for the first time to confirm the existence of the South China Sea throughflow (a branch of the Indo-Pacific Ocean), and the average volume transport of the Karimata Strait was (3.6 ± 0.8) Sv. The volume transport of SCSTF in winter plays an important role for ITF. In order to verify the contribution of the Karimata Strait in the southern South China Sea to the outflow of the SCSTF, He et al. (2015) used the BRAN model to conduct particle tracking experiments (Fig. 2.31). The particle tracer results showed that most of the water in the Karimata Strait enters the Indian Ocean in the first half of the year, and its maximum current from March to April can reach 3 Sv. In terms of the annual average, the volume transport of the Karimata Strait contributes about 1.6 Sv to the ITF, which is 13% of the annual average transport of the ITF, and the contribution from February to April reaches more than 20%. On the interannual time scale, more South China Sea water enters the Indian Ocean through the Karimata Strait during El Niño, while the opposite is true in La Niña years. During La Niña

2.2 South China Sea Through Flow

57

Fig. 2.30 a El Niño years (1982, 1991, 1997, 2002, and 2006) November 0–50 m circulation anomaly difference, the shading represents the 90% reliability test (Tozuka et al. 2009); b The difference of anomalous ocean circulation in 0–303 m layer of the abnormal years, the red vector represents the 95% confidence test (Wang 2010)

and the negative Indian Ocean Dipole phase, the waters of the South China Sea also enter the Pacific Ocean through the Karimata Strait. On the seasonal scale, the Karimata Strait is an important outflow channel of the SCSTF, but on the interannual scale, the Mindoro Strait is the channel with the most obvious interannual variability of the SCSTF outflow (Liu et al. 2011). SCSTF is the main reason for ITF formation of subsurface maximum current velocity and seasonal variability (Tozuka et al. 2007, 2009; Wang et al. 2011), thus confirming that the Luzon-Karimata-Makassar Strait is the main channel through which SCSTF regulates ITF variability. Gordon et al. (2012) further confirmed that the increase in SCSTF during El Niño will transport more high-temperature and low-salt South China Sea water through the Mindoro-Sibutu Strait into the Sulawesi Sea, forming a west–east pressure gradient in the upper ocean, which hinders the surface Mindanao stream from entering the Sulawesi Sea, thereby affecting the anomalous characteristic of the interannual variability of the ITF. Utilize a North Pacific Ocean Model [ATOP, the specific model settings can refer to Oey et al. (2013, 2014)] based on the high-resolution Princeton Ocean Model (POM) and observation data, Wei et al. (2016) re-examined the modulation mechanism of SCSTF on ITF on seasonal and interannual scales. The model resolution is 10 km, and the simulation area is 15° S–72° N, 90° E–70° W. The time used is from 2004 to 2012, which is consistent with the time of INSTANT observations. The ATOP model can better simulate the direction and current of NEC-ITF-SCSTF, the vertical

58

2 The Characteristics of Large-Scale Circulation Dynamics …

Fig. 2.31 Particle Tracer Test Results (He et al. 2015). The starting point of the particle release is at the northern end of the Karimata Strait, and the dotted lines represent the particles entering the South China Sea, the Pacific Ocean and the Indian Ocean

structure of ITF in the Makassar Strait, and the seasonal and interannual changes of ITF-SCSTF. The simulation results of Wei et al. (2016) show that the seasonal variability of the South China Sea throughflow along the Luzon-Kalimata-Makassar Strait and the Luzon-Mindoro-Sibutu-Makassar Strait paths are as follows: the current increases in winter and decreases in summer, and the difference in current between winter and summer is about 4 Sv. The variability of the Indonesian throughflow from the Mindanao-Sulawesi channel into the Sulawesi Sea is exactly opposite to that of the South China Sea throughflow, that is, the current decreases in winter and increases in summer, and the difference between winter and summer flow is 5–6 Sv. The South China Sea throughflow in opposite phases merge/offset with the Indonesian throughflow through the Karimata Strait and the Mindoro-Sibutu Strait, respectively, resulting in a relatively weak seasonal variation in the variability of the Indonesian throughflow in the Makassar Strait and is consistent with the Indonesian throughflow rate observed by INSTANT (Fig. 2.32). On a seasonal scale, the branch of the SCSTF along the Luzon-Mindoro-SibutuMakassar Strait path is mainly driven by geostrophic equilibrium, and this branch brings a part of the high temperature and low salinity South China Sea water into Sulawesi Sea, thus forming a pressure gradient from west to east, preventing part of the Mindanao Stream from entering the Sulawesi Sea. In addition, the branch along the Luzon-Karimata-Makassar Strait path is mainly driven by the monsoon, which transports the South China Sea water from the Java Sea into the Makassar Strait,

2.2 South China Sea Through Flow

59

20

14.5

20

14

10

10

0

0

-10

-10

Transport (Sv)

(a) 10 0

13

Apr

Jul

Oct

12.5 -20 Jan

Apr

Jul

-20 Jan

2

2

0

0

0

-2

-2

-2

Jul

Oct

-4 Jan

Apr

Jul

Oct

-4 Jan

(g)

2

0

0

0

-2

-2

-2

Jul

Oct

-4 Jan

Oct

(i)

(h) 2

Apr

Jul

4

4

2

-4 Jan

Apr

Makassar

Sibutu

Karimata 4

Oct

(f)

(e)

2

Apr

Jul

4

(d)

-4 Jan

Apr

Mindanao-Sulawesi

4

4 Transport (Sv)

Oct

Mindoro

Luzon

Transport (Sv)

(c)

(b)

13.5

-10 -20 Jan

MC

KC

NEC 20

Apr

Jul

Oct

-4 Jan

Apr

Jul

Oct

Fig. 2.32 Seasonal variation characteristics of volume transport in the western Pacific circulation system (North Equatorial Current, Mindanao Current and Kuroshio Current) and the main strait channels of SCSTF and ITF (Wei et al. 2016). A positive value represents an anomaly of volume transport to the north and east, and a negative value is an anomaly to the south and west. For comparison, bifurcation point of the north equatorial current and the observed ITF are superimposed on a and i respectively (blue line)

thereby preventing part of the Indonesian throughflow into the Java Sea. On the interannual scale, the branch of the South China Sea throughflow simulated by ATOP along the Luzon-Mindoro-Sibutu-Makassar Strait path has a correlation coefficient of − 0.79 with the Niño3.4 index (volume transport in the Makassar Strait) and − 0.67 (volume transport in the Sibutu Strait), the branch along the Luzon-KarimataMakassar Strait path has a correlation coefficient of 0.14 with the Niño3.4 index (volume transport in the Karimata Strait), while the branch of the Mindanao Stream entering the Sulawesi Sea has a correlation coefficient of 0.61 with the Niño3.4 index. This shows that on the interannual scale, the South China Sea throughflow mainly modulates the Indonesian throughflow through the Luzon-Mindoro-Sibutu-Makassar Strait, while the current of the South China Sea throughflow in the Karimata Strait is

60

2 The Characteristics of Large-Scale Circulation Dynamics …

mainly driven by the monsoon, the modulation effect on the interannual variability of the Indonesian throughflow is almost negligible (Figs. 2.33 and 2.34). 25

6

(a)

Strait 4: Sibutu strait Strait 5: Mindanao-Sulawesi Strait 6: Makassar strait

(b)

0.4

20

4 0.2

Transport (Sv)

15 0

10 4

5 5

0

2 0 -2

6

-4

-5 -10 100

105

110

115

120

125

130

-6 2004

2005 2006 2007

2008 2009

2010 2011

2012

Fig. 2.33 The average sea surface height anomaly from 2004 to 2012 obtained by ATOP model simulation (a) and the volume transport of Sibutu, Mindoro-Sulawesi and Makassar Strait (b) (Wei et al. 2016). In order to reflect the seasonal signal, a 12-point moving average was performed on the time series

2

Transport (Sv)

6

R = -0.74

(a)

2

6

R = -0.79

(c)

2 R = 0.61

(e)

3

1

3

1

3

1

0

0

0

0

0

0

-1 -3

-1 -3

-3 -6 04

06

08

10

-2 -6 04 12

06

2

(b)

08

10

-1

-2 -6 04 12

06

Sibutu

Karimata 6

Transport (Sv)

Mindanao-Sulawesi

Mindoro

Luzon 6

(d)

10

-2 12

Makassar 2

6

R = 0.14

08

2

6

R = -0.67

(f)

R = 0.15

3

1

3

1

3

1

0

0

0

0

0

0

-6 04

06

08

10

-2 -6 04 12

-1

-1 -3

-1 -3

-3

06

08

10

-2 -6 04 12

06

08

10

-2 12

Fig. 2.34 The Niño3.4 index and the interannual variation characteristics of volume transport of channels in each channel. The Niño3.4 index is plotted for reference (green lines). The red lines are monthly averaged results, and blue lines are the 12-month running means, used to filter out seasonal variations (Wei et al. 2016). The marked correlation coefficient is the correlation between the blue line and the green line

2.2 South China Sea Through Flow

2.2.3.3

61

The Impact of the South China Sea Throughflow on the Western Pacific Circulation

The NEC bifurcation controls the volume and thermohaline distribution of the Kuroshio and the Mindanao Currents, thereby affecting the Kuroshio intrusion and ITF in the Luzon Strait through the so-called “teapot” effect, resulting in a mutual modulation mechanism between the South China Sea throughflow and the ITF at different time scales. So, will the South China Sea throughflow have adverse effects on the Philippine Sea circulation system and the NEC bifurcation? Next, we will use the simulation results of the LICOM control test and the South China Sea closure test to discuss the possible dynamic feedback of the South China Sea throughflow to the Pacific western boundary current of the Philippine Islands (Wang 2010). The most significant difference between the results of the South China Sea closure test and the LICOM control test lies in the change of the Kuroshio axis, which is the inevitable result of the closure of the Luzon Strait and the disappearance of the Kuroshio set. In addition, a more significant phenomenon in the average circulation field is that the upper meridional flow velocity of the Makassar Strait is also significantly enhanced (Tozuka et al. 2007), which is most likely caused by the disappearance of the northward pressure gradient on the surface of the Makassar Strait after the closure of the Karimata Strait (Qu et al. 2005). The closure test in the South China Sea has no significant effect on the Philippine Sea-west boundary circulation system of the NEC-Kuroshio-Mindanao current in terms of the annual average circulation mode, but the seasonal characteristics have different reflections. Figure 2.35 shows the difference between the two experiments in the climatic monthly average laminar current field from 0 to 300 m in January and July in the east of Mindanao. It can be seen that there is a northward current along the coast in the difference field in January, while there is a southward current along the coast in July. The current rates of these two streams are both on the order of 5 cm/s. From the vertical velocity profile of the Kuroshio section, the difference between the two experiments reaches a depth of 300 m (Fig. 2.36), and the vertical results of the Mindanao Current are similar to this. The results of the LICOM control test minus the South China Sea closure test can be regarded as the “net effect” of the South China Sea throughflow, that is, the effect of the South China Sea throughflow on the Pacific western boundary current system east of the Mindanao is like a “superposition” on the upper stream, the tributary flows north in winter and south in summer. Before the closure of the South China Sea, the volumetric transport of the Kuroshio reached a maximum of 16.2 Sv in February and a minimum of 13.1 Sv in November; the Mindanao Stream reached a maximum of − 20.0 Sv in April (negative values indicate southward transport), a minimum of − 19.0 Sv was reached in September. After the closure of the South China Sea, the seasonal variation of the volume transport of the Kuroshio intensified, decreasing in winter and increasing in summer, reaching a maximum of 18.0 Sv in June and a minimum of 11.0 Sv in November; the seasonal variation of the volume transport of the Mindanao Stream also strengthened, but it increased in winter and decreased in summer, reaching a maximum of − 22.6 Sv in January and a minimum of −

62

2 The Characteristics of Large-Scale Circulation Dynamics …

Fig. 2.35 The difference between the 0–303 m layer circulation in the east of the Philippines and Mindanao in the control test and the South China Sea closure test (Wang 2010)

Fig. 2.36 Seasonal variation of the average meridional velocity in the range of 5 longitudes (123°– 128° E) east of the Philippine coast (Wang 2010) (unit cm/s). A positive value indicates northward current, and a zero line indicates the vertical profile of NEC

2.2 South China Sea Through Flow

63

16.6 Sv in August. After the closure of the South China Sea, the Kuroshio decreased by 2.7 Sv in December, reaching 20% of the total transport in the upper layer of the control experiment in the month; it increased by 2.5 Sv in June, reaching 16% of the total transport in the upper layer of the control experiment in the month. The Mindanao Stream increased by 3.0 Sv in January, reaching 15% of the total transport in the upper layer of the control experiment in the month; it decreased by 2.8 Sv in July, reaching 14% of the total transport in the upper layer of the control experiment in the month. In addition to affecting the upper current field of the Kuroshio and Mindanao Currents, the South China Sea closure test also changed the north–south movement of the NEC bifurcation point. The north–south movement of the NEC bifurcation point after the closure of the South China Sea was more severe than that before the closure of the South China Sea. Before the closure of the South China Sea, the latitude of the NEC bifurcation point reached the northernmost 14.1° N in January and the southernmost 13.1° N in July; after the closure of the South China Sea, the latitude of the NEC bifurcation point reached the northernmost 14.9° N in December, reaching a southernmost 12.6° N in July. After the closure of the South China Sea, the NEC bifurcation point of the relative control experiment moved northward in winter, reaching a maximum value of 0.73° in December; it moved relative southward in summer, reaching a maximum value of 0.53° southward in August. The annual average latitude of the NEC bifurcation point of the control experiment shifted northward with increasing depth. Figure 2.36 shows the seasonal variation of the average meridional velocity from 123° to 128° E east of the Philippine coast. The bifurcation line moves north rapidly below 100 m, both in January and July. As far as the difference before and after the closure of the South China Sea is concerned, it reaches 0.75° in the outermost layer in January, and the difference decreases with the increase of depth, and gradually disappears below about 150 m. The difference in July is relatively small, about 0.5° at the surface, and also decreases with increasing depth, gradually disappearing below about 200 m. Past studies have shown that the NEC bifurcated point moves north in winter and south in summer, accompanied by changes in the distribution of volume and heat-salt transport between the Kuroshio and Mindanao Current. The Kuroshio Current in the east of the Luzon Strait is the smallest in winter and the largest in summer, so the SCSTF is large in winter and small in summer through the β effect. Combined with the above analysis, the seasonal effects of the closure of the Luzon Strait on the western boundary current of the Philippine Sea can be summarized as follows: In winter, a stronger SCSTF leads to a stronger Kuroshio and a southward shift of the NEC bifurcation point. Such a result is not conducive to further strengthening of SCSTF; in summer, a weaker SCSTF leads to a weaker Kuroshio and a northward shift of the NEC bifurcation point. Such a result is not conducive to further weakening of SCSTF. The SCSTF’s reaction to the north–south movement of the NEC bifurcation and the distribution of transport between the Kuroshio and Mindanao Current can be considered a negative feedback (Fig. 2.37). The model study of Metzger and Hurlburt (1996) pointed out that the latitude change of the NEC bifurcation point is very sensitive to the topography. Tozuka

64

2 The Characteristics of Large-Scale Circulation Dynamics …

Fig. 2.37 The Negative Feedback of the South China Sea Throughflow to the Boundary Current on the West of the Philippine Sea (Wang 2010). The dashed arrow indicates the negative feedback effect in winter: the enhancement of SCSTF in winter leads to the southward movement of NEC bifurcation and the enhancement of Kuroshio, which is not conducive to the further enhancement of SCSTF. The situation in summer is the opposite

et al. (2009) believed that this could partly explain the difference in the latitude of the NEC bifurcation points before and after the closure of the South China Sea. However, in the model results, the north–south movement of the NEC bifurcation point before and after the closure of the South China Sea mainly occurred at a depth of less than 200 m. At this depth, the NEC bifurcation point was far from the location where the Luzon Strait was located, that is, the topography could not fully explain this phenomenon. In addition, the north–south movement in the LICOM model test occurred not only in winter but also in summer, which is also different from the model results of Tozuka et al. (2009). The existence of the South China Sea (Sulawesi Sea) and the dynamic negative feedback of the current field through the Luzon Strait (Sulawesi-Mindanao channel) seem to better explain why the variation range of the zero-value line of the zonal integral of wind stress curl is in the range of 11°–20° N, while the seasonal variation range of the latitude of the NEC bifurcation point is relatively small. The negative feedback of the SCSTF to the Philippine Sea-West boundary current also works on an interannual scale. The South China Sea closure test has a more severe meridional displacement than the control test, that is, the negative anomaly (southern year) of the NEC bifurcation point in the control test, and the South China Sea closure test has a larger negative anomaly (more southerly); Positive anomaly years (more northerly) at the NEC bifurcation point in the control experiment, with larger positive anomalies (more northerly) in the South China Sea closure experiment. Therefore, it

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can be considered that the dynamic negative feedback effect of SCSTF on the current field can also partially explain the actual variation range of the latitude of the NEC bifurcation point on the interannual scale, which is smaller than the variation range of the wind stress curl zonal integral zero line. The branch of the South China Sea throughflow that flows into the Luzon Strait and flows out of the Sibutu Strait has an important impact on the western Pacific boundary current system. In terms of climatic averages, this branch of the South China Sea throughflow re-enters the Pacific through the Sulawesi Sea and flows northward along the western boundary of the tropical North Pacific, strengthening the northward Kuroshio, weakening the southward Mindanao Current, and the North Equatorial Current bifurcation point moves south. More importantly, this branch of the South China Sea throughflow also affects the low-frequency variation of the western North Pacific boundary current system. Along with the change of the atmospheric Walker circulation trend, before the 1990s, the orth equatorial current bifurcation point showed a trend of moving northward, and the Kuroshio showed a linear weakening trend; since the early 1990s, the bifurcation point of the North Equatorial Current has tended to move southward, causing the Kuroshio to show a linear intensification. With the opening of the South China Sea throughflow channel, the changes in the North Equatorial Current bifurcation point and the Kuroshio Current are both weakened by about 20%. In particular, the trend mutation characteristics before and after the 1990s were significantly weakened by the modulation of the South China Sea throughflow branch (Zhuang et al. 2013). In view of the above-mentioned negative feedback characteristics of the South China Sea throughflow branch to the Pacific western boundary current, we used the same sea-land boundary as the reduced gravity model and calculated the variation of the western boundary current along the eastern coast of the Philippine Islands with the presence of circum-island oceanic channel through an analytical model of timevarying around-island circulation. At the same time, the linear baroclinic Rossby wave theory was used to calculate the variation of the western boundary current in the tropical Pacific when the oceanic channel around the island was closed (Zhuang et al. 2013). The results show that the north equatorial current bifurcation point and Kuroshio changes calculated by the time-varying analytical model of circulation around the island and the linear baroclinic Rossby wave theory are similar to those of the reduced gravity model, but the low frequency variation amplitudes of the Kuroshio and Mindanao currents obtained from the time-varying analytical model of the circulation around the island are significantly weaker than those obtained by the linear baroclinic Rossby wave theory. The difference between the two is similar to the difference between the results of the reduced gravity model on/off the oceanic channel around the island, which better reveals the negative feedback mechanism of the South China Sea throughflow branch around the island to the western boundary current of the tropical Pacific. In addition, the Mindoro Strait plays a very important role in the process of communication between the Pacific Ocean and the South China Sea. The nearequatorial rising Rossby wave excited by the anomalous equatorial easterlies in the Pacific Ocean reaches the western border, namely the east coast of the Philippines,

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and will stimulate the coastal Kelvin wave. The east coast of the Philippines enters the South China Sea through the Mindoro Strait, thereby affecting the internal dynamic adjustment of the South China Sea and the water exchange in the Luzon Strait (Liu et al. 2011). The volume transport of the Luzon Strait and the Mindoro Strait have quite consistent interannual variability, and the consistency is not caused by the wind field, but is closely related to the Kelvin fluctuations of the shore boundary. To this end, we carried out a series of numerical experiments using the reduced gravity model to further elucidate the couple circulation dynamics around the Philippine Islands. The results show that the sea level change signal in the western Pacific is mainly driven by the wind field in the tropical circulation area south of 13° N in the North Pacific, and the local wind field in the marginal sea area and the low-frequency change signal in the subtropical sea area are less affected. The low-frequency signal of the tropical Pacific wind field leads to the low-frequency oscillations of the clam in the western Pacific basin, and this low-frequency variation signal propagates westward through the baroclinic Rossby wave, thus affecting the western Pacific sea area east of the Philippine Islands (Zhuang et al. 2013). At the same time, if the Sibutu Strait is closed, the sea level changes in the Sulu Sea and the eastern part of the South China Sea will be significantly weakened, and will no longer show the same change characteristics as the western Pacific. In the case of closing other channels such as the Luzon Strait and the Karimata Strait, the sea level low-frequency signals in the western Pacific and marginal seas did not change significantly (Zhuang et al. 2013). The coastal Kelvin wave propagation path around the Philippine Islands is selected, and the lead-lag correlation analysis of the sea level change signal on this path further confirms the existence of the low-frequency coastal Kelvin waves, and the phase velocity of its propagation is about 2.3 m/s (Fig. 2.38). The presence or absence of the Indonesia throughflow has no obvious effect on the propagation process of the fluctuation signal. The study of Zhuang et al. (2013) further verified the conclusion of Liu et al. (2011), confirming that the SCSTF plays an important role in communicating the circulation process of the Philippine islands. The dynamic process of the Pacific signal affecting the South China Sea and the western boundary current of the Pacific Ocean through the Mindoro Strait can be summarized as follows: The variation of wind stress curl in the tropical Pacific drives the sinking (rising) movement of the thermocline, and the signal of the thermocline change traveled westward in the form of baroclinic Rossby waves to the east coast of the Philippine Islands, causing the sea level to rise (lower) here, and stimulate the coastal Kelvin wave, which traveled clockwise along the Philippine coast to the eastern South China Sea (Liu et al. 2011; Zhuang et al. 2013). Rising (lowering) sea level in the western Pacific moves the North Equatorial Current bifurcation point southward (northern), while increasing (decreasing) the flow of the Kuroshio. At the same time, affected by the coastal Kelvin wave signal, the sea level in the northeastern part of the South China Sea increased (decreased), resulting in a decrease (increase) of the volume transport of the Luzon Strait. Changes in the volumetric transport of the Sibutu Strait are further fed back to the western boundary of the North Pacific (Zhuang et al. 2013), forming in abnormal southward (northward) currents east of

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Fig. 2.38 a The sea level change signal simulated by the reduced gravity model is distributed along the lagging correlation around the Philippine Islands; where SP, MS and LS represent the Sibutu Strait, Mindoro Strait and Luzon Strait, respectively. b Simulated mean sea level distribution (contour) and the variance of its low frequency variation (filled), where the purple line represents the wave propagation path around the Philippine Islands (Zhuang et al. 2013)

the Philippine Islands, thus making the North Equatorial Current bifurcation point move northward (southward), and the flow of Kuroshio decreases (increases).

2.2.3.4

Regional Climate Effects of the South China Sea Throughflow

As an important part of the Northwest Pacific-Indonesia Circulation System, the role of the South China Sea throughflow in this circulation system is likely to be multifaceted. The South China Sea throughflow flows out through the Karimata Strait, forming a northward pressure gradient on the surface of the Makassar Strait, which affects the ITF and plays a non-negligible role in regulating the SST in the Indonesian waters and the adjacent Indo-Taiwan ocean (Qu et al. 2006). As mentioned above, the South China Sea throughflow plays a very important role in the change of the heat content in the upper layer of the South China Sea and the heat transport in the channel of the Makassar Strait. The closing and opening of the SCSTF will lead to the southward heat transport of the Makassar Strait producing 0.18 PW (Tozuka et al. 2009), so the South China Sea throughflow has important potential significance in the climate change system. Tozuka et al. (2009) presented the characteristics of the difference in sea surface temperature before and after the SCSTF closure (after closure minus before closure). After the closure of the SCSTF, the SST of the South China Sea increased significantly, which is related to the cold advection effect of the SCSTF mentioned above. The water body entering the South China Sea through the Luzon Strait is relatively cold, while the water body exiting from the Karimata Strait and the Mindoro Strait

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is relatively warm, and the SCSTF is a cold advection effect for the South China Sea. The South China Sea obtains 0.12 PW of heat from the surface and transports it out through the SCSTF (Qu et al. 2006). The Luzon Strait volume-weighted temperature is 19.0 °C, while the Karimata Strait is 27.5 °C. Another notable change is that the water bodies of the Pacific and Indian Oceans became cool after the SCSTF shut down. The cooling of the waters in the Pacific Ocean, especially in the western Pacific Ocean, can be explained by the fact that the southward water body heat transport of the Makassar Strait is 0.19 PW more without SCSTF (0.69 PW) than with SCSTF (0.50 PW). In addition, the Kuroshio region should be cooled by 0.2 °C without SCSTF, which may be related to the reduction of heat transport in the western boundary current of the Pacific Ocean, and the heat transport of the western boundary current is related to the northward shift of the NEC bifurcation point. On average, in the absence of SCSTF, the NEC bifurcation point moves northward from 13.0° N to 13.8° N. In summary, the South China Sea plays an important role in adjusting the SST in the Indo-Pacific region, so SCSTF has important potential implications for climate change. As stated by Tozuka et al. (2009), the SCSTF will further weaken the ITF during El Niño, so it may lead to longer El Niño period, adjusting the frequency of ENSO occurrence. When the SCSTF is closed, the southward heat transfer of the Makassar Strait will increase during El Niño, which will cause a 1.5 °C cooling in the Western Pacific, and this change will have important impacts on the coupled Indo-Pacific warm pool air-sea system. In addition, the weak warm SST anomaly in the Java Sea may also have a certain influence on the appearance of the Indian Ocean dipole mode. Using the air–sea coupling model, Tozuka et al. (2015) explored the effect of SCSTF closure on the occurrence cycle of ENSO, indicating that the existence of SCSTF can shorten the occurrence cycle of ENSO from 5 to 4 years. The reason may be that when SCSTF is lacking, the north–south expansion of the zonal wind stress anomaly is wider, and the Walker circulation in the Indian Ocean is stronger. In addition, when the eastern Pacific type and the central Pacific type El Niño occurred in the Pacific, the circulation pattern of western Pacific and the South China Sea, which prevailed from December to February (winter), also changed significantly (Liu et al. 2014). There is also a clear different in the circulation response under these two forms of El Niño (Fig. 2.39). Compared with the central Pacific El Niño, during the eastern Pacific El Niño, the South China Sea throughflow became the main part of the western boundary current, and the surface circulation weakened to a greater extent in winter. In the southern part of the South China Sea, the surface circulation in winter shows an abnormal anticyclonic circulation. At the same time, the abnormal cyclone circulation patterns on the west side of the Luzon Strait also have obvious differences. In terms of climate, the South China Sea gets heat from the atmosphere, and the relatively cold water entering from the Pacific Ocean flows out from the southern straits of the South China Sea after being heated, so the South China Sea throughflow has a cold advection effect (Qu et al. 2006; Liu et al. 2012b). During the autumn and winter seasons of the central Pacific-type El Niño, the Pacific water body entering

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Fig. 2.39 The composite map of the winter 0–46.6 m depth average surface current field obtained from SODA products (a) and the composite map of winter geostrophic current obtained from the satellite altimeter (b) (Liu et al. 2014). a1 and b1 are east Pacific type; a2 and b2 are mid-Pacific type

the South China Sea through the Luzon Strait increases, while continuously gaining heat from the atmosphere (the net heat flux anomaly is positive), but the occurrence of surface circulation anomalies in the western boundary current of the South China Sea (Liu et al. al. 2014) makes the heat obtained by the ocean surface from the atmosphere unable to be transported through the southern strait in the form of cold advection through the South China Sea. This may be one of the important factors leading to the occurrence of the South China Sea warm event during El Niño (Wang and Wu 1997). This conclusion does not contradict the previous research results (Liu et al. 2011), which refers to the possible effect of SCSTF on the upper SST. The change of heat content above 400 m in the upper layer is not synchronized with the change of sea surface temperature (Fig. 2.40), and the change of heat content is more due to the influence of the subsurface layer below the thermocline (Liu et al. 2012b), which further explains the cold advection effect of the South China Sea throughflow on the upper heat content of the South China Sea during El Niño. The cold advection of the SCSTF affects more the subsurface thermal characteristics, thus explaining

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Fig. 2.40 Niño3.4 index, the standardized time series of the average SODA sea surface temperature of the South China Sea and the average heat content of the South China Sea, and the vertical distribution of the average temperature of the South China Sea (Liu et al. 2012b)

the possible mechanism of the obvious warming trend of sea surface temperature but not the subsurface (Liu et al. 2012a). So far, although there has been a lot of knowledge about SCSTF, many issues are still not fully understood. For example, what is the specific path of SCSTF in the South China Sea, what is the effect of SCSTF on the monsoon system, etc. This kind of work still needs to be further studied and discussed through a large amount of observational data and the development of high-resolution air-sea coupled models.

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2.3 South China Sea Western Boundary Current 2.3.1 Interannual Variation of the Western Boundary Current of the South China Sea Using the observation data of the Xisha Deep Sea Marine Environment Observation and Research Station (hereinafter referred to as “Xisha Station”) for 7 years (2007– 2013), combined with shipborne ADCP and satellite observation data, the vertical structure of the western boundary current of the South China Sea in the waters of the Xisha islands was revealed characteristics and their interannual variation. In general, the west boundary current of the South China Sea in the waters of the Paracel Islands is southwest from November to April of the following year, and the maximum flow rate occurs in winter, exceeding 60 cm/s; It is northeast from July to September, and the flow rate is lower than that in winter; the speed direction from May to June and October showed a changeable frature, which belonged to the adjustment period (Figs. 2.41 and 2.42). The 7-year average current shows that the current direction of Xisha Station is southwestward in the climatic state, and the average velocity decreases from 12 cm/s at 50 m to 1.5 cm/s at 450 m (Fig. 2.43a). From the perspective of the monthly average velocity of the climate, the average from July to September is the northeast flow, and the average velocity is the largest in August, about 15 cm/s at a depth of 50 m, and about 8 cm/s at a depth of 450 m. The rest of the months are all southwestward currents, with the maximum occurring in the upper layer from November to December, about 32 cm/s; while the maximum southwestward current at a depth of 450 m occurs in February to March, about 7 cm/s (Fig. 2.43). In addition to strong seasonal variation, the observed western boundary current also exhibits strong interannual variability. In particular, the northeast-trending current in summer completely disappeared in 2011, showing a southwest-trending current with an average southwesterly current of 50–450 m reaching a maximum of 20 cm/s (Fig. 2.44). Comparing the 7-year average observations, Fig. 2.45 reveals the variation of the monthly average velocity anomalies with depth in 2010 and 2011. In 2010, the velocity anomalies mainly occurred in the shallow depth of 120 m. The maximum monthly average velocity anomalies in the latitudinal direction were 28 and 23 cm/s in the meridian direction, they occurred in August and July respectively, but at the depth of 120 m, the current anomalies were small and did not exceed 5 cm/s (Fig. 2.45). In 2011, however, the current anomaly appeared at the entire observation depth (50–450 m). Even at a depth of 450 m, the monthly mean zonal velocity negative anomaly reached 14 cm/s, and the radial reached 12 cm/s.

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Fig. 2.41 The zonal velocity profile observed by ADCP from 2007 to 2013 (Shu et al. 2016)

2.3.2 The Formation Mechanism of the West Boundary Current of the South China Sea On the basis of observations, Chen and Xue (2014) used an ideal numerical model to study the basic fact why a strong western boundary current can be observed in the

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Fig. 2.42 The meridional velocity profile of submersible mark ADCP observations at Xisha Station from 2007 to 2013 (Shu et al. 2016)

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Fig. 2.43 The 7-year average current vector a of the climatological state at Xisha Station, and the zonal (b) and meridional (c) velocity of the monthly average climatic state (Shu et al. 2016)

Fig. 2.44 The 50–450 m vertical average velocity time series observed by ADCP at Xisha Station from 2007 to 2013 (Shu et al. 2016)

South China Sea, but not in the Sea of Japan and the Gulf of Mexico. The results show that the strong western boundary current in the South China Sea is mainly attributed to the combined action of the strong monsoon and the throughflow. Although the Gulf Stream transports large volumes of water into the Gulf of Mexico, the existence of the Florida Strait prevents the inflow from strengthening the western boundary current, and the Gulf of Mexico wind stress is the smallest among the three marginal seas. The meridional ridge in the Sea of Japan prevents the entire basin from participating in the westward strengthening process, and the inflow adversely affects the formation

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Fig. 2.45 Anomalies of monthly average speed observed by ADCP at Xisha Station from 2010 to 2011 relative to the 7-year average (Shu et al. 2016)

of its western boundary. The β effect leads to westward strengthening of marginal sea. However, a strong western boundary current requires a reasonable configuration of wind, current and topography to generate. The western boundary current of the strong South China Sea can reach nearly 20 Sv.

2.3.3 Vietnam Offshore Current Due to the steep terrain along the coast of Vietnam, there has always been a significant western boundary current, and due to factors such as terrain changes and the configuration of wind field, there are obvious separation currents in this area. Qu et al. (2007) found that the Vietnam offshore current has an important influence on the thermal structure of the western South China Sea (Fig. 2.46). Xiao (2006) used the assimilation results to analyze the characteristics of offshore currents in Vietnam. The position and intensity of the anticyclonic eddy D off the coast of Vietnam sea are very close to the observations (Fig. 2.47). In early July, the circulation in the southern and central parts of the South China Sea are bounded by 12° N. The southern part consists of three eddies, two cyclonic eddies are centered at (9° N, 114° E), (7° N, 109° E), and an anticyclonic eddy is centered at (7° N, 113° E). We call them eddies A, B and C respectively. In mid-July, the positions of the three eddies remained unchanged, but the northward tributaries of the eddy began to intensify, and the northward tributaries of eddy C further extended northward to around 12° N in late July. As a result, the northward current in summer is formed. In the first ten days of August, the northern section of this northward current began to bend, and eddy B was nearly dead, and an anticyclonic eddy appeared near it (12° N, 113° E). This is the anticyclonic eddy off the coast of Vietnam. From mid to late August,

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Fig. 2.46 Annual average stratosphere, barrier layer and mixed layer (from Qu et al. 2007)

the anticyclonic gradually intensified eddy off the coast of Vietnam, and the northward currents developed near the coast. By the end of August, a northward current was clearly visible along the southeastern coast of Vietnam, heading northeastward, turning northeastward at around 12° N, forming the so-called Vietnam Offshore Jet (Fig. 2.47). Gan and Qu (2008) pointed out that from late spring to early autumn (P1), the separation flow region has negative wind stress in the x direction, and is balanced by nonlinear terms and non-geostrophic terms; from early autumn to late spring (P2), the non-geostrophic term becomes negative and strengthens all the time, which is balanced with the wind stress term and the nonlinear term. The y-direction is similar to the x-direction, but with a smaller amplitude. These results indicate that the northeasterly at nearshore points and the easterly at far shore points play a major role in the P1 phase. In the P1 stage, the pressure gradient force in both directions near the shore point is negative, so the negative non-geostrophic term represents the net southwest pressure gradient force. This negative pressure gradient force is balanced by the northeasterly stress and opposites the northeasterly current, thus becoming the inverse pressure of the separation current. It is similar in the P2 phase, except that the non-geostrophic term is balanced by the wind stress term and the nonlinear term. The reverse pressure becomes the driving force for the separation current on the narrow shelf. The non-geostrophic term at the far shore is very small and the reverse pressure is not significant. Therefore, the formation of reverse pressure is very sensitive to topography, and the separation current is closely related to reverse pressure (Fig. 2.48).

2.3.4 Response of Summer Cold Eddy to Monsoon on the Western Boundary of South China Sea There is an obvious land headland terrain in eastern Vietnam near 11° 30′ N. To the north of the headland, the eastern coast of Vietnam runs north–south, while to

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Fig. 2.48 3-year average vertical integral pressure gradient force, Coriolis force, non-geostrophic term, nonlinear term, acceleration term, wind stress term and bottom friction term (Gan and Qu 2008). prex and prey represent the pressure gradient force in the x and y directions respectively; corx and cory represent the Coriolis force in the x and y directions respectively; agex and agey represent the non-geostrophic terms in the x and y directions respectively; nlx and nly represent the non-geostrophic forces in the x and y directions respectively linear terms; acex and acey represent acceleration terms in the x and y directions respectively; tsx and tsy represent wind stress terms in the x and y directions respectively; thx and thy represent the bottom friction terms in the x and y directions respectively. The pressure gradient force and Coriolis force are both multiplied by 10–5 , and the others are multiplied by 10–6

the south of the headland, the shore boundary turns southwest, with a northeastsouthwest trend. According to the satellite (AVHRR) remote sensing sea surface temperature (SST) observation, the average climatic state from June to September shows that the low temperature center of the sea surface is always located along the southeastern coast of the headland. Among them, the cold center temperature in August is the lowest, and the extension to the east is the largest, which means that the cold eddy is the strongest at this time. The low temperature center of the surface layer is located in the coastal waters southeast of the coastal headland (south of 12° N), and the center temperature is lower than 28 °C. Its location is basically the same as that of the low temperature center in satellite remote sensing, and the cold tongue tends to expand eastward. However, due to the low spatial resolution of WOA2001 data and the smoothing of

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interpolation, the spatial structure of its SST is not as detailed as that of satellite remote sensing SST. From the depth of 50 m, the isobaths in eastern and southern Vietnam are roughly north–south direction, and there is no headland terrain similar to the shore boundary. Different from the surface layer, the low temperature zone at the 50 m layer is located north of the shoreline headland, with a central position of 12°–14° N and a central temperature lower than 22.5 °C (Fig. 2.49b). At a depth of 100 m, the location of the low temperature center is roughly the same as the 50 m layer, and the center temperature is lower than 18 °C (Fig. 2.49c). In addition, at a depth of 100 m, there is a significant warm eddy south of Vietnam with a central temperature higher than 22.5 °C. Previous field observations have shown that there is a strong anticyclonic eddy here. From this, it can be inferred that the convergence and sinking phenomenon caused by the anticyclonic eddy is the main reason for the formation of the warm eddy here. At a depth of 200 m, the influence of the Vietnam cold eddy is already very weak. The temperature of the warm eddy southeast of Vietnam is slightly higher than that of the surrounding open water mass, but it is significantly smaller. A control experiment (Epx0) and a sensitivity experiment (Exp1) were used to study the influence of the South China Sea summer monsoon on the upper ocean thermal structure, especially the intensify and spatial structure of the Vietnam cold eddy. In Exp1, the local wind stress is irrotational to the east of Vietnam in summer. According to the distribution map of the average upper water temperature in Exp0 (Fig. 2.50), from June to August, the water temperature in the east of Vietnam gradually decreased, and the low temperature area gradually expanded to the east; By September, the temperature in the low temperature center gradually increased again. In order to more comprehensively understand the influence of various dynamic and thermodynamic factors on the growth and decline of the cold eddy in Vietnam, this study selected a 3° × 3°square area A (11°–14° N, 109.5°–112.5° E) along the coast of Vietnam, which roughly included the area where the Vietnam cold eddy is located. − → The regional average horizontal advection term (− V · ∇T ), vertical entrainment term [−we (T − Tb )/ h] and sea surface thermal forcing term (Q/h) were calculated respectively, revealing the contribution of several different effects to temperature variation in this region. Figure 2.51a, b show the variation curves of the advective transport effect, the vertical entrainment effect, and the sea surface heating effect with time every 15 days relative to the previous time in the average temperature in area A moment under the conditions of Exp0 and Exp1, respectively. It can be clearly seen that from March to June, under the action of heat input from the sea surface, the average temperature in the area A continues to increase (dT > 0), and the contributions of the advective transport term and the vertical entrainment term are almost equal to zero. From the end of June to the end of August, the average temperature continues to decrease (dT < 0). During this period, the thermal forcing of the sea surface played a heating and warming effect. The reason for the decrease in water temperature was the vertical entrainment effect and advective transport effect. Among them, the vertical entrainment makes the cold water in the lower layer rise to the upper

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Fig. 2.49 Temperature distribution at depths of 0, 50, 100 and 200 m in August (Zhuang 2004). The isoline interval is 0.5 °C; the data comes from WOA2001 climate monthly average data

layer, which is the main reason for the local water temperature drop. The effect of advection transport can be divided into two parts: meridional advection (−v ∂∂Ty ) and zonal advection (−u ∂∂Tx ). It can be seen from Fig. 2.51b that the total contribution of the advection term is cooling, but its magnitude is significantly smaller than that of the vertical entrainment item. In July and August, its magnitude is only about 1/3 of the vertical entrainment item. By calculating the changes in flow over time at the four boundaries of the east, west, south, and north of A Redion (Fig. 2.52), the reasons for the changes in the advection effect can be revealed to a certain extent. From May to August, the eastward flow on the eastern border and the northward flow on the southern border continued to increase, and reached the maximum (both

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Fig. 2.50 Temperature field of upper layer from June to September under Exp0 condition (°C) (Zhuang 2004)

> 20 Sv) in August, then decreased rapidly, and began to turn in October. During this period, the eastward current at the western boundary and the northward current at the northern boundary were small (< 5 Sv) and did not change much, indicating that the anticyclonic circulation in the southern part of the South China Sea r formed a strong northward warm advection at the western boundary in summer, which transported the warm water in the south to the north. However, instead of continuing northward to 14° N, this northerly current turned off the coast of Vietnam, forming an eastward offshore current. This eastward current expands the local cold water produced by the vertical entrainment effect to the east, further increasing the influence of the cold vortex. By September, the vertical entrainment effect was significantly weakened. At the same time, due to the weakening of the anticyclonic circulation, both the cold and warm advection decreased rapidly and the eastward cold advection weakened faster than the northward warm advection, so the total advection term gradually increased and became positive. Under the combined effect of advection transport effect and sea surface heat input, the Vietnam cold eddy began to warm.

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Fig. 2.51 Control test Exp0 condition (a) and sensitivity test Exp1 condition (b) the average temperature change in area A every 15 days, as well as meridional advection, zonal advection, total horizontal advection effect, vertical entrainment effect and sea surface heating effect vary with time (Zhuang 2004)

Fig. 2.52 The annual transport cycle of the cross-section of the east, west, south, and north boundaries of area A under the control experiment Exp0 condition (Zhuang 2004)

2.3.5 The Relationship Between the Intraseasonal Variation of SST and the Intraseasonal Variation of Wind Stress in Vietnam Nearshore in Summer The development of wind jets and cold tongues in eastern Vietnam is not a smooth seasonal process, but consists of several intraseasonal events each year, spaced around

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45 days apart (Xie et al. 2007). In a typical intraseasonal event, a cold tongue develops in the ocean after a week or so, driven by intensification of the wind field jet and subsequent advection by the Vietnam offshore current. Through the Rossby wave adjustment, Vietnam offshore current itself also intensified under the influence of the events in the season, with the strongest increase in 2–3 weeks.

2.4 Southern South China Sea Circulation 2.4.1 Seasonal Succession of Circulation in the Southern South China Sea 2.4.1.1

Seasonal Succession of Temperature and Salinity

It can be seen from the temperature and salinity plots of the voyages in the spring (summer) of 1999 that in the spring (summer) of 1999, the properties of the middle water and deep water mass in the southern South China Sea were very stable and single, and there was no obvious differentiation. There is a big difference from the situation in 1998. It should be noted that the distribution of the surface water in the South China Sea during the spring voyage in 1999 was relatively scattered, indicating that the variation in surface water properties was relatively large; but during the summer voyage, the temperature and salinity points of the surface water were relatively concentrated, indicating that during the spring voyage in 1999, the mixed layer of the ocean surface in the southern South China Sea is relatively shallow, and the vertical gradients of temperature and salinity are not obvious. During the summer voyage, the South China Sea has a deep upper mixed layer, and the surface water properties of the South China Sea dominated by water bodies in the mixed layer are relatively simple. Below the mixed layer, there are strong thermoclines and haloclines.

2.4.1.2

Differences in Temperature and Salinity Level Distribution Fields in Spring and Summer

Compared with April 1999, the ocean surface and subsurface water temperature increased significantly, and the temperature increase decreased with the increase in depth (Fig. 2.53); the temperature of the mid-level water dropped slightly after the onset of the summer monsoon. In summer, the range of warm water in the northwest of the Nansha Islands expanded significantly, and the temperature difference with adjacent waters also increased significantly (Fig. 2.53). The results of the salinity distribution during the spring voyage in 1999 (Fig. 2.54) show that the spatial distribution pattern of salinity and temperature are roughly opposite at depths of 50 and 100 m. That is to say, the salinity in the warm water

Fig. 2.53 Temperature distribution of voyages in spring (April) and summer (July) in the southern South China Sea in 1999 (Chen 2005). The contour interval is 0.5, 0.25 and 0.05 °C respectively

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activity area is low at each depth, and the salinity in the cold water activity area is high. This indicates that the salinity changes at depths of 50 and 100 m have a relatively good inverse correlation with temperature changes. The salinity of the upper seawater decreases in summer, and the change amplitude decreases rapidly with depth. From the distribution results of temperature and salinity along the across-section, after the onset of the summer monsoon, the depth of the thermocline and the halocline deepened, and the thickness of the cline became thinner. Compared with spring, the range of low salt water bodies in southeastern Vietnam increases significantly in summer, controlling a large area in southeastern Vietnam, and its center is slightly shifted eastward than before the onset of the monsoon.

2.4.1.3

Seasonal Succession of Circulation

The geostrophic calculation results (Fig. 2.55) show that at a depth of 50 m in spring, the survey area is mainly controlled by cyclonic circulation, and there are three relatively obvious mesoscale eddies distributed in its interior: the Wanan cyclone, Vietnam anticyclone (10° N, 111° E) and the elliptical cyclone eddy on its east side; at a depth of 100 m, this circulation pattern is still maintained, and at the same time, a weak anticyclone eddy is formed north of the Beikang shoal; the circulation at a depth of 500 m is relatively simple, there is no very significant eddy activity. The west of the surveyed sea area is mainly southeast-trending current, and the east and south are northeast-trending current. The survey area is roughly a cyclonic circulation pattern. From April to July 1999, the monthly average geostrophic distribution results synthesized by TP&ERS MSLA and the multi-year average sea surface dynamic height (Fig. 2.56) show that in April, the South China Sea basin was still mainly characterized by cyclonic circulation, and the Xisha Islands in the central South China Sea and its adjacent waters and the waters of Southeastern Vietnam are mainly controlled by several cyclonic eddies of relatively low intensity. In May, the cyclonic circulation in the northern part of the South China Sea was still obvious, and there was obvious cyclonic bending near 12° N in the coastal waters of central Vietnam. The strength of the structure was further strengthened in June, and the range expanded eastward. In addition, there is no obvious anticyclone eddy in the southeastern waters of Vietnam; the west side of the southern basin of the South China Sea has a cyclonic circulation pattern, and the east side shows a weak anticyclonic trend. In June, an incomplete anticyclonic circulation structure appeared in the seas of southeastern Vietnam. The center of the structure moved northeastward to the waters near (11° N, 112° E) by July, and its intensity increased and its range expanded. The structure is fully developed, and the entire southern South China Sea is controlled by a large anticyclonic circulation. To sum up, from April to July, the circulation pattern in the southern South China Sea gradually changed from a cyclonic to an anticyclonic. The more obvious feature is that the Vietnamese anticyclonic gradually strengthened and expanded during the northward movement; the intensity of the cyclonic circulation in the northern waters of the South China Sea weakened and the scope was reduced, and the center moved away from the northwestern corner of the Philippines to the

Fig. 2.54 Distribution of salinity levels in the spring (April) voyages and summer (July) voyages in the southern South China Sea in 1999 (Chen 2005). The isolines are 0.05, 0.025 and 0.0005 psu respectively

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Fig. 2.55 Geostrophic current vector calculated by P-vector method (Chen 2005)

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Fig. 2.56 From April to July 1999, TP&ERS MSLA and multi-year average sea surface dynamic height combined sea surface topography and corresponding geostrophic current field and vertical orbital geostrophic current calculated from T/P 038 orbital data (blue) (Chen 2005)

northern continental slope of the South China Sea. These characteristics are relatively consistent with the climatic characteristics of the ocean circulation in the South China Sea, but there are significant differences from 1998.

2.4.2 Interannual Differences in Spring Hydrological Elements in the Southern South China Sea 2.4.2.1

Difference in Temperature Level Distribution

From the temperature distribution diagrams at a depth of 50 m for the three spring voyages in May 1985, April 1986, and May 1987 (Fig. 2.57a–c), it can be seen that the temperature change trend in 1987 was relatively close to that in 1986. The west side of the sea was occupied by high temperature water; the Nansha Trough area is a cold water area, and there is a relatively obvious sign of small-scale warm water activity in the southwest of Palawan Island. The temperature distribution pattern in 1985 was

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significantly different from that in 1986 and 1987. In general, the temperature in this sea area was the highest in 1985, followed by 1987, and the lowest in 1986. This may be related to the fact that observations only started in late spring 1985. At a depth of 100 m, the temperature in 1985 was high in the west and low in the east, which was close to the general distribution in 1986 and 1987. In the past three years, the Nansha Trough was occupied by low-temperature water; there were signs of warm water activity on the western side of the Balabac Strait for three years. The difference is that in 1987, the temperature of the Nansha Trough and its western sea area was obviously 0.5–1.0 °C lower than that of the previous two years, and its central temperature was lower than 19 °C, mainly distributed at (6° N, 113.5° E), which is westward than its position in 1985 and northerly than its position in 1986. Among the three years, the temperature in 1987 was the lowest, and the difference in temperature between 1985 and 1986 was very small. At a depth of 500 m, the temperature in 1985 showed a distribution pattern of high in the south and low in the north. The highest temperature was 8.8 °C, which was mainly distributed at the edge of the deep-water area south of Wanan Shoal, and the lowest temperature appeared in the southeastern waters of Vietnam. In 1986, the deep-water basin area between Beikang Shoal and Wanan Shoal was mainly occupied by low-temperature water; warm water was in the west of Palawan Islands, and at the same time at (9.5° N, 111.5° E) there may be a warm central structure. The temperature distribution pattern in 1987 was similar to that in 1986, only the temperature was slightly lower. In short, the temperature distribution patterns in 1986 and 1987 were relatively similar; in the three years, the low-temperature water in the Nansha Trough was more obvious at a depth of 100 m. But at a depth of 50 m, only the low temperature characteristics in 1986 and 1987 were more obvious; at a depth of 500 m, the temperature distribution trends in 1985 and the other two years were also different.

2.4.2.2

Differences in Salinity Level Distribution

At a depth of 50 m, the salinity of the observed sea area in 1987 was the highest, generally higher than 34 psu. The maximum salinity center was located in the waters west of the Balabac Strait (> 34.15 psu), and the lowest salinity was distributed in the waters near the Zengmu Shoal (Fig. 2.58). The salinity in 1985 was the lowest. Except for the relatively high salinity in the western Balabac Strait, the salinity in the rest of the seas was lower than 33.8 psu. The lowest salinity occurred in the waters near the Zengmu Shoal, which was about 33.35 psu. In 1986, the salinity was in the middle. There were large-scale high-salt water bodies in the northwestern waters of Kalimantan island, with a central salinity exceeding 33.95 psu, and the northern end all the way to the southern part of Palawan Island, and in the southeastern waters of Vietnam the salinity exceeded 34.1 psu. This may be related to the entry of high-salt water from the northern part of the South China Sea into the southern part of the South China Sea, and the west side of Palawan Island mainly distributes low-salt water with a salinity lower than 33.8 psu.

Fig. 2.57 Temperature distribution during the spring survey in 1985, 1986 and 1987 (Chen 2005). The contour interval is 0.25, 0.25 and 0.05 °C respectively

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Fig. 2.58 Salinity distribution during the spring survey in 1985, 1986, and 1987 (Chen 2005). The contour interval is 0.05, 0.025 and 0.005 psu respectively

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At a depth of 100 m, the salinity in 1986 was significantly lower than that in the other two years, and the distribution pattern was also different. Specifically, in 1985, the salinity was low in the west and high in the east, with a difference of 0.1 psu between the east and the west. In 1986, there was a low-salinity tongue in the Wanan Shoal that entered the observation core area eastward from the coastal waters of Vietnam, and its minimum salinity was only 34.25 psu. The high salt water of more than 34.5 psu appeared in the waters of southeastern Vietnam. The source is the same as the depth of 50 m. It may come from the northern part of the South China Sea. The salinity of the waters west of Kalimantan island is 0.1 psu lower than the other two years. At the same time, a small range of low-salt water body appeared in the west of the Balabac Strait; the salinity in 1987 was generally higher than 34.4 psu, and the lowest salinity appeared in the waters north of the Wanan Shoal, while relatively low-salt water bodies appeared in the west of the Balabac Strait. It can be seen that the salinity distribution of the 100 m layer in 1985 is roughly opposite to that of the 50 m layer, while the salinity distribution of the 100 m layer in 1986 and 1987 is consistent with that of the 50 m layer. At a depth of 500 m, the salinity was generally 34.415–34.425 psu in 1985, slightly higher in the continental slope area in the southwest of the basin, and slightly lower in the sea off the southeastern part of Vietnam. The salinity in 1986 was 34.4–34.44 psu, the maximum salinity and minimum salinity were located near the southwestern continental slope of the sea basin and the sea off southeastern part of Vietnam; the salinity in 1987 was 34.44–34.45 psu, and its salinity increased from the southwest of the basin to the waters west of Palawan Island, but the salinity of the sea off southeastern part of Vietnam was still relatively low. It can be seen that the distribution of salinity at different layers also has obvious differences in. The salinity distribution trends of the 50 and 100 m in 1986 and 1987 were very consistent. However, in 1985, the salinity distribution trends of the 50 m layer and the 100 m layer were roughly opposite. In 3 years, the 50 m layer was high salt water on the west side of Balabac Strait, and the 100 m layer is low salt water on the west side of Balabac Strait, suggesting some signs of exchange of Sulu sea water and South Sea water. In the middle layer, 1987 was obviously different from the previous two years in terms of the spatial trend of salinity. It is also worth noting that the salinity below the 100 m layer in 1986 was the lowest in three years, while it was the highest in 1987, indicating that there may be significant interannual variation in the salinity of the subsurface water in this area.

2.4.2.3

Distribution Differences of Geostrophic Current

The results of the geostrophic vector distribution at the 50 m layer (Fig. 2.59a–c) show that the surveyed sea area has an obvious multi-vortex structure in the past three years. Cyclone eddies and anticyclonic eddies coexist, and their center positions have also change. But the general trend is that in 1985 and 1986, cyclonic circulation pattern was mainly manifested in the observed sea area, and in 1987, it was an anticyclonic circulation pattern. During the three years, the southern part of the Nansha Trough

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was dominated by a cyclone eddy. The center of the eddy in 1985 was relatively northerly at 6.5° N, and both in 1986 and 1987 at 6° N. The strength of the eddy was the strongest in 1986, the weakest in 1987, and the range was the smallest, and the structure has begun to disintegrate on the 100 m layer. In the sea area between Wanan Shoal and Beikang Shoal, in addition to the anticyclone eddy centered on Wanan Shoal at a depth of 100 m in 1985, there was also a small cyclone eddy on the west side of the sea south of Wanan Shoal. There was an anticyclone eddy with a slightly larger range on the east side, but at a depth of 50 m, the Wanan anticyclonic eddy was not obvious; in 1986 it was basically controlled by an anticyclonic trend; in 1987, it also showed a weak anticyclonic circulation patterns of trends. Although their morphology has changed in 3 years, the more prominent feature is the multi-vortex structure. In the spring of these three years, the west of the upper Balabac Strait at a depth of 50 and 100 m was controlled by the circulation of the anticyclonic trend, especially in 1987. At a depth of 500 m, it was controlled by cyclonic circulation for 3 years. In 1986, there was a cyclonic circulation center in the southeastern waters of Vietnam, and its position was souther than the 50 m layer and the 100 m layer, and it was on the south side in 1985. The center of the upper-level cyclonic circulation was relatively northerly in 1986. It can be seen that the main axis of the southeastern Vietnam cyclone tilted northward in in 1985 and southward in 1986. Whether it is related to the baroclinic adjustment of the circulation needs to be further studied by numerical simulation methods.

2.5 Summary and Outlook The large-scale circulation in the South China Sea is characterized by an open “penetration”. After the water body of the Pacific Ocean enters the South China Sea through the Luzon Strait, in addition to flowing out of the South China Sea through the Taiwan Strait in the north, it will also flow out of the South China Sea through the Karimata Strait and Mindoro Strait in the southern part of the South China Sea. This chapter mainly reviews the characteristics of seasonal and interannual variation and its variation mechanism from the perspective of the SCS throughflow, and further discusses the dynamic connection between the SCS throughflow and the adjacent Indo-Pacific circulation, and reveals the variation of the trade wind anomaly in the Pacific Ocean. Under the influence of the ocean circulation adjustment, the interannual and long-term changes of the SCS throughflow and the Indonesian throughflow show antiphase characteristics, which confirms that the water body carried by the SCSTF flows from the Luzon Strait into the South China Sea, and then passes through the Karimata Strait in the southern part of the South China Sea. After the outflow from the Mindoro Strait, it will have an impact on the Indonesian throughflow, an important branch of the classic global thermohaline conveyor belt, so it has very important climatic significance. The South China Sea plays the role of heat and freshwater transport in the process of connecting the oceans. Through in-depth understanding

Fig. 2.59 Distribution of geostrophic currents during the spring voyages in 1985, 1986 and 1987 at different depth levels (Chen 2005)

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of the dynamic feedback of the South China Sea throughflow to the surrounding waters, especially its impact on the Indonesian throughflow, it can help us deeply understand the important potential impact of the South China Sea circulation, as a branch of the general Pacific-Indian Ocean throughflow on the climate change system. However, there are still many unresolved scientific issues in the study of the marine connection and dynamic mechanism between the South China Sea and the adjacent waters, such as whether there is a seasonal-scale dependence between the SCS throughflow and the surrounding circulation dynamics, and how to better understand the importance of the South China Sea circulation in the communication of the Pacific-Indian Ocean system in the context of global warming, there is still a long way to go.

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Wang Q, Cui H, Zhang S et al (2009) Water transports through the four main straits around the South China Sea. Chin J Oceanol Limnol 27(2):229–236 Wang W, Wang D, Zhou W et al (2011) Impact of the South China Sea throughflow on the Pacific low-latitude western boundary current: a numerical study for seasonal and interannual time scales. Adv Atmos Sci 28(6):1367–1376 Wei J, Li M, Malanotterizzoli P et al (2016) Opposite variability of Indonesian throughflow and South China Sea throughflow in the Sulawesi Sea. J Phys Oceanogr 46(10):3165–3180 Wyrtki K (1961) Physical oceanography of the Southeast Asian Waters. NAGA Rep 2:1–195 Wyrtki K (1974) Equatorial currents in the Pacific 1950 to 1970 and their relations to the trade winds. J Phys Oceanogr 4(3):372–380 Xiao X (2006) Three-dimensional variational ocean data assimilation system in the South China Sea. PhD thesis of South China Sea Institute of Oceanology, Chinese Academy of Sciences (in Chinese) Xie S, Chang C, Xie Q et al (2007) Intraseasonal variability in the summer South China Sea: wind jet, cold filament, and recirculations. J Geophys Res 112:C10008 Xu JP, Shi MC, Zhu BK et al (2004) Several characteristics of water exchange in the Luzon Strait. Acta Oceanol Sin 23(1):11–21 Yaremchuk M, Qu TD (2004) Seasonal variability of the large-scale currents near the coast of the Philippines. J Phys Oceanogr 34(4):844–855 Yu JY, Lau KM (2005) Contrasting Indian Ocean SST variability with and without ENSO influence: a coupled atmosphere-ocean GCM study. Meteorol Atmos Phys 90(3–4):179–191 Yu JY, Kao HY (2007) Decadal changes of ENSO persistence barrier in SST and ocean heat content indices: 1958–2001. J Geophys Res 112:D13106 Yu L, Weller RA (2007) Objectively analyzed air-sea heat fluxes for the global ice-free oceans (1981–2005). Bull Am Meteor Soc 88(4):527–539 Yu K, Qu TD (2013) Imprint of the Pacific decadal oscillation on the South China Sea throughflow variability. J Clim 26(24):9797–9805 Yuan D, Wang Z (2011) Hysteresis and dynamics of a western boundary current flowing by a gap forced by impingement of mesoscale eddies. J Phys Oceanogr 41(5):878–888 Zeng L, Liu WT, Xue H et al (2014) Freshening in the South China Sea during 2012 revealed by Aquarius and in situ data. J Geophys Res 119(12):8296–8314 Zhou W, Chan JCL (2007) ENSO and the South China Sea summer monsoon onset. Int J Climatol 27(2):157–167 Zhou H, Nan F, Shi M et al (2009) Characteristics of water exchange in the Luzon Strait during September 2006. Chin J Oceanol Limnol 27(3):650–657 Zhuang W (2004) The distribution characteristics and formation mechanism of upwelling along the coast of East Guangdong and Vietnam. Master’s degree thesis of Xiamen University (in Chinese) Zhuang W, Qiu B, Du Y (2013) Low-frequency western Pacific Ocean sea level and circulation changes due to the connectivity of the Philippine Archipelago. J Geophys Res 118(12):6759–6773

Chapter 3

The Northern Shelf and Slope Currents of the South China Sea

3.1 Introduction 3.1.1 The Continental Slope Current in the Northern South China Sea Cyclonic circulation exists in the northern part of the South China Sea all year round (Su 2004), the continental slope current is the northern flank of the cyclonic circulation in the northern South China Sea, located on the continental slope outside Dongsha Islands–Hainan Island–Jinsha Bay, with a depth of 200–1000 m. Early studies on continental slope current suggest that it flows southwest in winter and northeast in summer. Many subsequent observations have proved that even in the summer when the southwest monsoon is prevalent, the continental slope current still flows southwest and maintains a weak cyclonic circulation in the northern part of the South China Sea. For example, Xu and Su (1997) analyzed the results of 8–9 months ADCP data indicate that there is a southwestward slope current at the north slope of 19ºN, and the maximum velocity is about 0.3 m/s. The “South China Sea Warm Current Dynamics Experiment” from February to March 1982, the South China Sea Institute of Oceanology, Chinese Academy of Sciences, used the actual measurement results of ocean currents to prove that the winter flow field in the deeper waters of the northern South China Sea is dominated by baroclinic currents, that is, geostrophic currents with better representativeness. The isotherms and isodensity lines on the section crossing the continental shelf show a distribution trend of uplifting from the continental slope to the continental shelf, the temperature at the location of the slope current and the South China Sea warm current flow axis in winter decreases to the south and north, respectively, with obvious density flow properties (South China Sea Institute of Oceanology, Chinese Academy of Sciences (SCSIO) 1985). Su and Liu (1992) numerical simulation study on the circulation of the South China Sea concluded that the Kuroshio induced a cyclonic circulation in the South China Sea basin, covering the entire basin and located in the sea area 400 m away from the © Science Press and Springer Nature Singapore Pte Ltd. 2022 D. Wang, Ocean Circulation and Air-Sea Interaction in the South China Sea, Springer Oceanography, https://doi.org/10.1007/978-981-19-6262-2_3

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continental slope. They believed that the Kuroshio South China Sea branched as the northern part of the circulation, Its upstream is not a direct branch of the Kuroshio, but the recirculating water of the South China Sea with a small flow rate from the east side of the South China Sea to the north. Li (2002) believes that in winter, whether it is the Dongsha current, the Kuroshio South China Sea branch or the Luzon coastal current, they are part of the cyclonic local circulation in the northern South China Sea. The South China Sea Warm Current is a current flowing from the coastal area of eastern Guangdong and the deep water area off the coast of Guangdong to the northeast all the year round. Because it flows against the northeast wind in winter, it is called the winter upwind current (Guan 1998). In winter, except for the southward coastal currents in the surface and offshore areas, at a distance from the shore, at least from the 5 m level, the South China Sea warm current flows from the south to the north of the South China Sea, passes through the Taiwan Strait, and goes straight to the coastal waters of eastern Zhejiang and heading north (Guan 1978, 1985). When the wind is strong, the surface layer of the South China Sea warm current will be covered by the drifting southwest, but the flow from the surface to the deep is still northeastward (Guan 1985). The South China Sea warm current flows from the east of Hainan Island along the isobath to the coastal waters of eastern Guangdong, and the flow rate and amplitude of the warm current in the southeast of the Dongsha Islands is greater than that of the west, that is, there is a trend of increasing downstream, and the stability and durability of the South China Sea warm current and continuity are weak, with significant seasonal and inter-annual variation characteristics (Guo et al. 1985). The particularity of the South China Sea warm current is that it flows eastward against the west-north circulation on the land slope, especially when the warm current runs against the wind in winter, which is even more special. There have been many discussions on the formation mechanism of the South China Sea Warm Current, which can be roughly divided into the following categories. (1) The South China Sea Warm Current is caused by the Kuroshio invasion and the topographical interaction in the northern part of the South China Sea (Su and Wang 1987; Hong 1987; Zhong 1990; Huang et al. 1992; Yuan and Deng 1996; Hsueh and Zhong 2004). (2) Wind stress relaxation provides a transient force for the formation of the South China Sea warm current, which is the main cause of the South China Sea warm current, and the Kuroshio intrusion only plays a strengthening role (Chao et al. 1996; Chiang et al. 2008). (3) The South China Sea warm current is caused by the Ekman transportation caused by wind stress being blocked by the coast, which causes seawater to accumulate in the seas east of Hainan Island, which forms a clear slope along the continental shelf isobath from the east of Hainan Island to the coastal waters of eastern Zhejiang. (Zeng et al. 1989; Li et al. 1993). (4) Fang et al. (1998) believe that the downstream sea surface slope plays a controlling role in the formation of the South China Sea warm current; Ye (1994)

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believes that the winter circulation in the northern South China Sea is mainly a density flow caused by baroclinic thermodynamics; Yang et al (2008) believe that neither Kuroshio intrusion nor wind stress relaxation is the main mechanism for the generation of the South China Sea warm current, while the perennial northward current in the Taiwan Strait is the main mechanism for the generation of the South China Sea warm current.

3.1.2 Upwelling in Eastern Guangdong The coastal area of eastern Guangdong in the northern part of the South China Sea is a typical upwelling area, and the eastern Guangdong fish flood is formed from June to September each year. The upwelling in the northern part of the South China Sea includes the Qiongdong upwelling and the eastern Guangdong upwelling system. The southwest monsoon prevails in the northern part of the South China Sea in summer (June–August), the upwelling in the eastern Guangdong sea area is fully developed, and the cold bottom layer of high-nutrient salt water flows to the surface near the shore(Wu and Li 2003). The upwelling in the northern South China Sea is widely regarded as wind-driven upwelling (Shaw 1992; Li 1993; Su 1998; Hu et al. 2001). At the same time, the spatial distribution of upwelling is modulated by factors such as topography, coastal currents, and the Pearl River diluted water (Gan et al. 2009a, 2009b; Shu et al. 2011; Wang et al. 2012, 2014).

3.1.2.1

Wind-Induced Upwelling

Coastal wind stress is considered to be the most extensive and most important driving factor for coastal upwelling. Wyrtki (1961) first reported the existence of upwelling in summer in eastern Guangdong. During the same period, Niino and Emery (1961) also pointed out that there was an upwelling offshore Shantou. Since then, domestic and foreign scholars have conducted a lot of research and mechanism discussion on the upwelling in eastern Guangdong. Guan and Chen (1964) pointed out based on the national ocean census data that the summer southwest wind in the northern part of the South China Sea is the main driving mechanism for the upwelling in eastern Guangdong. It is generally believed that there are two main processes that may produce wind-induced upwelling: without taking into account the submarine friction, the southwest monsoon prevailing in the northern part of the South China Sea in summer will generate offshore currents in the surface Ekman layer, and the offshore movement of the water body in the surface Ekman layer will lead to the divergence of the upper water body near the shore, thus forming the convergence of deep cold water at the bottom and forming the eastern Guangdong upwelling (Rossi et al. 2010). Wang et al (2012) analyzed satellite and voyage observations and confirmed that the intensity of upwelling near the coast of East Guangdong is closely related to the changes in wind fields. The nearshore wind-induced upwelling theory

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considering bottom friction shows that the offshore transport of surface Ekman layer water will form a pressure gradient perpendicular to the shore, thereby inducing a northeastward coastal current in the subsurface layer. Due to bottom friction, this coastal current will drive the shoreward movement at the bottom layer, transporting deep-layer cold water uphill, and forming upwelling in eastern Guangdong (Shaw 1992; Li 1993; Su 1998; Hu et al. 2001). So far, the southwest wind along the coast in summer is considered to be the main mechanism of upwelling in the northern part of the South China Sea (Yu 1987; Zeng 1986; Gan et al. 2009a; Jing et al. 2011; Gu et al. 2012).

3.1.2.2

Topographically-Induced Upwelling

Relevant research work shows that topography mainly affects upwelling through the following two possible ways: The first is to influence the spatial change of upwelling intensity through topography; the second is to directly induce upwelling through the interaction of topography and coastal currents. Gan and Allen (2002) pointed out that coastal topography is an important reason for the spatial distribution of wind-induced upwelling: In the wind-driven upwelling area, the distribution of the coastal topography controls the direction of the coastal current, and the mass transport perpendicular to the shore is modulated by the geostrophic balance, thereby affecting the spatial distribution of upwelling intensity. Hong and Li (1991) analyzed many years of historical data and pointed out that there are obvious spatial differences in the upwelling in eastern Guangdong in summer and strong interannual variability. Gan et al. (2009b) studied the influence of the widened continental shelf terrain in the northern South China Sea on the upwelling under the condition of ideal wind, and found that the widened continental shelf terrain in the eastern region of Guangdong induced the westward pressure gradient force, thus enhancing the intensity of the wind-generated upwelling near Shantou. Oke and Middleton (2000) pointed out that terrain not only affects the spatial distribution of wind-induced upwelling, but also can generate upwelling when it interacts with coastal currents. For the southwest-northeast trending submarine topography of the northern hemisphere, according to the theory of stratification and rotating fluid, even if there is no wind, the northeastward coastal current in the bottom Ekman layer will cause the bottom layer to transport to the shore, forming a topographicinduced upwelling (Hsuesh and O’Brien 1971). However, according to the thermal wind relationship between the bottom Ekman layer and the inner zone, the cold and heavy water transported from the bottom layer to the shore will produce a horizontal pressure gradient to the bank, and cause the vertical shear strengthening of the coastal current near the bottom layer. This vertical shear weakens the coastal currents near the bottom layer and reduces the bottom friction, thereby inhibiting the transport of the bottom layer to the shore, causing the upwelling to close (or called buoyancy capture) (Brink and Lentz 2010). MacCready and Rhines (1993) showed that if the bottom friction is increased in certain areas, the increased bottom friction will increase the vertical viscosity coefficient, leading to strong vertical

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mixing in the bottom Ekman layer, reduce the vertical stratification of the water body, weaken the pressure gradient between the Ekman layer and the inner zone toward the bank, which will adversely affect the transportation to the bank. Therefore, the large bottom stress can drive the inshore transport of the bottom Ekman layer and produce upwelling. The enhancement of bottom stress in certain areas is often caused by the changes in the bottom topography of the coast. Therefore, previous studies called the upwelling caused by the interaction between this topography and the coastal current as topographically-induced upwelling. The topographically-induced upwelling exists in multiple shelf areas, such as the Gulf Stream Region of Guinea (Ingham 1970), the continental shelf region of East Australia (Oke and Middleton 2000), and northeastern Taiwan (Chen 1994). Most areas found to have topographically-induced upwelling have an obvious feature: There is a sudden widening of the continental shelf topography along the coast (Oke and Middleton 2000). This is very similar to the coastal topographic changes in the eastern Guangdong region of the northern South China Sea. Shu et al. (2011) used ensemble Kalman smoothing and reanalysis data in the northern part of the South China Sea, found that the coastal bottom friction in the widened continental shelf area (especially the sea off Shantou) suddenly strengthened, and topographicallyinduced upwelling may be the main reason for the difference in the spatial distribution of upwelling in this area. Gan et al. (2015) studied the evolution of the upwelling in eastern Guangdong with the wind field in summer, and found that the topographically-induced upwelling plays an important role in the upwelling maintenance and disappearance stage.

3.1.3 Pearl River Diluted Water Plume Diluted water refers to the water body with low salt, low density and high buoyancy formed in estuaries and shelf sea areas after fresh water enters the ocean through rivers on land and mixes with high-salt seawater. The diluted water plume is a plume-like flow that is driven by buoyancy caused by the difference in density between the diluted water and the surrounding seawater and is driven by external forces such as wind, tides, and large-scale background circulation. Diluted water plumes often carry a large amount of terrestrial nutrients and sediments, so it is easy to distinguish them from the surrounding seawater by the color of the water body near the coastal estuary area. Zu et al. (2014) pointed out in a review of research work on continental shelf diluted water plumes that idealized numerical simulations (Chao and Boicourt 1986; Yankovsky and Chapman 1997) showed that, in the case that the northern hemisphere is not affected by external forces such as wind, tide and continental shelf circulation, fresh water in rivers will form a bulge of anticyclonic circulation structure as shown in Fig. 3.1a and a buoyancy driven current with a narrower width and turning to the right in the direction of Kelvin wave propagation when it is pumped into the continental shelf sea area. Such a plume of diluted water belongs to a supercritical

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state (Chao 1988a; Kourafalou et al. 1996a), floating on high-salt sea water is surfaceadvected transport, but it is not common in nature (Garvine 2001). Corresponding to this, as shown in Fig. 3.1b, there is only a weak (or no) bulge outside the estuary and a buoyancy driven current with a similar width moving to the right near the shore. Such a plume of diluted water belongs to a subcritical state (Chao 1988a; Kourafalou et al. 1996a), which is manifested as seafloor-advected transport and can feel seafloor friction, can be obtained by adding background circulation on the shelf in the same direction as Kelvin wave or wind stress in favor of descending flow in ideal numerical simulation (Garvine 2001). Changes in external physical forces such as runoff, wind and tide in the natural environment make the more common pattern of diluted water plume is a combination of the above two, which is manifested as seafloor-advected transport on the nearshore side and sea surface-advected transport on the offshore side. In the natural environment, affected by wind, tides, shelf circulation and changes in freshwater runoff, the diluted water plume exhibits a more complex threedimensional structure and movement characteristics. For example, during periods when upwelling favorable winds are prevailing, Ekman transport and wind-driven coastal currents, which travel in the opposite direction to the nearshore Kelvin wave, Horizontal structure of diluted water

Vertical structure of diluted water

a. Surface-advection transport under supercritical conditions

b. Seabed-advection transport under subcritical conditions

Fig. 3.1 Horizontal and vertical structure diagram of diluted water on the shelf (Yankovsky and Chapman 1997)

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105

the diluted water will move in the opposite direction to the offshore and Kelvin wave propagation (Chao 1988b; Choi and Wilkin 2007; Fong and Geyer 2001; Gan et al. 2009a; Berdeal et al. 2002; Kourafalou et al. 1996b; Lentz. 2004; Whitney and Garvine 2005). The diluted water plume responds very quickly to changes in wind and coastal circulation, the wind favorable to upwelling and the diversion of the coastal current will cause the low salt water to escape from the main body of the diluted water plume, forming an independent low salt water mass on the continental shelf (Wolanski et al. 1999). In addition, changes in the water mixing rate caused by wind and tides will directly affect the vertical structure of the flush water plume, thereby changing its movement characteristics (Chao 1990; Hetland 2005; Guo and Valle-Levinson 2007; Simpson 1997; Simpson et al. 1990; Xing and Davies 1999; Zu and Gan 2009). In addition, the buoyancy flux that the low-density diluted water plume inputs to the continental shelf sea area, also influences the structure of the continental shelf circulation and the offshore tide by changing the water stratification and pressure gradient force.

3.2 South China Sea Warm Current 3.2.1 Numerical Simulation of the South China Sea Warm Current The numerical model uses the Princeton Ocean Model (POM) (Blumberg and Mellor 1987). The model water depth adopts ETOPO5 data, and the 10 m isobath is used as the dividing line between water and land points in the model. The grid adopts a curved orthogonal grid (Fig. 3.2). The horizontal grid resolution of the model is 13–29 km, and the vertical σ coordinate is divided into 25 layers. The initial field uses WAO01 temperature and salinity field, the lateral boundary uses the global assimilation product SODA data, the wind field uses HR data, and the heat flux uses OAFLUX data. There are relatively few current measurement data in the South China Sea, Guan (1986) summarized the observed velocities in the 10 m layer of the sea of the southeast coast of China in winter (Fig. 3.3b), covering the coastal and continental shelf of the northern South China Sea and the sea area near Taiwan. In order to verify the model results, the winter velocity of the 10 m layer simulated by the model was plotted in the same area as Fig. 3.3b (Fig. 3.3a). From the comparison between Figs. 3.3a and b, it can be seen that the flow velocity distribution characteristics simulated by the model are relatively close to those observed. From simulation and observation results, it can be found that the South China Sea warm current originated on the east side of Hainan Island and basically flows along the isobath toward the Taiwan Strait. The simulated coastal current of Guangdong can also be clearly seen inside the shelf. The slope current opposite to the South China Sea Warm Current on the south side

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Taiwan Strait Sec. II Sec. I Kuroshio SCSEast western boundary Vietnam

Luzon Strait

Mindanao Current

Karimata Strait

Sibutu Passage

Fig. 3.2 Model calculation area and horizontal grid distribution (Hongbo 2006) 200 m and 1000 m isobaths are superimposed in the figure

of the South China Sea Warm Current can also be confirmed in the research of Guo et al. (1985) (Fig. 3.3c).

3.2.2 Momentum Balance of the South China Sea Warm Current The three-dimensional momentum equation can be expressed as vt + V · ∇v − Am vx x + f u + Py − (K m vσ )σ = 0

(3.1)

u t + V · ∇u − Am u x x − f v + Px − (K m u σ )σ = 0

(3.2)

where V represents the velocity vector (u, v, w); f represents the Coriolis force parameter; P is pressure; K m represents the mixing coefficient of vertical turbulent kinetic energy; Am represents the horizontal eddy viscosity coefficient. Each term in the equation represents the time variation term (a), the nonlinear horizontal advection

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107

Fig. 3.3 Comparison of winter model simulation results and observation results. a Model simulation of 10 m layer velocity; b Observed 10 m layer velocity distribution (Guan 1986); c Sea surface dynamic height (calculated based on field observation data relative to 500db) (Guo et al. 1985)

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diffusion term (b), the Coriolis force term (c), the pressure gradient term (d) and the vertical diffusion term (e). The momentum equation includes the three-dimensional structure of the circulation field and represents the three-dimensional momentum balance mode in the real ocean. The horizontal viscosity coefficient and vertical mixing coefficient here are all calculated by subroutines inside the POM model. In the northern continental slope area of the South China Sea, select two transects that cross the continental slope and mark them as transect I and II from west to east (Fig. 3.2). First, each term in Eqs. (3.1) and (3.2) is integrated vertically to obtain the estimated values of terms in the momentum equation under positive pressure. Figure 3.4 shows the momentum equation balance method of transect I and II along the slope direction and along the slope under barotropic conditions. It can be seen from Fig. 3.4 that in the direction of crossing the shelf, the various terms of the momentum equation show the characteristics of geostrophic balance, in addition, the direction of the pressure gradient and Coriolis force from the nearshore to the open sea has changed twice, corresponding to the coastal current, the South China Sea warm current and the continental slope current in the continental shelf/slope area. In the direction of the continental shelf, wind stress, pressure gradient force and Coriolis force are the main balance items, showing the characteristics of nongeostrophic balance. The prevailing wind direction in the northern part of the South China Sea in winter is roughly parallel to the direction along the shelf, and from the perspective of the circulation field, the mainstream axis direction of the current system in this sea area is roughly parallel to the direction of the shelf, and there is no prevailing current system in the direction across the continental shelf. The diagnostic analysis of the three-dimensional momentum equation can further reveal the dynamic balance mode inside the circulation field. The spatial distribution characteristics of items in Eq. (3.1) on transect I, II are shown in Fig. 3.5. Except for the pressure gradient term and the Coriolis force term, the magnitude of the other terms is very small, indicating that in the direction of crossing the shelf, the Coriolis force term and the pressure gradient term are the dominant terms of the momentum balance, while the other terms have relatively small contributions to the momentum balance. From the perspective of spatial structure, the pressure gradient term (d) is negative in the continental shelf area and positive in the continental slope area, that is, the direction of the pressure gradient points to the inshore and offshore sea respectively in the continental shelf area and the continental slope area, indicating that there is a high value zone of pressure gradient in the continental shelf break zone in the northern South China Sea, resulting in the reverse of the pressure gradient in the continental shelf and the continental slope area. The spatial structure of Coriolis force (c) in the shelf area and the slope area indicates that the Coriolis force has the opposite direction in the shelf area and the slope area, its positive value in the shelf area indicates that there is a northeastward current in the shelf area, from the circulation field, it corresponds to the South China Sea warm current; Its negative value in the continental slope area indicates that there is a southwestward flow in the land slope area, corresponding to the continental slope current. Figure 3.6 shows the spatial distribution characteristics of the momentum equation items along the shelf direction. It can be seen from Fig. 3.6 that the Coriolis force term

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109

a

b

c

d

e

f I

II

Fig. 3.4 The spatial distribution of each item in the vertical integral momentum equation on transect I and II (Hong 2006). a and b represent the momentum balance in the direction across the shelf; c and d represent the momentum balance along the shelf; e and f represent the slope topography at the location of the transect. PG represents pressure gradient

(c), pressure gradient term (d), and vertical diffusion term (e) are the dominant terms for the upper ocean momentum balance of the continental shelf/slope area, and the contributions of other items are small. In the direction along the continental shelf, because the winter wind is roughly parallel to the direction along the continental shelf, the vertical mixing of the upper ocean is enhanced under the action of wind stress, and the flow field is in a non-geostrophic balance state, but in the lower layer, the continental slope current still has some characteristics of geostrophic current. In addition, comparing the spatial distribution of items in section I and section II, it can be found that the Coriolis force term (c) of section I is in the opposite direction to that of section II, where the Coriolis force term of section I is positive, indicating the presence of onshore flow here, while the Coriolis force term of section II is negative, indicating the presence of offshore movement here. This difference indicates that there is transport across the continental shelf in the northern shelf/slope area of the South China Sea, and there seems to be weak anticyclonic motion on the outer edge of the shelf. By comparing Figs. 3.5 and 3.6, it can be found that the magnitude of momentum equation items along the continental shelf direction is smaller than those across the continental shelf direction, which is consistent with the prevailing flow direction along the continental shelf in the northern part of the South China Sea, that is, the intensity of trans-continental shelf transport is much weaker than that of the continental slope current, the South China Sea warm current and the coastal current. The momentum equilibrium relationship between the SCS Warm Current and the continental slope current indicates that momentum and mass exchange exist between the two currents.

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a

a

b

b

c

c

d

d

e

e

Fig. 3.5 The spatial distribution of the momentum equation in the direction across the continental shelf on transect I (a1–e1) and II (a2–e2) (Hong 2006). a Time variation term; b Nonlinear horizontal advection diffusion term; c Coriolis force term; d Pressure gradient term; e Vertical diffusion term

3.2.3 Vorticity Balance of the South China Sea Warm Current The vorticity equation of the vertical integral can be written as: ∂ ∂ v ∂ u [ ( ) ( )] ∂t ∂ x D ∂ y D

=

−[u ·

∂ ( f )] ∂y D

+v·

∂ ( f )]+ ∂y D

a b τ τ curl( DF )+ curl( DA )+ curl( ρ Da )+ curl( ρ Db ) d e f g

J (Φ, D1 )]+ c (3.3)

3.2 South China Sea Warm Current

111

a

a

b

b

c

c

d

d

e

e

Fig. 3.6 Along the momentum equation on the shelf direction in the cross section I (a1 –e1) and II (a2–e2) on the spatial distribution of (Hong 2006). a Time change item; b Diffusion term of nonlinear horizontal advection; c Coriolis force term; d Pressure gradient term; e Vertical diffusion term

∫ η (∫ η ) where (u, v) = −H udz, −H vdz represents the velocity of vertical integra) ( tion; ∫ J Φ, D1 is the joint effect term of baroclinic topography (JEBAR), where / η Φ = −H zgρ ρ0 dz is potential energy, ρ is density, η is hydrocratic motion, and ( ) ( ) D = H + η is water depth. τx, τ y, a and τx, τ y, b are the stresses of the surface layer − → − → − → − → − → − → and the bottom layer respectively, and F = Fx i + Fy j and A = A x i + A y j are the horizontal advection term and horizontal diffusion term of vertical integration respectively. The a term at the left end of Eq. (3.3) is the relative vorticity change

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trend term; The b term at the right is the planetary potential vorticity advection (APV) term; c is Jebar item, d is horizontal diffusion item (DIF), e is horizontal advection item (ADV), f is surface stress tarque, and g is bottom stress tarque. Since this study analyzes the results of the seasonal average of climate states and the ocean state is close to the steady state, the trend term (a) of relative vorticity change is approximately zero. Figure 3.7 shows the spatial distribution of items at the right end of Eq. (3.3). The distribution of APV in the margin of the continental shelf is much larger than that in other regions, which indicates that the trans-continental shelf transport is very active in the whole northern continental shelf slope break region of the South China Sea, although there is trans-continental shelf transport in the inner shelf area, it is relatively weak. APV and JEBAR are the dominant items in the slope break area along the shelf. APV is mainly balanced by JEBAR, advection is the second contribution of the other items, and the bottom friction and surface wind field are only more obvious in shallow water. Because the transportation across the shelf is very active at the break of the shelf, the area of the 200–600 m isobath is the focus of the analysis. The cross-shelf velocity and vorticity equations are averaged between the 200 m and 600 m isobaths along the cross-shelf direction (Fig. 3.8). The results show that onshore current and offshore current exist alternately in the slope break region, and this is corresponding to APV. It can be seen from vorticity balance that the main contribution of equilibrium APV comes from JEBAR term. Although the size of these terms has seasonal variation, their spatial distribution is basically stable. From the above analysis, it can be found that JEBAR is the main driving force of transport across the continental shelf in slope break region. The same analysis in shallow water shows that JEBAR is no

Fig. 3.7 Spatial distribution of items in the vorticity equation (Hong 2006). The solid black line is the zero line; the isoline interval is 0.3 × 10–9 /s2 ; the white line is 400 m isobath

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113

longer the dominant factor, but advection, wind stress and bottom friction are the main contributors.

Fig. 3.8 Vertical distribution and vorticity balance of velocity across the continental shelf along the continental slope (Wang et al. 2010) Shaded sections represent rip currents, and the isoline interval is 2 cm/s

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3 The Northern Shelf and Slope Currents of the South China Sea

Fig. 3.9 Monthly average transport across the continental shelf (negative values indicate northward transport), APV distribution, and other items at the right end of Eq. (3.3) (Wang et al. 2010) All variables are integrated along the 200 m contour from 111.1° E to 117.2° E

Since both onshore and offshore currents exist at the slope break, it is necessary to calculate the cross-shelf flows. If there is a net shoreline transport at the slope break, then this shoreward transport can explain the source of the South China Sea warm water body. Based on this, the integral results of trans-continental shelf transport along 200 m isobath are calculated. The results show that there is net water transport from deep sea to shelf area throughout the year, and it is stronger in winter (Fig. 3.9a). The APV (Fig. 3.9b) and other vorticity terms (Fig. 3.9c) were also integrated. The results show that the APV shows the same trend, and when the APV reaches its maximum in December, the net onshore transport also reaches its maximum (1.28 Sv). It can be seen from the evolution of other terms of vorticity equation that JEBAR is the dominant term of equilibrium APV. The isobath of the northern shelf/slope area of the South China Sea is northeast-southwest, when the deep slope current moves westward under the action of wind field and density field, a movement across the equipotential vortex line f /H occurs under the JEBAR effect, when f remains unchanged, the fluid column will be compressed by the uplift of the topography, the climbing fluid will deflect to the right under the constraint of the principle of potential vorticity conservation, and finally reach a geostrophic balance with the pressure gradient force toward the shore, and becomes the source of water of the South China Sea Warm Current.

3.2.4 The Source Driving Force of the South China Sea Warm Current From the previous analysis, it can be seen that the governing equation for the direction across the flow axis of the South China Sea Warm Current can be written as (a 1.5-layer reduced gravity model with just cover) f u = −g ′

∂h ∂y

(3.4)

3.2 South China Sea Warm Current

115

where g ′ = g Δρ is reduced gravity; u is the velocity in the direction of counterρ0 clockwise rotation of 30° from the east–west direction, that is, the velocity in the downstream direction of the South China Sea Warm Current; h = h 0 + h ′ is the thermocline thickness, where h ′ is the disturbance of the thermocline depth. The thermocline equation can be written as follows (Liu et al. 2001): ∂h ′ ∂h ′ −C = −we ∂t ∂x

(3.5)

where C = β L 2D is the wave velocity of the first baroclinic Rossby wave, where H L 2D = g Δρ is the baroclinic deformation radius, H is the average thermocline ρo f 2 ( / ) depth. we = curl τ ρ0 f is the vertical movement of thermocline caused by Ekman pumping, where τ is the wind stress. Under the first-order approximation, the depth of the thermocline is inversely proportional to the height of the sea surface, that is, when the thermocline drops, the sea surface height rises, and vice versa. When advection is neglected, the change of thermocline depth is mainly controlled by the speed of Ekman suction. Let Eq. (3.5) partially differentiate time, and substitute Eq. (3.5) with the wave term omitted, we can get ∂u g ′ ∂we = ∂t f ∂y

(3.6)

It can be seen from Eq. (3.6) that the gradient of the Ekman suction velocity across the South China Sea warm current can drive the flow along the continental shelf. The right end term of Eq. (3.6) is essentially the time change of pressure gradient force in the direction across the South China Sea wam current, the gradient of Ekman pumping speed in the direction of the cross-current axis can cause the gradient of the change of thermocline depth, thus inducing the gradient of sea surface height in the direction of the cross-current axis. Figure 3.10 is the diagnosis result of the right end term of Eq. (3.6) based on the winter climate state data of ERA40, where g′ = 0.03 m/s2 , and only the positive distribution area of 50–200 m is drawn in the figure (indicating the positive contribution to the South China Sea Warm Current). As can be seen from Fig. 3.10, only in the area east of Hainan Island can the wind field drive the South China Sea Current through Ekman pumping, while in the middle segment of the continental shelf, the effect is opposite. There is a weak positive contribution to the South China Sea Current west of Taiwan, but its intensity is very weak and the range is very small, and it almost contracted into the Taiwan Strait. Through the above analysis, it can be found that the Ekman suction caused by wind stress has different effects on the east and west ends of the continental shelf, and the Ekman suction in the western section is closely related to the change of sea surface height, and the sea surface height gradient across the South China Sea Current caused by its spatial distribution can make a great contribution to the formation of the South China Sea Current. However, in the middle and eastern sections of the

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3 The Northern Shelf and Slope Currents of the South China Sea

Fig. 3.10 Contribution of Ekman suction to the South China Sea warm current (less than 0 not shown) (Wang 2013)

continental shelf, the effect of Ekman suction is different. On the one hand, the change of sea surface height does not show much correlation with Ekman pumping; on the other hand, the contribution of Ekman pumping to the sea surface gradient across the current axis is weak or opposite to that of the western section. Based on the positive contribution of Ekman pumping to the formation of the Western South China Sea Warm Current, it can be assumed that Ekman pumping is one of the important driving mechanisms of the South China Sea Warm Current at its source (east of Hainan Island). In order to research the effect of Ekman pumping, it is necessary to remove the effect of wind stress curl in the forced field of numerical experimentation. The simplest way to remove the wind stress curl is to use the regional average wind stress vector to replace the real wind stress field, but in order to obtain a more real largescale circulation structure of the South China Sea, the wind stress in the northern part of the South China Sea is only substituted here. However, when the regional wind stress is substituted instead of the whole simulated field, special treatment should be carried out at the boundary of the substituted region. Due to artificial substitution, a false wind stress gradient (i.e., artificial wind stress curl) is introduced at the boundary„ in order to reduce and avoid this phenomenon, a transition layer (9 grid points) is set at the boundary of the substituted area, so that the wind stress in the substituted area slowly approaches the real wind stress field of the periphery in the transition layer. After the average wind stress replaces the real wind stress field, in addition to eliminating the influence of wind stress curl, the magnitude of wind stress also changes, therefore, the replacement of wind field actually includes two changes of wind stress curl and wind stress magnitude. Figure 3.11 shows the ratio of the modified wind stress to the real wind stress. The wind stress increases at the

3.2 South China Sea Warm Current

117

eastern end of the shelf (east of about 118° E) after replacement, and is strongest along the coast and decreases southward. The variation of wind stress is 20–40% between 50 and 200 m isobath. However, in the mid-west end of the continental shelf, the increase of the near-shore wind stress is the most obvious, and gradually decreases across the continental shelf to the south, When it reaches the middle of the continental shelf (about the middle line of the 50 m isobath to the 200 m isobath), the sign of the wind stress increment changes, that is, the replaced wind stress is weaker than the real wind stress. The percentage change of wind stress at the central and western ends is −20% ~ 40%. The northeast monsoon is opposite to the South China Sea warm current, which attenuated the warm current. In order to distinguish the real wind stress after replacement, the change of the south China sea warm current is the change of the wind stress curl or the size of the wind stress change, in the second sensitivity test will be selected in this study area the size of the wind stress unity enhanced 50% (Do the same process at the boundary) is used to explore the wind stress size change on the influence of the south China sea warm current, The specific experiment design is listed in Table 3.1. Figure 3.12 shows the vertical profile distribution of the flow velocity of the selected east and west sections (marked in Fig. 3.11), a positive value indicates that the flow velocity is eastward and perpendicular to the section. It can be seen from the control test results that the South China Sea Warm Current is mainly located between 50 and 100 m isobath in the west section, and extends from the surface to the bottom, with the maximum flow velocity at about 10 m layer; However, in the eastern section, the southern boundary of the South China Sea Warm Current moves southward to the 150 m isobath, and the maximum velocity layer is basically

Fig. 3.11 The ratio of the modified wind stress (Exp1) to the change from the original wind stress (Wang 2013) (unit: %) The dashed line is the 50 m and 200 m isobath

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3 The Northern Shelf and Slope Currents of the South China Sea

Table 3.1 South China Sea warm current sensitivity test design Name of test

Design

Objective

Control test

Driven by real wind field

Real reproduction of the South China Sea Warm Current

Exp1

Driven by uniform wind field

Response of the South China Sea Warm Current without Wind Stress Curl

Exp2

Real wind field enhanced 50% drive

Response of South China Sea Warm Current to Increase Wind Stress

also located in the 10 m layer. By comparing the two sections of the South China Sea Warm Current, it can be found that the amplitude of the South China Sea Warm Current in the east section is about 0.6 latitude, while the amplitude span of the South China Sea Warm Current in the west section is about 1 latitude, and the velocity of the South China Sea Warm Current in the east section is obviously higher than that in the west section. When the wind stress curl in the northern wind field of the South China Sea is removed (Exp1), the South China Sea Warm Current on the western section almost disappears (Fig. 3.12b), and there is only a warm current center with a very small velocity (below 0.02 m/s) around the upper 20 m layer, and its flow amplitude is also greatly compressed, about 0.4 latitude; In the east section, the velocity of the South China Sea Warm Current decreases (the maximum isoline decreases from 0.1 to 0.06 m/s), but its current amplitude barely changes and even expands northward, but its vertical structure is almost consistent with the control experiment. After the wind stress increases by 50% (Exp2), the velocity of the South China Sea Warm Current at the west section (Fig. 3.12c) decreases slightly (the maximum contour decreases from 0.06 to 0.04 m/s), and its flow amplitude Narrows to about 0.8 degrees of latitude. By comparing the Exp1, Exp2 and control test results can be found, when the influence of wind stress curl in the northern part of the South China Sea is removed, the South China Sea Warm Current on the western section almost disappears, leaving only a small center of the South China Sea Warm Current. However, since the substitution of the average wind stress for the real wind field can not only eliminate the influence of wind stress curl, but also change the size of wind stress. Previous analyses have indicated that the wind stress varies by −20 to −40% in the western section of the continental shelf (50–200 m isobath), the change of wind stress magnitude has positive and negative, if only from the wind stress magnitude and the South China Sea warm current relationship, the South China Sea Warm Current should weaken in the region where the wind stress increases, while the South China Sea Warm Current should strengthen in the region where the wind stress weakens. Experimental results disproved this inference, the South China Sea Warm Current weakens obviously in the whole western transect, which indicates that the change of wind stress by the South China Sea Warm Current is not very obvious in the western transect of the continental shelf, but it is extremely sensitive to the change of wind stress curl. To further verify the above conclusions, after the wind stress is unified increased by 50%, the change of the West South China Sea Warm Current is not very obvious, which further confirms the important

3.2 South China Sea Warm Current

119

driving effect of wind stress curl on the western section of the South China Sea Warm Current. However, it can be seen from the results of EXP1 that even if the influence of wind stress curl is eliminated, the South China Sea Warm Current in the western segment does not completely disappear and the weak center of the South China Sea Current is still retained. In other words, wind stress curl is an important but not the only driving factor of the South China Sea Warm Current in the western segment of the continental shelf. The response of the South China Sea warm current on the east section to the wind field is completely different from that on the west section. The effect of removing wind stress curl or increasing wind stress on the South China Sea Warm Current in the eastern part of the continental shelf is not very obvious, which indicates that wind field is not an important driving mechanism of the South China Sea Warm Current in the eastern part of the continental shelf. In order to quantitatively analyze the different effects of Ekman pumping on the continental shelf of the South China Sea Warm Current in the east and west sections, further analysis was made on the Ekman pumping on the east and west sections and the distribution of sea surface height in different tests (Fig. 3.13). Along the west section, there is a peak of Ekman suction near 20° N, and the sea height calculated by the control test corresponds to this peak, the match between the two is consistent with the previous theoretical analysis and inference assumptions, that is, Ekman suction

Fig. 3.12 Vertical sectional distribution of velocity (Wang et al. 2011). a–c West section; d–f East section; a, d Control test; b, e Exp1; c, f Exp2. A positive value indicates that perpendicular to sections and eastward

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3 The Northern Shelf and Slope Currents of the South China Sea

induces the sea level to rise in the western section of the continental shelf, forming a sea level gradient toward the shore, which becomes the main contributor to the geostrophic constraint of the South China Sea warm current. The peak sea level near the shore corresponds to the accumulation of Ekman transport on the shore. After the contribution of wind stress curl is removed (Exp1), the peak value of sea surface height along the west section almost disappears and only a very weak peak value is retained, which is consistent with the previous analysis results. In the east section, the change of sea surface height distribution has little relation with the change of wind stress. At the same time this paper also calculated the vertical integration of two section water, the amount of divergence, and Ekman pumping speed of the contrast, can be found in the west section, on the one hand, the spatial distribution and the distribution of sea surface height is not consistent, on the other hand its value than the Ekman pumping speed of quantity at least an order of magnitude smaller, it shows that the change of the western sea surface height is mainly decided by the Ekman pumping speed. When the divergence is positive, the sea level drops; otherwise, the sea level rises, in the east section, the water divergence is in inverse phase with the sea level distribution. This correspondence indicates that the distribution of sea level in the eastern section of the shelf is mainly determined by the dynamic relationship within the ocean, and to a certain extent confirms the relationship between the Kuroshio intrusion into the South China Sea and the sea level in the eastern section of the shelf.

3.3 Upwelling of East Guangdong in South China Sea 3.3.1 The Spatial Distribution Characteristics of the East Guangdong Upwelling in the South China Sea There is a wide shelf area in the northern part of the South China Sea. Starting from the west of Shanwei, there is a widened shelf topography to the east (Fig. 3.14). The prevailing southwest monsoon in summer drives a strong upwelling in the eastern region of Guangdong. The regional distribution of upwelling in eastern Guangdong is very different. Figure 3.15 reveals the spatial distribution of summer upwelling in the northern South China Sea observed in 2000 and 2002 (Gan et al. 2009b). In summer, the coldest surface water temperature of upwelling in the northern South China Sea can be as low as 23 °C. During the voyage in 2000, a strong southwest monsoon prevailed, with upwelling cold water extending from the coast to the 50 m isobath. However, the coastal wind speed in 2002 was obviously weaker than that in 2000, and gradually weakened from west to east, so the intensity of upwelling was not as strong as that in 2000, and the range of upwelling was not as large as that in 2000. The strongest upwelling region of eastern Guangdong in the northern South China Sea is distributed in Shanwei and Shantou (Fig. 3.15). The regional distribution difference is mainly determined by the intensity of the coastal wind and

3.3 Upwelling of East Guangdong in South China Sea

121

-6

-6

x 10

x 10

b

a 0.1857

7.5 0.1857

7.5

0.1617

5

5

0.1378

2.5 0.1378

2.5

0.1139

0

0

0.09

ssh in control experient ssh in exp1 Ekman pumping divergence 21.2

21

20.8

20.6

20.4

20.2

20

19.8

-2.5

0.1617

0.1139

0.09

23.2

23

22.8

22.6

22.4

22.2

22

21.8

-2.5

Fig. 3.13 The height of the sea surface along the east and west sections (unit: m), Ekman suction distribution (unit: m/s) and seawater divergence (unit: m/s; multiplied by 10) (Wang et al. 2011)

the coastal topography. When the southwest monsoon is weak, the size of upwelling is small, and the area with strong upwelling intensity may appear in the sea off Shanwei. When the southwest monsoon is strong, the strongest upwelling intensity in the northern part of the South China Sea is located off Shantou. Figure 3.16 is the vertical temperature and salinity profiles of five sections selected from west of Shanwei to east of Shantou in 2008 simulated by the assimilation model. It can be seen that on the Shanwei west section and Shanwei section, the strength of the upwending current from the 50 m isobath is stronger than that of the other sections, the reason is that the isobath begins to converge off the west Shanwei sea and the velocity along the coast increases; Due to the effect of the bottom friction, the strong bottom eastward coastal currents leads to a strong westward bottom friction, which induces a strong shoreward Ekman transport. Thus, off the west side of Shanwei, strong bottom climbing brings deeper bottom cold water to shore. However, the surface upwelling intensity of the west side of Shanwei and the Shanwei section is relatively weak, and the 27 °C isotherm has no outcrop on the surface. There are two possible reasons for this: On the one hand, it can be seen from the distribution of salinity section that the Pearl River diluted water expands from the shore to the east on these two sections in summer, and the surface low-salt fresh water strengthens the vertical stratification, and the strong stratification inhibits the upwelling from rising

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3 The Northern Shelf and Slope Currents of the South China Sea

Fig. 3.14 Terrain of the Northern South China Sea (Wang et al. 2014). GCC is the coastal current of Guangdong in summer; SCSWC is the South China Sea Warm Current

a. The sea surface temperature in 2000

b. The sea surface temperature in 2002

Fig. 3.15 SST observed by CTD during voyage (Unit: °C) (Gan et al. 2009b)

to the surface in the west of Shanwei; On the other hand, Gan et al. (2009b) believe that in the upstream area of the broadening continental shelf topography, the coastal currents on these two sections are relatively strong, and when the cold water climbing from the bottom has not had time to rise to the surface, the strong coastal currents will transport the advection of the cold water climbing to the downstream and gradually outcrop from Shanwei to Shantou. Therefore, on the surface, the strength of the upwelling is stronger in Shantou than in Shanwei. The distribution of the bottom temperature and salinity along these five sections shows that the bottom temperature (24 °C) and salinity (34 psu) are not continuous in Shantou, which further proves that the low temperature and high salt water in the bottom of Shantou comes from the upstream advection. When the southwest monsoon is weak, the advection effect is correspondingly weakened, and the cold water climbing from the bottom can appear at the surface near Shanwei, which explains why the intensity of upwelling

3.3 Upwelling of East Guangdong in South China Sea

123

Shanwei west

Shanwei

Shantou west

Shantou

Shantou east

Fig. 3.16 Vertical distribution of temperature and salinity at five sections selected from west Shanwei to east Shantou in 2008 simulated by assimilation model (Shu et al. 2011)

is occasionally observed to be stronger near Shanwei than in other regions under the weak southwest monsoon.

3.3.2 Response of Eastern Guangdong Upwelling to Variable Wind Field in the South China Sea The southwest monsoon in the northern part of the South China Sea has strong temporal and spatial variations, and there are often many wind field events unfavorable to upwelling during the southwest monsoon (Fig. 3.17a). During the voyage in 2000 (10 July to 22 August), the sea surface wind field before 21 July was generally unfavorable to the development of upwelling, from July 21, southwesterly winds favorable to upwelling began to prevail over the northern part of the South China Sea. Before July 21, there was no upwelling phenomenon in SST distribution; However, after July 21, there was an obvious upwelling in eastern Guangdong (Fig. 3.17b, c).

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3 The Northern Shelf and Slope Currents of the South China Sea

Fig. 3.17 Wind speed in eastern Guangdong of Quikscat in summer 2000 (a), average wind vector and SST distribution from July 10–21, 2000 (b), and average wind vector and SST distribution from July 22, 2000 solstice to August 2, 2000 (Wang et al. 2012)

The regional wind field in eastern Guangdong is divided into two categories: southwest wind which is favorable to upwelling development and northeast wind which is unfavorable to upwelling development, and then the SST during the two prevailing wind fields were respectively synthesized and analyzed, and the results are shown in Fig. 3.18. When the southwest wind is prevailing, the coastal upwelling of east Guangdong mainly occurs from Shanwei to Fujian. On the south side of Taiwan Shoal, there is also a cold SST distribution. During the period of unfavorable upwelling development, cold SST also existed in the southeast of Shantou. The formation of this surface cold water may be caused by the interaction of topography and coastal currents, which we will discuss later. In addition, there is a persistent low temperature area on the south side of Taiwan Shoal. The formation of cold water on the sea surface in this region is obviously different from the formation mechanism of wind-generated upwelling. The formation of this cold water is probably caused by the interaction between tides and topography, i.e., the upwelling caused by the strong tide-induced mixing. In conclusion, the intensity of upwelling in the coastal area of eastern Guangdong, especially from Shanwei to Shantou, is relatively sensitive to the variation of coastal wind field. However, the fact that low temperature water on the sea surface can still be observed in Shantou during the prevailing northeast wind

3.3 Upwelling of East Guangdong in South China Sea

125

Fig. 3.18 Synthetic analysis field of AVHRR SST and QuikScat wind field with positive zonal component of wind speed (a) and the synthetic analysis field with negative zonal component (b) (Wang et al. 2012)

indicates that the upwelling in this region is not completely closed due to the force of unfavorable upwelling wind field. Based on the ocean current observation data from June 1, 2000 to July 30, 2000 at the depth of 100 m south of Shanwei (21.89° N, 115.5° E), near the bottom of the submersible buoy (85 m), it is found that the near-bottom current is closely related to the anomaly of the sea surface height at Shanwei Tidal Survey Station (Fig. 3.19). The correlation coefficient between the coastal current and the current perpendicular to the shore and the Sea level anomaly reaches 0.92 and 0.86 respectively, which is mainly due to the geotransition relationship in the inner ocean, the shoreward pressure gradient force is mainly in balance with the offshore Coriolis force caused by the littoral current, so the decrease of the nearshore sea surface height increases the shoreward pressure gradient force, leading to the strengthening of the littoral current. In the bottom Ekman layer, the enhanced littoral current will increase the reverse bottom friction, which will induce a shoreward bottom current, resulting in the coastal Coriolis force equilibrium and the enhanced reverse littoral friction. Therefore, there is a good correlation between coastal wind field, Sea level anomaly, bottom current and upwelling intensity in the upwelling area of wind-generated continental shelf. This relationship can be reproduced well in both observation and simulation (Fig. 3.19). Using the results of an assimilation model, the response of surface upwelling signals to varying wind fields is studied. Figures 3.20 and 3.21 show the changes of temperature, salinity and velocity profiles with time in Shanwei and Shantou offshore sections from June 30 to July 10, 2008 respectively. During this period, the wind field in the northern part of the South China Sea experienced a change from the wind field that was favorable for upwelling (before July 2) to the wind field that was unfavorable for upwelling (July 3–6) to the wind field that was favorable for upwelling (July 7–10). Figure 3.20 shows that the intensity of cold water climbing ashore near the bottom of Shanwei is stronger than that of Shantou. However, during the prevailing period of favorable upwelling wind field, the intensity of upwelling on

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3 The Northern Shelf and Slope Currents of the South China Sea

Fig. 3.19 Trend of velocity and daily average temperature along the coast and perpendicular to the shore from subsurface buoy observation (a) and simulation (b) in eastern Guangdong (dT /dt) and SLA comparison (Wang et al. 2012)

the surface of Shantou is slightly stronger than that of Shantou. The 24 °C isotherm at the bottom of Shantou is not continuous, which indicates that the cold water at the surface of Shantou upwelling is not the direct ascent of the bottom cold water from the outer sea along the continental slope, but is probably the advection of the bottom cold water rising from the outer sea to the shore of Shantou and then to the surface water at the outer sea. This is consistent with the research results of Gan et al. (2009b). From June 30 to July 6, when the wind direction changed from favorable to upwelling to unfavorable to upwelling, the intensity of the coastal current and the velocity from the bottom to the shore weakened (Fig. 3.21), and the vertical structure of temperature indicated that the upwelling gradually weakened, and the signal of the surface upwelling completely disappeared on July 6 (Fig. 3.20).When the wind field turns to be favorable for upwelling again (July 7–10), the velocity of the coastal current and the bottom to the shore increases, and the surface upwelling develops rapidly (Figs. 3.20 and 3.21). In general, the upwelling intensity gradually weakens when the wind field changes to a wind direction unfavorable to upwelling. However, when the wind field changes to a wind direction favorable to upwelling again, the upwelling intensity will soon be rebuilt. Moreover, as shown in Figs. 3.20 and 3.21, the closing time scales of Shanwei and Shantou upwelling are different.

3.3 Upwelling of East Guangdong in South China Sea

127

By July 4 the Shanwei Upwelling was almost closed, but the Shantou Upwelling continued to exist until July 6.The main reason is that when the upwelling wind field relaxes (disappears), the closing time scale of upwelling is closely related to the local topography and stratification (Oke and Middleton 2000): τs =

f (N α)2

where τs is the time scale of upwelling closure; is the buoyancy frequency; α is the topographic slope. Because the slope of Shanwei Sea is larger than that of Shantou Sea, the time scale of upwelling closure is shorter.

Fig. 3.20 Temperature and salinity distributions of Shanwei and Shantou offshore sea crosssections at different times in summer 2008 simulated by assimilation model (Shu et al. 2011)

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3 The Northern Shelf and Slope Currents of the South China Sea

Fig. 3.21 Distribution of coastal velocities (columns 1 and 3) and perpendicular to shore velocities (columns 2 and 4) at Shantou and Shanwei cross-sections at different times in the summer of 2008 simulated by assimilation model (unit: m/s) (Shu et al. 2011)

3.3.3 Contributions of Wind and Topography to the Upwelling in Eastern Guangdong, South China Sea As mentioned above, the interaction between the changing coastal topography and the coastal current can also induce upwelling. In the northern part of the South China Sea, the continental shelf is widened eastward from the Shanwei Sea, and in the Shanwei Sea, the shallow water area is widened outwards again because of the existence of the Taiwan Shoal. The interaction between the sharply widened shallow water topography of the continental shelf and the large-scale northeasterly current of the northern South China Sea in summer also induces upwelling, that is, the upwelling in the northern South China Sea is both wind-driven and topography-induced upwelling.

3.3 Upwelling of East Guangdong in South China Sea

129

Topographically-induced upwelling in the northern South China Sea was observed in four voyages to the northern South China Sea. The observation time of these four voyage sections all occurred more than 10 days after the wind field unfavorable to upwelling prevailed (Fig. 3.22). However, significant low-temperature and high-salt water body climbing at the bottom was observed on both sections (Figs. 3.23 and 3.24). This upwelling phenomenon is caused by the interaction between topography and large-scale circulation and is called topographically-induced upwelling. In order to confirm that the subsurface isotherm climbing phenomenon observed during the voyage is Topographically-induced upwelling, we conducted four sensitivity tests using a high-resolution ocean model, and then studied the relative contribution of topography and local wind field to the upwelling intensity in the northern South China Sea. The pattern area is shown in Fig. 3.14. In the test, the model started from quietness, and the initial temperature and salinity were the same throughout the region. The vertical stratification was from the August WOA09 dataset, and the

Fig. 3.22 The spatial average wind field in the open waters of eastern Guangdong during the summer and autumn voyage observations in 2000, 2005, 2009 and 2011 Wang et al. (2014)

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3 The Northern Shelf and Slope Currents of the South China Sea

Fig. 3.23 Temperature distribution in the eastern Guangdong cross-sections in 2000, 2005, 2009 and 2011 after a long period of unfavorable upwelling wind prevailing Wang et al. (2014)

Fig. 3.24 Salinity distribution in the eastern Guangdong cross-sections in 2000, 2005, 2009 and 2011 after a long period of unfavorable upwelling wind prevailing Wang et al. (2014)

lateral boundary was the August inflow of climate state provided by the nested South China Sea circulation model. The large-scale circulation information of climate state is transmitted to the inner region through the lateral boundary. Surface fresh water and heat fluxes were set to 0. Test 1: Set southwest wind force of 4 m/s with consistent space; Test 2 was similar to test 1, except there was no wind field forcing on the surface. Test 3 is similar to test 2, except that the inflow intensity at the side boundary is reduced by half, which represents the reduction of large-scale circulation. The difference between test 4 and test 2 is that the inflow intensity at the side boundary increases by half. The sensitivity test setting above shows that test 1 represents the upwelling intensity of the regional climate state in eastern Guangdong in summer. Test 2 represents the topographically-induced upwelling in eastern Guangdong, and test 3 and

3.3 Upwelling of East Guangdong in South China Sea

131

4 represent the influence of weakening and strengthening of large-scale circulation in eastern Guangdong on the topographically-induced upwelling intensity, respectively. Figure 3.25 shows the simulated SST of the four tests on the 30th day. The simulation of test 1 showed that the upwelling in eastern Guangdong was mainly distributed in Shanwei and Shantou coastal areas under climate conditions, which was consistent with the previous research results (Fig. 3.25a). In test 2, although there was no wind forcing in favor of upwelling and the whole field was standard stratification at the initial moment, the interaction between large-scale circulation and topography would also induce strong upwelling (Fig. 3.25b). This proves that a large part of the upwelling in eastern Guangdong is topographically induced. The topographically-induced upwelling has two areas of high intensity, one is off Shantou Sea and the other is off Shanwei Sea. This is consistent with the local widening of the shallow topography of the northern South China Sea off Shanwei and Shantou respectively. When the large-scale circulation weakens by half, the topographically-induced upwelling basically disappears in the surface layer (Fig. 3.25c); At the same time, when the intensity of large-scale circulation increases by half, the topographicallyinduced upwelling intensity became strong, even exceeding the combined intensity of wind-induced upwelling and topographically-induced upwelling in climate states (Fig. 3.25d). In order to quantitatively analyze the contribution of topography and local wind field to the upwelling in East Guangdong, the upwelling index is introduced (Nykjær and Van Camp 1994):

Fig. 3.25 SST distribution on the 30th day simulated by four sensitivity tests (Wang et al. 2014)

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3 The Northern Shelf and Slope Currents of the South China Sea

Σ N ( Ikt

=

i=1

t0 t − Ti,k Ti,k

N

) (3.7)

where I is the upwelling intensity index; k is the model sigma layer; t stands for time; t0 is the first day of the model simulation; i is the pattern grid point; T is the simulated temperature; N is the number of samples. Here I represents the change of upwelling intensity with time. Considering that the upwelling flow mainly occurs between Shanwei and Shantou, a box region is defined within this range (Fig. 3.14). Compared with the first day, the SST index of Exp 1 and Exp 2 decreased by 3 °C and 2.3 °C on the 30th day, respectively (Fig. 3.26). When the intensity of largescale circulation was halved (Exp 3), the SST index on the 30th day decreased by about 1 °C compared with that on the first day. However, when the intensity of large-scale circulation increased by half (Exp 4), the intensity index of both surface and seafloor upwelling was stronger than Exp 1. This indicates that the strength of upwelling in surface layer is sensitive to the strength of large-scale circulation. In the near bottom layer, the topographically-induced upwelling intensity index (Exp 2) was only slightly weaker than Exp 1. This indicates that the topographically-induced upwelling intensity in the surface layer is approximately the same as that in the windinduced upwelling intensity, while the topographically-induced upwelling intensity in the bottom layer is dominant due to the interaction between large-scale circulation and topographically-induced upwelling. The climb of cold water near the bottom caused by local wind field acting on local circulation may be less than that caused by large-scale circulation.

Fig. 3.26 Time series of upwelling intensity of the surface and bottom layers simulated by 4 sensitivity tests Wang et al. (2014)

3.3 Upwelling of East Guangdong in South China Sea

133

The upwelling intensity should be most directly expressed in the vertical motion, that is, the vertical velocity. The relative contribution of topographically-induced upwelling can be directly defined using simulated vertical velocities: C=

wt ⎟⎟ ⎟ w wt >0 and w>0

(3.8)

where C is the relative strength index of upwelling flow; wt is the vertical velocity of topographically-induced upwelling (exp 2); w is the vertical velocity of exp 1. A value of C is close to 1, indicating that topographically-induced upwelling is dominant, while a value of 0 indicates that wind-induced upwelling is dominant. The vertical velocity distribution of exp 1 and exp 2 also showed that the upwelling in eastern Guangdong was mainly distributed between Shanwei and Shantou (Fig. 3.27). The relative intensity index of topographically-induced upwelling is close to 1 in most areas below 50 m from the bottom, which further indicates that the topographicallyinduced upwelling in eastern Guangdong has a stronger upwelling effect near the bottom than the local wind-induced upwelling. The bottom friction caused by the coastal current and the changing topography are the main reasons for topographically-induced upwelling. Its main explanation is that the bottom Ekman dynamic process induces the bottom water to climb to the shore, and the bottom friction is strongest in Shanwei and Shantou open waters (Fig. 3.28a, b), strong bottom friction increases the vertical viscosity coefficient, causes strong vertical mixing in the bottom Ekman layer, reduces the vertical stratification of the water body, and increases the time scale of the upwelling closure, so that the topographically-induced upwelling can be maintained. In other words, the strength of topographically-induced upwelling is closely related to the strength of bottom friction. By comparing the spatial distribution of upwelling intensity (Fig. 3.27) and bottom friction (Fig. 3.28a, b), it is found that the spatial distribution of upwelling intensity is not consistent with that of bottom friction, but has a good spatial consistency with the curl of friction (Fig. 3.28c, d). The reasons are as follows.

Fig. 3.27 Vertical velocities (1 × 10–4 m/s) on the 30th day of the spinup mode with wind a and no wind b and the ratio of vertical velocities between Exp 2 and Exp 1 c under the background of large-scale flow field in summer (Wang et al. 2014), and contour lines are isobaths

134

3 The Northern Shelf and Slope Currents of the South China Sea

Fig. 3.28 Distribution of coastal bottom friction ( ρτb0 , unit: 1 × 10−4 m/s2 ) and its curl (∇ × unit: 1 × 10−7 m/s2 ) of Exp 1 (a, c) and Exp 2 (b, d) on day 30 (Wang et al. 2014)

(

τb ρ0

) ,

In the stable state, when the Rossby number is far less than 1, the vorticity equation of the vertical integral is: ) ( ) ( ) ( ) τb τs 1 f , Ψ +∇ × +∇ × + J χ, =0 J H ρ0 H ρ0 H H (

(3.9)

∫ 0 where f is Coriolis parameter; Ψ is stream function; χ = ρg0 −H zρdz; ρ0 = 1025 kg/m3 is the reference density; H is water depth; τb and τs are bottom friction and wind stress respectively. Decompose Eq. (3.9) along the isobath line and perpendicular to the isobath line, and on the f plane, we can get: ⏋ ) ⎡( ) H ∂ H −1 ∇ × τb ∂n ρ0 f ⏋ ( )−1 ⎡( ) H 1 ∂χ ∂H τss − ∇ × τs − + ρ0 f ∂n ρ0 f f ∂s

Un =

τbs − ρ0 f

(

(3.10)

where Un = − ∂Ψ , represents the transport perpendicular to the isobaths. In ∂s Eq. (3.10), the first term on the right is the Ekman transport caused by bottom friction, the second term is the effect of bottom Ekman pumping, the third term is surface Ekman transport, the fourth term is surface Ekman pumping, and the last term is Jebar effect. Under the effect of no wind on the sea surface, Eq. (3.10) becomes:

3.3 Upwelling of East Guangdong in South China Sea

τbs − Un = ρ0 f

(

∂H ∂n

)−1 ⎡(

H ρ0 f

135

⏋ ) 1 ∂χ ∇ × τb − f ∂s

(3.11)

Equation (3.11) shows that in the absence of wind, the transport across the isobathic line to shore is the result of the combined action of bottom Ekman transport, bottom Ekman pumping and Jebar. Using this formula and the numerical model, the contribution of Ekman transport, Ekman pumping and Jebar effect to the upwelling intensity of eastern Guangdong under different background flow intensities can be quantitatively discussed. Based on the diagnostic analysis of the model results, Fig. 3.29 reveals the contribution of bottom friction and curl of bottom friction to topographically-induced upwelling in eastern Guangdong. When the large-scale circulation is northeastward, in the Shanwei to Shantou area, Ekman pumping transports the entire water column offshore, reducing the strength of upwelling; while in Shanwei and Shantou, Ekman pumping transports the water column to shore, increasing the upwelling strength. This explains why we often observe that the upwelling is stronger in Shanwei and Shantou, but weaker in other areas.

Fig. 3.29 Contribution of bottom friction and curl of bottom friction to upwelling in the northern South China Sea Wang et al. (2014), The contour lines are isobaths

136

3 The Northern Shelf and Slope Currents of the South China Sea

3.4 The Pearl River Diluted Water Plume 3.4.1 Seasonal Characteristics and Interannual Variability of the Pearl River Diluted Water The Pearl River system is the second largest water system in my country. Every year, large amounts of fresh water, sediment, nutrients and other substances enter the shelf waters of the northern South China Sea, forming a diluted water plume. The structural variation of the diluted water plume is influenced by the complex dynamic conditions in the northern South China Sea, which is an important part of the dynamic framework of the northern South China Sea, and has a significant influence on the formation and variation of the nearshore circulation in the northern South China Sea. The average annual runoff of the Pearl River Basin is about 3.36 × 1011 m3 , ranking the second in China, second only to the 8.94 × 1011 m3 of the Yangtze River. The Pearl River Estuary basin consists of three tributaries: Xijiang River, Beijiang River and Dongjiang River, which empties into the South China Sea from the eight mouth gates of the Pearl River Delta (Humen, Jiaomen, Hongqili, Hengmen, Modaomen, Jiti Gate, Hutiao Gate and Yamen). Influenced by the seasonal and inter-annual variations of rainfall in the Pearl River system, the seasonal and inter-annual variations of runoff in the Pearl River system are very obvious. The runoff is mainly concentrated in the flood season, the runoff into the sea in flood season of Dongjiang River and Beijiang River accounts for more than 70% of the total annual runoff, while the runoff in flood season of Xijiang River accounts for more than 90% of the annual runoff (Fig. 3.30). The interannual variation of discharge also shows that the Dongjiang River, Beijiang River and the main stream of Xijiang River all have obvious years of high water, medium water and low water (Fig. 3.31).

Fig. 3.30 Monthly variation of average Pearl River discharge from 1959 to 2000 Ou (2005)

3.4 The Pearl River Diluted Water Plume

137

Fig. 3.31 Variation of annual mean discharge anomaly values at Boluo Station of Dongjiang River, Shijiao Station of Beijiang River and Gaoyao Station of Xijiang River Ou (2005)

In addition, under the influence of East Asian monsoon, northeast monsoon prevails in winter (dry season), which is conducive to the formation of southwest coastal current, while southwest monsoon prevails in summer (wet season), which is conducive to the formation of northeast coastal current. Under the influence of ENSO, the monsoon intensity and rainfall in the sea area also showed obvious interannual variation. The significant seasonal and inter-annual variations of the fresh water runoff of the Pearl River and the East Asian monsoon make the expansion and intensity of the plume of the Pearl River diluted water have obvious seasonal and inter-annual differences. On the one hand, the extension range and direction are different in the dry season and the wet season. In the winter dry season, the southwestward coastal current is consistent with the natural expansion of the Pearl River diluted water after entering the South China Sea, inshore coastal current and the diluted water plume reinforce each other, which accelerates the westward movement of the plume and hinders its expansion to the open seas. During the summer wet season, a large amount of the diluted water from the Pearl River Estuary was released, under the action of the Ekman offshore transport caused by the summer monsoon and the horizontal

138

3 The Northern Shelf and Slope Currents of the South China Sea

transport of the northeast coastal current, the diluted water floats in the near surface and expands to the southeast sea in a tongue-like manner, the salt line of 32 psu could reach to the open waters off the Shantou. In summer, the morphology of the diluted water plume is more complex because of the large freshwater runoff, the relatively weak and unstable monsoon. Taking the surface salinity 32 psu of historical hydrological observations as the edge of the diluted water, Ou et al. (2009) summarized the expansion modes of the Pearl River diluted water in the northern continental shelf of the South China Sea into the following four forms. (1) Seaward expansion type, in which the westward and eastward spreading is small, the expansion of diluted water is confined to a very narrow area along the western coast of Guangdong, and the distance across Hong Kong to the east coast of Guangdong is very short, the diluted water of the Pearl River Estuary is mainly concentrated outside the estuary and expands towards the sea. (2) West Guangdong extended type, and can be divided into two extreme and nonextreme. The extreme west Guangdong expansion type is shown in that the diluted water of the Pearl River Estuary, especially the low salt water from Lingdingyang, all spreads to the west of Guangdong, and the expansion distance to the sea is nearly 0. The diluted water of Lingdingyang does not reach the Dangan islands, that is, all expands to the west Guangdong coast. The most common type of expansion of western Guangdong is not extreme expansion type of western Guangdong. A small part of the expansion of diluted water bypasses Hong Kong and extends to the waters of Hong Kong Bay, while most of the expansion of diluted water extends to the sea and the coast of western Guangdong. The expansion range of diluted water varies with the time, ranging from the eastern end of Hainan Island to the vicinity of Shuidong Port. The diluted water front also changes accordingly, extending approximately parallel to the west of Guangdong coastline, or extending one or two curves along the west of Guangdong, the big curves generally appear in the nearshore waters of Yangjiang and Shuidong. (3) East Guangdong expansion type, mainly offshore expansion type. The most significant characteristic of the expansion pattern of the Pearl River diluted water along the eastern part of Guangdong is the offshore expansion of the diluted water, which is completely different from West Guangdong extended type. When the diluted water comes out of the Pearl River Estuary, it floats on the relatively salty shelf water and expands eastward, and basically continues to expand to the eastern shelf waters near the coastal area of Huizhou, instead of expands along the coast to Shantou, the coastal water from Huizhou to Shantou are controlled by high-salt shelf water. (4) Symmetric expansion type, that is, the expansion form to the west and east of Guangdong is approximately symmetric with the Pearl River estuary as the axis. In this case, the west and east of Guangdong are both coastal expansion, and the expansion range of diluted is generally limited to within 60 km near the east and west shore of Guangdong. For example, in June 1984, the diluted water extended far along both sides of the coast, along the east coast of Guangdong

3.4 The Pearl River Diluted Water Plume

139

to Shantou, and along the west of Guangdong to the west of Shuidong Port. The front line of this type of diluted water expansion is more complex and changeable compared to other types. On the other hand, summer diluted water in different months also has its own characteristics. From the expansion direction, the diluted water of Pearl River Estuary mostly expands to the west of Guangdong in June, and the diluted water expansion pattern is mainly the west of Guangdong type, its main axis can expand to the area from Zhanjiang Port to Qiongzhou Strait in the west, with 30–40n mile offshore. The expansion of diluted water in July is mainly the east of Guangdong type, the main axis of diluted water turns to the east, and it can extend to the sea area to the east of 117° E, and the offshore water can reach up to about 60n mile. However, the expansion direction of August diluted water is changeable, and all the four expansion forms of August diluted water exist. In terms of the expansion range (Table 3.2), the expansion range of diluted water in July is the widest, reaching 161 km from the Pearl River Estuary to the sea, 245 km to the east and 286 km to the west of Guangdong respectively, and the maximum expansion area in the continental shelf sea area is more than 70,000 km2 ; In August, the expansion range is relatively minimum, the expansion distance to the west coast of Guangdong is generally less than 100 km, and the total area of expansion is mostly 15,000–30,000 km2 . In addition, it can be clearly seen from Fig. 3.32 that the expansion distance and range of the diluted water of the Pearl River have interannual changes. The difference between the minimum and maximum diluted water expansion area is 2–3 times, and there is a negative correlation between the diluted water expansion area in June and August (Fig. 3.32). In terms of the factors affecting the expansion area of diluted water, comparing the expansion area of diluted water in the Pearl River Eestuary (Table 3.2) with the monthly average runoff of the Pearl River (Table 3.3), it can be found that the response of the expansion area of diluted water to the amount of runoff into the sea is relatively obvious, and it is also related to the amount of fresh water runoff in the previous time. After excluding the two extreme values in July 1978 and August 1983, which were closely related to the distribution pattern of early diluted water, the corresponding relationship between the runoff of the Pearl River into the sea in summer and the spread area of the diluted water on the shelf (Fig. 3.33) shows that there is a good positive correlation between the expansion area of the diluted water and the runoff of the Pearl River into the sea, with a correlation coefficient of 0.97. The larger the runoff of the Pearl River into the sea, the longer the duration of the large runoff, the larger the expansion range, and the larger the expansion area of the diluted water, and vice versa. × 104 km2 The interannual, seasonal and diurnal variations of monsoon are the main factors affecting the expansion direction and morphology of the Pearl River diluted water. By comparing the monthly summer average wind field characteristics of COADS with the expansion pattern of the Pearl River Estuary diluted water (Table 3.4) from 1978 to 1984, it can be found that there is a significant causal relationship between the expansion pattern of the diluted water and the wind field in the northern South

6

6

6

6

6

6

6

7

7

7

7

8

8

8

8

8

8

8

1978

1979

1980

1981

1982

1983

1984

1978

1979

1980

1981

1978

1979

1980

1981

1982

1983

1984

89

55

55

133

89

122

33

122

116

149

161

122

133

111

22

122

66

155

41

41

194

296

214

296

0

275

31

286

286

286

296

102

0

102

51

0

41

107

87

92

5

102

112

82

56

245

133

128

56

184

245

133

184

332

4517

11,858

9600

10,164

565

11,294

12,423

9035

6211

27,105

14,682

14,117

6211

20,329

27,105

14,682

20,329

36,704

565

565

10,164

12,988

15,811

27,105

0

31,622

3388

27,105

26,540

18,070

32,751

5082

0

2259

1,129

0

10,164

6776

6776

14,682

9035

12,423

5647

12,423

14,117

20,329

20,329

12,423

12,988

12,988

3388

13,552

6,776

14,682

15,246

19,199

26,540

37,834

25,411

50,822

18,070

53,080

23,716

74,539

61,551

44,610

51,951

38,399

30,493

30,493

28,234

51,386

Years Months Extended distance Extended distance Extended distance Expanded area of Expanded area of Expanded area of Total expanded to the sea (km) to western to Eastern western Eastern PRE (km2 ) area (km2 ) 2 2 Guangdong (km) Guangdong (km) Guangdong (km ) Guangdong (km )

Table 3.2 Eigenvalues of the Pearl River estuary diluted water expansion (Ou 2005)

140 3 The Northern Shelf and Slope Currents of the South China Sea

3.4 The Pearl River Diluted Water Plume

141

Fig. 3.32 Year-on-year changes in the expansion area of the Pearl River Estuary’s diluted water in June and August (Ou 2005)

Table 3.3 Monthly average runoff of the Pearl River from 1978 to 1984 (Ou 2005) (Unit: m3 /s) Years

May

June

July

Auguest

1978

21,150

23,190

11,604

10,990

1979

15,500

16,120

21,174

21,180

1980

15,459

10,920

14,389

16,820

1981

16,570

15,739

18,300

12,846

1982

16,960

17,550

9610

15,590

1983

16,550

23,520

9949

12,060

1984

14,050

17,360

12,405

10,497

China Sea, under the action of different wind directions, the expansion pattern of the diluted water presents different patterns. In summer, under the action of East and Southeast winds, a short-term wind-driven southwest flow was formed along the northern coast of the South China Sea, which interacted with and enhanced the plume of diluted water driven by the southwest buoyancy force, and accelerated the expansion of the diluted water from the Pearl River Estuary to the west of Guangdong. When the diluted water of the Pearl River Estuary is East Guangdong expansion type, the climate monthly mean wind fields of the northern South China Sea are all SSW and SW wind fields. When the diluted water expands seashore, the sea area is dominated by S wind. More importantly, the wind speed is low. The diluted water expands outward to the sea and forms bulge (similar to Bulge), and forms a narrow freshwater belt along the west coast of Guangdong.

142

3 The Northern Shelf and Slope Currents of the South China Sea

Fig. 3.33 Relationship between average runoff in different years and average expansion area of diluted water in the Pearl River Estuary in summer (Ou 2005)

When the expansion of the Pearl River diluted water is symmetrical, the northern part of the South China Sea is mostly SW–SSW wind. Zu et al. (2014) pointed out that the different responses of the coastal currents on the east and west sides of the Pearl River Estuary to the relaxation of the southwest monsoon in summer are the main reasons for the symmetrical expansion of the Pearl River diluted water„ when the southwest monsoon weakens, the northeast flow of the continental shelf east of the Pearl River Estuary will not close immediately, so that the diluted water will continue to expand eastward, and the northeast wind-induced coastal current of the continental shelf west of the Pearl River Estuary has been replaced by the buoyancy driven westward diluted water plume, thus forming a symmetric expansion type.

3.4.2 Rapid Response of the Pearl River Diluted Water and Its Front to Changes in Physical Driving Factors Such as Wind, Tide and Fresh Water Runoff Although the observational data reveal a certain relationship between the shape and expansion mode of the diluted water and the variation of freshwater runoff and monsoon, it is difficult to obtain the influence of physical driving factors such as wind, tide and freshwater runoff on the variation of the plume, salinity front and stratification of the diluted water in the Pearl River only through the observation data with very limited spatial and temporal resolution. The contribution of these physical drivers can be quantified by using numerical models and numerical experiments.

3.4 The Pearl River Diluted Water Plume

143

Table 3.4 Corcorresponding relation between diluted water expansion form and wind direction in the Pearl River Estuary (Ou 2005) Years

Months

Expanded form

Monthly mean prevailing wind direction

Wind speed (m/s)

1979

6

West Guangdong expansion type

E,ESE

3–7

1980

6

West Guangdong expansion type

E,SE

3–8

1981

6

West Guangdong expansion type

E

4–7

1982

6

West Guangdong expansion type

S

2–5

1983

6

Symmetrical expansion type S–SE

3–8

1984

6

Symmetrical expansion type S,SW

3––8

1978

7

East Guangdong expansion type

SW,SWW

4–8

1979

7

East Guangdong expansion type

SW

3–8

1980

7

Seaward expansion type

S,SSE

2–4

1981

7

East Guangdong expansion type

SSW,SSE

3–9

1978

8

West Guangdong expansion type

E

3–10

1979

8

East Guangdong expansion type

SSW,SW

3–8

1980

8

East Guangdong expansion type

SSW

3–7

1981

8

Symmetrical expansion type SW

1–3

1982

8

Symmetrical expansion type SW,SSW

3–7

1983

8

West Guangdong expansion type

S,SE

1–3

1984

8

Seaward expansion type

S

3–4

Wong et al. (2003a, 2003b), Ji et al. (2011a, 2011b), Zu and Gan (2009, 2015), Luo et al. (2012), Zu et al. (2014) apply POM, EFDC, ROMS and other different regional modes to reproduce the basic structure and shape of the diluted water and its salinity front (Fig. 3.34) of the Pearl River Estuary and its adjacent sea areas during the dry (dry period, winter monsoon) and wet (high water period, summer monsoon) seasons (Fig. 3.34), and the rapid response of fresh water to changes in physical driving factors (Fig. 3.35). Observation and simulation results show that the subsurface salinity fronts in the estuaries in winter and summer are basically distributed in the northeast-southwest direction. The fronts are located near the upper part of the estuary in winter and near the intersection of the lower part of the estuary and the open seas in summer (Fig. 3.34). The responses of diluted water to changes in physical

144

3 The Northern Shelf and Slope Currents of the South China Sea

driving factors (Table 3.5) in the sensitivity numerical experiments without considering wind (RT) or tide (WR) and the control experiments (both wind and tide WRT were considered) showed significant differences in different regions of the estuarine shelf system. The surface shape of diluted water on the continental shelf is mainly controlled by wind, and the expansion and mixing of diluted water on the continental shelf are modulated by wind-driven near-shore circulation. Tidal mixing controls the vertical structure and bottom morphology of diluted water in shallow areas near estuaries (Fig. 3.36). According to the analysis of mechanical energy budget, this is because the estuary/shelf system obtains energy from tide/wind through pressure gradient force/surface stress, and dissipates energy through the mixing of bottom friction/internal shear (Zu et al. 2014). As can be seen from Fig. 3.36, the surface shape of diluted water can quickly respond to wind and tide changes in a short time, showing a variety of forms such as westward expansion, eastward expansion, outward expansion, etc. The simulation results show that changes of diluted water expansion direction and shape also have a significant influence on the continental shelf wind-driven coastal circulation (Zu and Gan 2015). During the period of favorable upwelling wind, the diluted water moves offshore, while when the favorable upwelling wind relaxes, the diluted water shrinks to the shore, but continues to expand eastward.

3.4.3 Impact of Diluted Water Expansion of the Pearl River Estuary on the Northern South China Sea Coastal Current 3.4.3.1

Constraints of Estuary Shelf Topography Against Diluted Water Plumes

The spread pattern of diluted water is not only affected by tide, wind and other factors, but also restricted by continental shelf topography and coastal currents. Shu et al. (2011) used the reanalysis data of voyage observations to study the restraining effect of the coastal currents under the variable wind field and the continental shelf topography on the eastward expansion of the Pearl River diluted water in summer. Under the action of short-term changes in the wind field, when the wind field (southwest wind) that is favorable to upwelling changes to the wind field that is unfavorable to upwelling, the direction of the coastal current is still eastward due to the short action time. However, due to the dynamic effect of diluted water, the flow field near the Pearl River Estuary is easily converted into a westward flow (Fig. 3.37). Thus, isolated low-salt areas often appear in the northern part of the South China Sea in summer (Fig. 3.38). From the Pearl River Estuary to the east, the position of the lowest salinity on the same longitude is defined as the position of the main axis of diluted water, so that the cross-sectional distribution of salinity on the main axis of diluted water can be

3.4 The Pearl River Diluted Water Plume

145

Fig. 3.34 Surface and bottom layer salinity distribution (unit: psu) in the Pearl River Estuary and its adjacent sea areas during 17–24 January 2000 (a, b) in winter and 17 to 27 July 1999 (c, d) in summer (Wong et al. 2003a; Ji et al. 2011a)

obtained (Fig. 3.39). It can be seen that west of 116° E, the influence depth of diluted water cap on its main axis is about 10 m in the Pearl River Estuary, but at 116° E, the halocline suddenly drops, and the influence depth of the Pearl River diluted water also deeps to 15–20 m. It can be explained by the spatial distribution of potential vorticity. Due to the widening of the continental shelf topography, the coastal current is offshore at 116° E, and the diluted water advection flows from the positive vorticity zone west of 116° E to the negative vorticity zone east of 116° E (Fig. 3.39). Positive vorticity corresponds to ascending motion, while negative vorticity corresponds to descending motion, so the influence depth of diluted water will deepen east of 116° E.

146

3 The Northern Shelf and Slope Currents of the South China Sea

(a)

(b)

(c)

(d)

Fig. 3.35 The observed (a and b, log (mg/m3 ) Logarithm of chlorophyll concentration inversion by SeaWiFS) and simulated (c and d, sea surface salinity distribution) changes in the distribution of diluted water during upwelling favorable wind prevailing period (August 10, 2000) and its decline period (August 19, 2000) (Zu and Gan 2015) Table 3.5 Comparison of different wind, tide and fresh water runoff intensities (Zu et al. 2014) The number of days to July 1, 2000

Freshwater runoff (m3 /s)

Wind stress (N/m2 )

The ratio of tide Physical driving amplitude to spring characteristics tide amplitude (%)

22

11 080

~0.001

~34

Light/no wind, light tide

26

13 176

~0.07

~45

Moderate wind in favor of upwelling, moderate tide

30

9 952

~0.09

~97

Wind favorable to upwelling, spring tide

37

9 602

~−0.003

~30

Relaxed upwelling favorable wind/weak down flow favorable wind, neap tide

Surface layer Bottom layer

3.4 The Pearl River Diluted Water Plume

147

Surface layer

Bottom layer

WRT

a

b WR

WR

c RT

d

RT

e

f

Fig. 3.36 The 32 psu contour distribution of the average surface and bottom salinity of WRT, WR, and RT on the 22nd, 26th, 30th, and 37th days of different sensitivity tests (Zu et al. 2014) To characterize the form of diluted water under different physical driving environments

3.4.3.2

Modulation of the Pearl River Diluted Water Plume on the Coastal Current in Summer

The diluted water of the Pearl River is superimposed on the coastal salty sea water, on the one hand, the stratification of sea water is strengthened, and then the effect efficiency of sea surface wind stress on the near surface water is enhanced (Lentz 2001); On the other hand, light fresh water causes changes in sea level, and a pressure gradient perpendicular to the shore, thereby regulating the nearshore coastal current (Chao 1988b; Rennie et al. 1999). Shu et al. (2014) used the observation data of three subsurface buoy (S205, S206, S305, see Fig. 3.40) in 2008 to analyze the modulation of the Pearl River diluted water to the coastal velocity in summer. The observation results show that the surface velocity of the nearest offshore subsurface buoy S205 is larger than that of S206 and

148

3 The Northern Shelf and Slope Currents of the South China Sea

Fig. 3.37 Reanalysis of the sea surface flow field based on the ensemble Kalman smooth assimilation method (Shu et al. 2011)

Fig. 3.38 Reanalysis of sea surface salinity field based on ensemble Kalman smoothing assimilation method (Shu et al. 2011)

S305 in July 2008 (Fig. 3.40), and it can be inferred that the station S205 is closer to the main axis of the coastal current in eastern Guangdong than that of S206 (Shu et al. 2011). By analyzing the time-average velocity shears, it is found that the velocity shears observed by three subsurface buoys which are not far from each other are obviously different. The vertical shear of the velocity at S305 station, which is far offshore, is small, while the vertical shear at S205 station is the largest (Fig. 3.41). Looking back at the runoff of the Pearl River in the summer of 2008, it is found that in the late June, the extreme rainfall in the Pearl River Basin led to the abnormally increased runoff of the Pearl River, which reached a peak of 68,000 m3 /s. Therefore, one possible reason for the difference in the vertical shear of nearshore velocity is the dynamic effect of the Pearl River diluted water. Influenced by the Pearl River

3.4 The Pearl River Diluted Water Plume

-20

24oN

33.5

33.5

23oN Latitude

Depth /m

31 .5

30

33 .5

31

-15

29.5 29. 24 27 2828 28.529 28.5 29.5 .5 31 9.5 3031 3 30.5 30 5 30 2 30 .530 31 3130. .5 5 30.5 1.5 30.5 30. 0 31 31.5 32.5 32 31.5 5 30.5 30.5 331 .5 31.5 31 32 32 1 31 33 3 .5 32 31 33 32 .5 31.5 312 32 332 32 .5 .52.5 3 32 .5 32 2 3 .5 32.5 32.5 32.5 32 .5 33 32 33 33 33 33 .5 .5 32 33

-525 272.59 2.5 -10 3

149

-25 -30

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-35

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salinity: psu -40 -2

21oN

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-50 114

115

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119oE

Fig. 3.39 Temporal mean distribution of salinity (a) and relative vorticity (b) along the main axis of the Pearl River diluted water (Shu et al. 2011). b The black line represents the main axis of diluted water, while the white line represents the axis of coastal current

diluted water, the surface salinity of S205 station is much lower than that of S206 and S305 stations (Fig. 3.42a), resulting in the minimum surface density of S205 station (Fig. 3.42b). The less dense diluted water overlay the denser seawater, strengthening the surface stratification and weakening the vertical momentum and heat exchange. Therefore, at the S205 station with lower surface salinity, the stable stratification strengthens the local wind’s dynamic forcing on the upper layer, which is conducive to the formation of large vertical shear. In addition, the eastward expansion of the Pearl River diluted water raises the sea surface height. In the direction perpendicular to shore, the surface current is strengthened on the nearshore side and weakened on the offshore side due to the effect of geostrophic equilibrium. In conclusion, because the Pearl River diluted water strengthens the surface stratification and changes the upper pressure gradient, the vertical shear of velocity of S205 station near the shore is the strongest. Two numerical sensitivity experiments further confirmed that the Pearl River diluted water affects the coastal current. Exp 1 is a control test, and the model adopts the climatic summer runoff of the Pearl River; while in Exp 2, the model does not have runoff forcing. By comparing the coastal velocity difference between Exp 1 and Exp 2, it is found that the surface coastal current strengthens on the shore side of the diluted water main axis and weakens on the offshore side (Fig. 3.43b). Surface shoreward currents strengthen on the shore side of the diluted water main axis and weaken on the offshore side (Fig. 3.43c). Combined with the direction of the flow field in Fig. 3.43a, the surface velocity increases on the shore side of the diluted water main axis and decreases on the offshore side. Gan et al. (2009a) established a circulation simulation system of the northern shelf of the South China Sea by using ROMS model, and discussed in detail the interaction process between the Pearl River diluted water and the upwelling of the northern shelf of the South China Sea in combination with numerical experimentation without considering freshwater runoff. Under the horizontal transport of monsoon and continental shelf coastal current, the diluted water expands eastward, and is

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3 The Northern Shelf and Slope Currents of the South China Sea

Fig. 3.40 Average upper 10 m velocity (a), near-bottom velocity (b) and vertical average velocity (c) observed by three subsurface buoys from July 1–13 (Shu et al. 2014)

affected by surface Ekman drift in the process of movement, and its width gradually increases. The difference in flow velocity between freshwater runoff and no freshwater runoff (Fig. 3.44c, d) shows that, the presence of diluted water greatly improves the offshore transportation of the surface layer and at the same time enhances the inshore transportation of the bottom layer, this is because of the freshwater buoyancy

3.5 Summary and Outlook

151

Fig. 3.41 Time-averaged velocity (a) and direction (true north is 0°) (b) changes with depth (Shu et al. 2014)

input enhances the upper water stratification and efficiency of work done by wind stress, so as to enhance the surface Ekman transport offshore. However, the effect of freshwater buoyancy is limited to the water layer shallower than 20 m, so it has little effect on the upwelling in the shelf area where the water depth is greater than 20 m.

3.5 Summary and Outlook This chapter reviews the characteristics and mechanisms of the South China Sea Warm Current, the East Guangdong Upwelling and the Pearl River Diluted Plume. In addition to the earlier discussions on the mechanism of the SCS Warm Current, this chapter focuses on analyzing a potential mechanism for the combined effect of the topography and baroclinic pressure in the northern South China Sea to generate the SCS Warm Current, it is believed that the combined effect drives the transport

152 Fig. 3.42 Profiles of temperature and salinity (a) and density (b) observed by three subsurface buoys (Shu et al. 2014)

3 The Northern Shelf and Slope Currents of the South China Sea

0

T & S profiles 24 27 30 33

0

-10

-10

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Density profiles 36

a

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-30

-30

-40

-40

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-50

-60

-60

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S205 S206 S305

b

S205 S206 S305

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15

20

25

Fig. 3.43 The surface salinity and flow velocity simulated by the control test (a), the difference between the coastal velocity (b) and the velocity perpendicular to the shore (c) between the control test and the non-Pearl River runoff test (Shu et al. 2014)

of seawater off the continental shelf to the continental shelf, providing water replenishment during the progress of the South China Sea warm current; This chapter also studies the effect of wind stress curl on the South China Sea Warm Current on the east side of Hainan Island, and believes that it provides the driving force for the source of the South China Sea Warm Current. Early studies believed that the upwelling in eastern Guangdong was a typical wind-induced upwelling. In this chapter, using methods such as observation and numerical simulation, it is believed that the terraininduced upwelling, that is, the upwelling induced by the large-scale shelf circulation

3.5 Summary and Outlook

153

Fig. 3.44 Surface velocity (a), surface salinity (b), the difference of surface flow in the direction along the shelf (c) and the direction across the shelf (d) on the 30th day with and without fresh water runoff (Gan et al. 2009a)

in the changing terrain area through the bottom friction effect, It is another important mechanism for the upwelling of eastern Guangdong. The terrain-induced upwelling has a comparable strength to the local wind-induced upwelling, which controls the spatial distribution of the upwelling in eastern Guangdong and affects the interannual variation of the upwelling to a certain extent. Influenced by the monsoon, freshwater runoff, and tides, the Pearl River diluted plume exhibits complex three-dimensional structure and movement characteristics, and interacts with the shelf circulation to regulate the intensity and spatial structure of the upwelling in eastern Guangdong in summer. At present, there is still a lack of systematic research on the transport of matter and energy between the continental shelf and the continental slope, and between the deep-water basin and the continental shelf. Although the previous studies on the SCS warm current are many, there is no long-term and large-scale observation to confirm it. Is the South China Sea Warm Current a relatively stable flow that persists? This issue is still controversial. The warm SCS in winter, the upwelling in summer, and the Pearl River diluted water plume existing on the continental slope can all form strong density fronts. The development of these fronts and the atmospheric forcing can lead to sub-mesoscale dynamic processes, which in turn affect the NSCS Multiscale interactions and their energy cascades have an important impact, but there is still a lack of targeted research in this area.

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Chapter 4

Middle and Deep Waters Mass and Circulation in the South China Sea

4.1 Intermediate Waters and Circulation in the South China Sea The South China Sea is the largest semi-enclosed marginal sea in the Western Pacific. As a relatively isolated sea area, it has its own independent water mass system. According to the typical characteristics of temperature, salinity, density, etc., using TS diagrams, statistical indicators and other analysis methods, the South China Sea water mass can be divided into four typical water masses in the vertical direction: ➀ the surface waters (SW) of the South China Sea are located at 0–50 m, which potential density is less than 23.5 kg/m3 , and it has the characteristics of high temperature and low salt; ➁ the subsurface waters (SSW) of the South China Sea are located at 50– 300 m and have a potential density of 23.5–25.5 kg/m3 . It is a maximum salinity layer with a core salinity of 34.54–34.65 psu; ➂ the intermediate waters (IW) of the South China Sea is located at 350–1000 m, and its potential density is 26.5–27.0 kg/m3 . It is a minimum salinity layer with a core salinity of 34.40–34.50 psu; ➃ the deep waters (DW) of the South China Sea, which are below 1000 m and have a potential density greater than 27.0 kg/m3 , are a water mass with low temperature and high salinity (Wang and Chen 1997; Qu et al. 2000; Xie 2004; Tian et al. 2005; Liu et al. 2008). The subsurface water of the South China Sea is generated by the denaturation of the subsurface waterS of the North Pacific Ocean after entering the South China Sea. The typical feature is high salinity. The salinity value of the core layer at the entrance of the Luzon Strait is close to 35.0 psu. After intruding into the South China Sea, it gradually decreases to 34.50 psu (Li and Su 2000), the spatial distribution shows the characteristics of shallowness in the north and deepness in the south. Li et al. (1998) used CTD (conductivity-temperature-depth system) data from two surveys in the northern part of the South China Sea in 1992 and 1994 to analyze the temperature and salinity properties of the Luzon Strait and the shallow waters of 400 m in the northern part of the South China Sea. Basically, it can be divided into two water masses: the subsurface water of the South China Sea and the subsurface water of © Science Press and Springer Nature Singapore Pte Ltd. 2022 D. Wang, Ocean Circulation and Air-Sea Interaction in the South China Sea, Springer Oceanography, https://doi.org/10.1007/978-981-19-6262-2_4

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the Kuroshio. Wang et al. (2001) analyzed the CTD data of the South China Sea Monsoon experiment from May to August 1998 and found that the hinterland of the South China Sea was basically controlled by the typical South China Sea water. However, in the northeastern part of the South China Sea, especially near the Luzon Strait, the subsurface water is obviously affected by the water of the Western Pacific, which shows that different water systems are mixed with each other and the mixing is insufficient. Li et al. (2002) analyzed the temperature and salt distribution near the Luzon Strait and the Mindoro Waterway based on the data of the two crusion in the winter and summer of 1998 and combined with the measured data in July and December 1997, and classified several main water masses in the South China Sea. It is concluded that Kuroshio subsurface water intrusion occurs only in summer. Liu et al. (2001) also used the CTD data of two intensive observations in the South China Sea monsoon experiment in 1998 to further prove that the two major water masses systems in the South China Sea are the South China Sea water mass and the outer mass, and summer and winter are different. The difference lies in the Kuroshio surface and subsurface water could not be observed in winter, which is consistent with the conclusion of Li et al. (2002). Tian and Wei (2005) used the data obtained from the observation in the Pacific Ocean near the Luzon Strait and the South China Sea in 2002 to analyze water mass, revealing that the Kuroshio subsurface water exists in the northeastern part of the South China Sea in summer, and their distribution was more significant than that in the South China Sea subsurface waters). The thickness of the South China Sea intermediate waters is about 650 m, and its typical feature is low salinity, with the lowest salinity near the Luzon Strait reaching 34.40 psu (Li and Su 2000). Intermediate water is distributed at 350–1000 m, and the core layer is 450–550 m, however, the intermediate water of the North Pacific entering the South China Sea is the most typical at 500–800 m (Tian and Wei 2005). Whether it is winter or summer, South China Sea intermediate water is almost entrenched in the entire basin. The temperature range is 5.5–11.8 °C in summer, which is slightly higher than 5.27–10.37 °C in winter; there is no obvious difference in salinity in summer and winter, and the range is 34.39–34.47 psu (Liu 2001). Below 200 m, except for the Luzon Strait, the South China Sea Basin is almost closed. Regarding intermediate water exchange between the South China Sea and the Pacific, Wyrtki noticed in his work in 1961 that the currents in the Luzon Strait turned around at 300 and 400 m. From this it is speculated that the intermediate water exchange is likely to be the opposite of the upper ocean. Nitani (1972) pointed out that the middle water of the South China Sea will flow out along the southwest coast of Taiwan to the Northwest Pacific, and believed that this is the reason for the relatively high minimum salinity of the intermediate water of the Kuroshio in eastern Taiwan. Chu (1972) discovered that the intermediate water of the South China Sea flows out to the Pacific through the Luzon Strait. This view is confirmed many times by subsequent chemical and hydrological observations. Gong et al. (1992) analyzed the chemical and hydrological properties of the South Sea and the Northwest Pacific Philippine sea, and pointed out the similarities and differences in the properties of the seawater on both sides of the Luzon Strait at a shallow depth of 1500 m: Corresponding to the NPTW (north Pacific tropical waters) with high temperature

4.1 Intermediate Waters and Circulation in the South China Sea

161

and high salinity in the North Pacific and NPIW (north Pacific intermediate waters) with low temperature and low salinity, the South China Sea also has high salt water and low salt water. The temperature of the 100–600 m layer of the South China Sea is lower than that of the West Philippine Sea. It is rich in nutrients but low in dissolved oxygen at the same temperature depth, while the intermediate water below is just the opposite. Chen and Huang (1996) found that by using chemical properties as tracers, at the middle depth, the South Sea water flows out. There is a long-term front at a depth of 350–1350 m near 122° E. The east side of the front is the water of the Northwest Pacific. On the side is a mixture of South Sea water and Pacific water. The intermediate water of the South China Sea that flows eastward through the Luzon Strait is blocked by the Kuroshio and merges into the Kuroshio, which changes the composition of the intermediate water on the shore of the Kuroshio. The intermediate water of the South China Sea, centered on the 500 m layer, which is rich in nutrients, is covered by the Kuroshio. It can flow into the Okinawa Trough and rise to become the main source of nutrients in the East China Sea (Chen and Wang 1998; Chen and Wang 1999; Chen 2005). The intermediate water of the South China Sea can continue to follow the Kuroshio and flow eastward to about 140° E in southern Japan, where Oyashio and Kuroshio converge to form the middle water of the North Pacific (Chen 2005). Chen et al. (2001) used the box model of conservation of mass and found that at 350–1350 m in the Luzon Strait, the South Sea water flows out to the Pacific regardless of whether it is the rainy or dry season. The dry season discharge (2 Sv) is slightly larger than the rainy season (1.8 Sv). The dissolved oxygen distribution chart of Qu (2002) also shows that water at a depth of 700–1500 m flows out of the South China Sea. Tian et al. (2006) used a large depth LADCP (lowered acoustic Doppler current profiler) in the Luzon Strait for the first time in the fall of 2005 to obtain direct observational flow velocity in the middle and deep layers. The flux results of the quasi-steady flow showed that there is a 5 Sv net flux of South Sea water flowing out in 500–1500 m. The observations in the summer of 2007 also showed a net flux out of the South China Sea, but the flux value was reduced to 2.5 Sv (Yang 2008). In addition, model research has also obtained similar results (Chao et al. 1996). Yuan (2002) used the high-resolution MOM model to study the relationship between the water exchange in the Luzon Strait and the circulation of the South China Sea, and believed that the outflow of the intermediate waters from the South China Sea is related to the anticyclonic circulation in the middle of the South China Sea basin, and it is related to the mixing of cross-density surfaces in the South China Sea. Xie (2009) used the intensified observation data of hydrology and currents in the Luzon Strait in 2005 and 2008, and part of the observation data from March to April 2009, and further research was made on the basis of Tian et al. (2006) research. It was found that there is an anticyclonic mesoscale eddy in the middle layer of the Luzon Strait (26.8–27.3 kg/m3 , 500–900 m). They believe that the existence of the eddy has a direct impact on the efficiency of the exchange of water of the Northwest Pacific and South China Seas, and proposed another possible path for the outflow of SCSIW (South China Sea intermediate water): it turned south in a mesoscale eddy in the

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northern part of the Luzon Strait, and then turned westward in the southern part of the Strait and flowed back to the South China Sea. Contrary to the “outflow theory” of SCSIW, some scholars also hold the “inflow theory” of SCSIW, and believe that the North Pacific Intermediate Water (NPIW) has also invaded the South China Sea. Qu (2000) analyzed that both NPIW and the North Pacific Tropical Water (NPTW) invaded the South China Sea, but NPIW leaks into the South China Sea only in spring, when the intrusion of NPTW is weakes; You et al. (2005) found through hydrological data and model analysis that the South China Sea is the cul-de-sac for the subtropical NPIW, which means that the NPIW still has strong invasion to the South China Sea in the sense of annual average (estimated at 1.1 Sv ± 0.2 Sv), they believe that the NPIW that invades the South China Sea is stronger in winter and spring, while outflow is weaker in summer and autumn. Liu et al. (2008) believed that NPIW has invaded the South China Sea, and pointed out that it is relatively strong in spring and summer, and NPIW hardly invades the South China Sea in winter. The above studies have given a qualitative understanding of the overall situation and quantitative results of the net flux of the intermediate water exchange between the South China Sea and the Pacific through the Luzon Strait, but the research on the specific flow field patterns of the intermediate water exchange is still lacking. Whether SCSIW flows into the North Pacific or NPIW invades the South China Sea is still controversial, and there is no final conclusion, and further research on the specific exchange patterns of the two is lacking.

4.1.1 Annual Average and Seasonal Variation Characteristics of the Intermediate Water in the South China Sea The minimum salinity layer with a potential density of 26.5–27.0 kg/m3 is defined as the North Pacific Intermediate Water. The distribution of the elements (temperature, salinity, density, and depth) corresponding to the minimum salinity layer is used to discuss the distribution characteristics of NPIW in the South China Sea in the sense of annual average climate. Furthermore, the seasonal variation of the NPIW intrusion into the South China Sea is discussed through the distribution of the minimum salinity layer of the seasonal mean salinity, and the invasion mechanism is preliminarily discussed.

4.1.1.1

Climatic Distribution Characteristics of Intermediate Water Mass

The 34.42 psu iso-salinity line is used to discuss the distribution of NPIW in the South China Sea. From the salinity, temperature, potential density and depth distribution of the climatic annual average salinity minimum layer (Fig. 4.1), it can be seen that

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Fig. 4.1 The salinity, temperature, geopotential density, and depth of the climatic annual average salinity minimum layer Liu et al. (2008). Color filling means that the water depth is less than 500 m

in the mean climate, the distribution of NPIW in the South China Sea is limited to a small area near the Luzon Strait. The potential density in the South China Sea is about 26.73 kg/m3 and the depth is 480–500 m. The salt on the east side of the Luzon Strait is significantly lower than the salinity inside the South China Sea, at a depth of about 600 m, and the temperature is also significantly lower than the temperature inside the South China Sea, at 7.6–7.8 °C. In the sense of climatic annual average, the intrusion range of NPIW in the South China Sea is very small, which is related to the weak southward movement of the South China Sea meridional overturning circulation (Fig. 4.2) in the range of about 500 m.

4.1.1.2

Seasonal Characteristics of the Intermediate Water

In the following, we will trace the distribution of NPIW in the South China Sea and its seasonal changes from the salinity distribution of the minimum salinity layer in each

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Fig. 4.2 The annual mean meridional overturning circulation streamfunction (Sv) in the South China Sea Liu et al. (2008)

season, and discuss its change mechanism from the perspective of the meridional overturning circulation. From the salinity distribution of the seasonal average minimum salinity layer (Fig. 4.3), it can be seen that the salinity gradient in the Luzon Strait in each season is larger, which indicates that the properties of the water mass in the strait is quite different. The South Sea and North Pacific waters converge here, and strong mixing occurs, resulting in a larger salinity gradient in the strait. In the process of invading the South China Sea, NPIW will mix with the relatively high-salt water in the South China Sea, which will increase the salinity of the invading water. Here, the 34.42 psu salinity contour is used as the dividing line between the NPIW invading water and the South China Sea water. In spring, water mass with salinity lower than 34.40 psu appeared in the seas southeast of Hainan Island, indicating a certain degree of NPIW invasion in spring. It can be seen from Fig. 4.4 that in spring, the meridional overturning circulation moves southward at the depth of 500 m, which is conducive to the intrusion of North Pacific intermediate water; in summer, the 34.42 psu salinity contour is basically withdrawn eastward to the Luzon Strait nearby, the salinity distribution in the South China Sea is relatively uniform, with salinity values ranging from 34.42 to 34.44 psu; in autumn, the 34.42 psu salinity contour continues to withdraw eastward, and water with salinity higher than 34.45 psu appear in a large area in the South China

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Sea. There are also 34.50 psu high salinity areas near Kalimantan and Palawan; In winter, except for a small area in southwestern Taiwan, the salinity of the intermediate water of the entire South China Sea is basically larger than 34.44 psu, reaching the highest value in four seasons. This is a strong evidence that NPIW has not invaded the South China Sea. In winter, NPIW almost did not invade the South China Sea and the relatively strong intrusion in spring and summer may be related to the opposite direction of the two water masses NPTW and NPIW mentioned in previous studies. In addition, we can get a partial explanation from the seasonally averaged meridional overturning circulation structure in the South China Sea. From the seasonally averaged South China Sea meridional overturning circulation structure (Fig. 4.4), it can be seen that in winter, the northward movement occurs at the 300– 700 m, which prevents the intrusion of the intermdiate water in the North Pacific. In the spring and summer, the depth is south. The movement is conducive to the invasion of NPIW. Of course, the invasion of NPIW may also be affected by other factors.

Fig. 4.3 Seasonal variation of salinity distribution in the minimum salinity layer (unit: psu) (Liu et al. 2008). Color filling means that the water depth is less than 500 m

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Fig. 4.4 Distribution of seasonal meridional overturning streamfunction (Sv) in the South China Sea (Liu et al. 2008)

4.1.2 Characteristics of Changes in South China Sea Intermediate Water on a Long-Time Scale 4.1.2.1

Interannual Variation of the Intermediate Water

From the annual mean T-S diagram in Fig. 4.5, Liu (2006) found that there is a significant differentiation in the T-S diagram, which indicates that salinity has changed significantly in these years. Compared with 1966, the salinity of each level of 600– 1500 m increased in 1968. Compared with 1975, the salinity in 1979 was higher from 500 to 1500 m, and the salinity in 1975 was lower than in 1966. From 1985 to 1999, salinity also changed significantly. In these years, the lowest salinity values of 500–1500 m appeared in 1986, and the highest salinity value appeared in 1999. It can be seen from Fig. 4.5 that the salinity of the 500 m layer in 1986 was 34.40–34.41 psu, which is equivalent to the minimum salinity of the middle water in the sense of climate average. The salinity decreased from 1985 to 1986 and increased from 1986 to 1988. The salinity was in a decreasing stage from 1988 to 1990. From 1990 to 1999, the salinity at all levels continued to increase (except in 1998, which was A special year).

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Fig. 4.5 The temperature and salinity curve of the South China Sea west of 118° E and south of 18° N from 1966 to 1999 by deep-water observation stations Liu (2006). The figure shows the average temperature and salt curve of 500–1500 m, (interval of 100 m)

The change of the average temperature is much more complicated than the change of the average salinity, there are large fluctuations, and the characteristics of interannual changes are more obvious. According to the temperature time series of the 500 m layer, the interannual variation is quite obvious. The temperature rose from 1966 to 1968, and then fell from 1968 to 1969. Then the temperature rose again from 1969 to 1975. The temperature dropped from 1975 to 1981 and the average temperature in 1981 was the lowest. The temperature rose again from 1981 to 1986. The temperature fell from 1986 to 1987. The temperature rose from 1987 to 1989. The temperature fell again from 1989 to 1991. The temperature rose from 1991 to 1993 and then continued until 1998 it showed a downward trend, and the temperature rose again from 1998 to 1999. It can be seen that the evolution of the average temperature of this layer over time has obvious characteristics of interannual variation, and the temperature fluctuation range is large, indicating that this layer may have a close relationship with the upper ocean dynamic process. The evolution characteristics of the average temperature of 600, 800, and 1000 m over time are similar, and similar to the 500 m, with obvious interannual variation characteristics. Only in the 1000 m, the temperature fluctuation range has been significantly reduced since the 1980s, but from the long-term trend of these layers, there are obvious warming processes. Since

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1985, the average temperature of the 1200 m layer still fluctuates to a certain extent, but the amplitude is small and there is no obvious long-term change characteristic. The average temperature change of the 1500 m is quite different from the temperature changes of the above layers. The temperature continued to decrease from 1975 to 1987, and there was a heating process from 1987 to 1989, and then the temperature mainly showed a downward trend until 1999. The long-term change trend of the average temperature of this layer is relatively obvious.

4.1.2.2

Interdecadal Changes of the Intermediate Water

Liu (2006) pointed out that based on historical observation data from the deepwater station of the South China Sea Institute of Oceanology, Chinese Academy of Sciences, and WOD01 data in the sea area south of 18° N, the average salinity curve of the four years from the 1960s to the 1990s was significantly different (Fig. 4.6), indicating that there are obvious changes in salinity in these four years. The average salinity of each layer below the depth of 500 m continued to decline from the 1960s to the 1980s, but the average salinity in the 1990s was significantly higher than the average salinity of the previous three years, and the average salinity in the 90 s increased by more than 0.05 psu compared with the average salinity in the 80 s. Zhao et al. (2014a, b) used historical observation data from the deep-water station of the South China Sea Institute of Oceanology, Chinese Academy of Sciences and

Fig. 4.6 Interdecadal mean salinity curve in the sea south of 18° N Liu (2006)

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Fig. 4.7 Interdecadal variation of the whole layer average of intermediate water salinity at the 18° N section Zhao et al. (2014a, b)

WOD2009 data to point out that the salinity of the intermediate water at the 18° N section of the South China Sea also has significant interdecadal changes (Fig. 4.7). From 1965 to 2012, the average salinity of the South China Sea intermediate water experienced an increase from 1965 to 1977 and 1979 to 1990, and then decreased from 1991 to 2012, with an interdecadal oscillation amplitude of about 0.01 psu during the entire time period. In the 1960s, the average salinity of the middle water was about 34.432 psu, while in the 1980s, the average salinity of the middle water reached the highest in the valid data interval, with an average value of about 34.440 psu. From the 1960s to the 1980s, the salinity of the middle water showed an increasing trend. Comparing the results in Fig. 4.6, it can be seen that the interdecadal variation of the 18° N section is opposite to that in the waters south of 18° N. From the 1960s to the 1990s, the salinity of the intermediate water at the 18° N section first increased and then decreased, while the sea area south of 18° N first decreased and then increased. It may be due to different data and data processing methods, or it may be affected by the invasion of the Kuroshio, leading to the difference in results as described above. It can be seen from Fig. 4.8 that the difference in average temperature between the 1960s and the 1990s is much smaller than the difference in salinity, especially the average temperature difference between the 80s and the 90s is very small. Between 500 and 1200 m, the average temperature in the 1960s was significantly lower than the average temperature in the other three years. At depths above 800 m, the average temperature of the four years showed an increasing trend with time.

4.1.3 The Current Deflection Around Dongsha Islands When analyzing the observation and simulation data near the Dongsha Islands, Wang et al. (2013) found that the inter-middle level flows field near the Dongsha Islands (near 500 m) in the autumn has a clear phenomenon of flowing into the deep sea

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Fig. 4.8 The Interdecadal average temperature curve in the sea south of 18° N Liu (2006)

across the isobath. This section will focus on this phenomenon and introduce the characteristics and causes of the separation flow from observation to simulation. The separation flow mentioned in this section refers specifically to the phenomenon that the intermediate seawater near the Dongsha Islands flows across the isobath to the deep sea.

4.1.3.1

Observational Evidence

Figure 4.9 shows the pressure distribution at 300 and 500 m observation stations. In each observed section, the pressure gradually increases from shallow water to deep water, and there is a high-pressure zone along the outer edge of the land slope. The arrow in Fig. 4.9 is the calculated geostrophic current. It can be found that the geostrophic current flows from the southwest to the northeast on the land slopes of 300 and 500 m. The following mainly introduces the results of the ship-mounted ADCP data (acoustic Doppler current profilers, ADCP) after tide filtration (Fig. 4.10). The data in 2004 basically covered the Dongsha Islands. It can be seen that to the west of the Dongsha Islands (west of 116° E), the flow velocity is basically parallel to the isobath. In the area deeper than 2000 m, it appears as the movement of sea water climbing, but on the land slope, it mainly appears as the flow along the isobath. The section on the south side of the Dongsha Islands is characterized by a clear flow deflect from the isobath and veer to the deep sea. On the section east of the

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Fig. 4.9 The horizontal distribution of the pressure (Wang et al., 2013): a 300 m and b 500 m. The vectors are the geostrophic velocity calculated from the adjacent two points. The pressure is calculated from the in situ CTD data acquired from SCS open cruise between 5 and 23 September in 2005 and the corresponding absolute dynamic topography (ADT) data (T/P)

Dongsha Islands, there is a clear flow to the deep sea. It can be inferred from this that in the area on the southeast side of the Dongsha Islands, the velocity distribution is dominated by the flow deflect from the isobath to the deep sea. The observation results in 2008 are very similar to the observation results in 2004. The continental slope area on the west side of Dongsha Island is also dominated by flow along the isobath, while on the southeast side of Dongsha Island, there is a very significant flow deflect from the isobath to the deep sea. In 2010, there were only observation data along a section of 20° N, but from the velocity distribution of the section, it can be seen that in the western section of the section (basically bounded by 117° E), the velocity is basically along the isobath. However, in the eastern section, there is a clear flow deflect from the isobat. The above observations were all in early September, and the observation results are relatively consistent. Therefore, the flow characteristics of the inter-middle level (about 500 m) of the northern slope of the South China Sea in the early autumn period can be summarized as: the seawater on the slope west of

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Fig. 4.10 Snapshot of the currents at 471.5 m around Dongsha Island, superimposed with the 300, 500, 1000, and 2000 m isobaths, the triangle marks Dongsha Islands (Wang et al. 2013). The shipmounted ADCP current were obtained between a 5 and 23 September in 2004, b 11 August and 2 September in 2008, and c 5 and 25 September in 2010. The left columns are fitted results and the right columns are the raw results

the Dongsha Islands basically flows to the northeast along the isobath. When it flows to the south side of the Dongsha Islands, the sea water begins to break away from the constraint of the isobath and flow across the isobath to the deep sea. Although there are only three years of data, the intervals between 2004, 2008, and 2010 are relatively large, and the observed results are relatively consistent, which to a certain extent shows that the appearance of the deflection of flow seems to be a normal state. Analyzing the long-term fixed-point (about 100 mile east of the Dongsha Islands) observed current data (Fig. 4.11), and found that during the entire observation period, except for the flow cross isobath to shallow water in October and March, the other times showed a very strong flow deflect from the isobath to the deep sea. Although the analysis is only for single-point observations, long-term continuous fixed-point observations have explained the flow characteristics of the sea area to a certain extent, which are basically consistent with the analysis results of the sailing ADCP. In order to further verify the normality of this phenomenon, the following uses WOA01 historical temperature and salinity data and ADT (absolute dynamic topography) data from satellite altimeters to calculate the distribution of geostrophic currents in the northern South China Sea to understand the characteristics of climate large-scale current. Figure 4.12 shows the calculated distribution of geostrophic velocity at depths of 100, 300, and 500 m in autumn. At the 100 m level, the current in the shelf/upland area is significantly southwest, that is, the north flank of the cyclonic circulation in the South China Sea. The flow near the 300 and 500 m isobaths still shows a southwest flow, but the northeast current is the main flow in the

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Fig. 4.11 The velocity data are from mooring station ADCP observation from 20 August 2000 to 17 March 2001, and collected from Aanderaa current meter at 1500 and 2000 m. “Along” means along the isobaths and “Vertical” means vertical to the isobaths. Terrain distribution around Dongsha Island is shown in the small box, with the mooring stations marked by solid pentacle and Dongsha Islands marked by solid triangle (Wang et al. 2013)

entire continental slope area, and the deflection happens when the current flows over the Dongsha Islands. This deflection phenomenon is more obvious in the velocity distribution of the 500 m layer. In summary, it can be seen that the current on the entire land slope is dominated by the northeast direction, but on the south side of the Dongsha Islands, there is a clear deflection characteristic of intermediate water flowing across the isobath to the deep sea. After a variety of field observation data and historical temperature and salinity data analysis and comparison, it can be summarized as follows: in the autumn, the current in the inter-middle level of the northern slope of the South China Sea is mainly northeastward, current flows almost along the isobaths in the west of the Dongsha Islands. However, on the southeast side of the Dongsha Islands, it shows obvious deflection characteristics of currents, and it has the characteristics of normalization. Next, numerical simulation will be used to reveal the dynamic mechanism of current deflection.

4.1.3.2

Numerical Simulation to Reproduce Current Deflection

Figure 4.13 shows the current velocity distribution at different depths in the northern part of the South China Sea in autumn using the POM (Princeton ocean model) model. It can be seen that at the 100 m level, the northern part of the South China Sea

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Fig. 4.12 The geostrophic velocity vectors at a 100 m, b 300 m, and c 500 m in fall. The geostrophic velocity is derived from the climatologic hydrography data (WOA01) and absolute dynamic topography (ADT). Dongsha Islands are marked by solid triangle Wang et al. (2013)

basically shows a cyclonic circulation under the control of the monsoon. However, unlike the geostrophic flow diagnosed by the WOA01 data, a weak northeastward current has been shown near the 100 m isobath. And there is a deflection phenomenon on the southeast side of Dongsha. At the 300 and 500 m levels, the northern slope area of the South China Sea is occupied by northeastward currents, and a very strong deflection phenomenon is shown on the southeast side of Dongsha, which is consistent with the results of geostrophic currents in WOA01 data. However, the location where the model simulation deflection occurs is easterly than the location where the WOA01 geostrophic current deflects. However, it can be seen from the analysis of the

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measured data that the actual location seems to be easter than the location where the WOA01 geostrophic current deflects. This may be caused by excessive smoothness and low resolution of WOA01 data. The model simulation results can reproduce the deflection phenomenon near Dongsha well, which provides the feasibility for using the model results to analyze the dynamic mechanism of the deflection phenomenon.

Fig. 4.13 Velocity field at a 100 m, b 300, and c 500 m in fall from POM, superimposed with the 50, 100, 500, 1000, and 2000 m isobaths. The triangle marks Dongsha Islands, and mooring stations marked by solid pentacle. The red line is a stream line that we selected to analyze the momentum balance in Fig. 12 Wang et al. (2013)

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4.1.3.3

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Dynamic Mechanism Analysis

(1) Vorticity Balance Cross-differentiate the vertically integrated momentum equation will result in the vertically integrated vorticity equation (Wang et al. 2010)             1 ∂ ∂ f f ∂ u ∂ ∂ v + J , =− u· +v· − ∂x D ∂y D D ∂t ∂ x D ∂y D       c a b         A τa τb F −curl +curl +curl (4.1) + curl D D ρ D ρ D       0   0 e

d

f

g

η

 η where (u, v) = −H udz, −H vdz represents the vertically integrated velocity, 

η dz is the potential energy, ρ is the density, J , D1 is the JEBAR term,  = −H zgρ ρ0

η is the surface elevation, D = H + η is the water column depth, τx , τ y a and

τx , τ y b are the surface and bottom stresses, respectively, and F = Fx i + Fy j and A = A x i + A y j are the vertically integrated horizontal diffusion term and the nonlinear advection term, respectively. The left-hand side of Eq. (4.1) includes (a) the tendency term. The right-hand side of Eq. (4.1) includes (b) advection of the planet potential vorticity f/D (APV) term, (c) the JEBAR term, (d) the diffusion term, (e) the advection term, (f) surface stress torque, and (g) bottom stress torque. All the terms are diagnosed using the model results. In the quasi-steady state, the tendency term should approximately be zero. Figure 4.14 displays the spatial distribution of each term in Eq. (4.1) in fall, limited to the deflection domain. The JEBAR and APV terms are dominant, and the advection term and the advection term are secondary. The contribution of wind stress curl and bottom stress torque is very small. This is mainly because the influence range of them is basically limited to the upper and bottom Ekman layers. Therefore, it affects the entire water column after vertical integration. The impact is very small. Although the direct influence of the surface and bottom stress on the overall water column is very weak, its indirect effect cannot be ignored, such as the influence of the large-scale circulation driven by it on the thermohaline structure. Since the Jebar term and APV term are the dominant terms of the vorticity balance, the following will mainly analyze these two terms. If we neglect the effects of advection, diffusion, and surface stress curl, Eq. (4.1) can be rewritten as       ∂ ∂ f f 1 u· +v· = J , (4.2) ∂x H ∂y H H due to (u, v) =

 η

−H

udz,

η

−H

vdz , and Eq. (4.2) can be rewritten as

4.1 Intermediate Waters and Circulation in the South China Sea Fig. 4.14 Spatial distribution of the vorticity terms in fall, superimposed with the isobaths. a JEBAR, b advection of the geostrophic potential vorticity, c advection plus diffusion, d surface stress torque, and e bottom stress torque (Wang et al. 2013)

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d dt



f H

 =

Jebar H

(4.3)

In order to verify the effectiveness of Eq. (4.3) in controlling the deflection phenomenon of the northern slope of the South China Sea, a barotropic streamline is selected in the sea area where the deflection phenomenon occurs, and Eq. (4.3) is diagnosed and analyzed. Figure 4.15 is the result of the diagnosis calculation. Figure 4.15a shows the distribution of the relative vorticity and planetary vorticity along the streamline. It can be seen that the planetary vorticity is much larger than the relative vorticity, and the relative vorticity is in the region where the deflection occurs. The change of the relative vorticity is also much smaller than the planetary potential vorticity, which confirms the feasibility of ignoring the relative vorticity when analyzing the change of the potential vorticity. And it can be seen that the planetary vorticity shows a significant decreasing trend in the area where the deflection occurs.

 Figure 4.15b is the diagnostic calculation of Eq. (4.3). It can be seen that f d and Jebar match very well, and their magnitude and change characteristics are dt H H quite consistent. This shows that Eq. (4.3) can explain the middle-level deflection flow near the Dongsha Islands well.

Fig. 4.15 The a distribution of the potential vorticity and the b relationship between the variability of the planetary potential vorticity and JEBAR, which are selected along the barotropic stream line (Wang et al. 2013)

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(2) Momentum Balance analysis The momentum equation can be written as du = Fx dt dv = Fy dt

(4.4)



where (u, v) denote the longitude and latitude velocity, and the Fx , Fy denote the forcing terms. The forcing terms can be written as (Wang et al. 2010) Fx = Am u x x + f v −Px +(K m u σ )σ        a

b

c

d

Fy = Am vx x − f u −Py +(K m u σ )σ        a

b

c

(4.5)

d

where (a) horizontal diffusion (difh), (b) Coriolis (cor), (c) pressure gradient (pre), and (d) vertical diffusion (difv)) Using the model output to perform diagnostic calculations on the momentum equation, it can be seen that in both directions, the geostrophic balance dominates the continental shelf current (Fig. 4.16). The along-isobath acceleration is positive during the deflection, and the ageostrophic term is the main contribution, which demonstrates the along-isobath pressure gradient is the active force that pushes the current to accelerate. It can be known from the geostrophic balance relationship that the pressure gradient along the isobath direction is positive, and the positive geostrophic deviation is provided by the pressure gradient. The previous analysis also pointed out that the density gradient along isobath points to the southwest, which means that the direction of the pressure gradient is northeast, which drives the current to accelerate along the isobath. In the cross-isobath direction, the pressure gradient is positive, indicating that there is a high-pressure area at the outer edge of the continental slope, which is consistent with the pressure distribution in the inter-middle layer of the northern continental slope area of the South China Sea analyzed by CTD data. The cross-isobath acceleration is negative, and then the current is pushed to deflect from the isobath. From the dynamic balance relationship in the cross-isobath direction, it can be known that the ageostrophic term is also the main contribution. The ageostrophic term in the cross-isobath direction is negative, indicating that the pressure gradient cannot completely offset the Coriolis force, and the Coriolis force becomes the main contributor to the change of the speed in the cross-isobath direction. Based on the above discussion, the dynamic process of the deflection can be summarized as follows: To the west of the Dongsha Islands, sea water basically flows along the isobath of the land slope. The pressure gradient force along the northeast direction of the land slope drives the sea water to accelerate continuously. And the Coriolis forcing vertical to the isobath increases gradually, and then becomes larger than the cross-isobath pressure gradient forcing. So, the

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Fig. 4.16 Momentum balance along the stream line at 500 m (Wang et al. 2013). cor, Coriolis force; pre, pressure gradient; age, ageostrophic term; ace, acceleration; difh, horizontal diffusion; difv, vertical diffusion; A, terrain term (all multiplied by 106 ). x denotes the direction along the stream, and y denotes the direction orthogonal to the stream

cross-isobath acceleration by the Coriolis force is negative, and then the current is pushed to deflect from the isobath. The results of momentum analysis and vorticity analysis are consistent. In the vorticity analysis, the Jebar term produces the effect of the density gradient along the slope, while the result of the momentum analysis is the contribution of the pressure gradient along the slope. These two are different expressions of the same dynamic factor, and both are the combined effect of baroclinic and terrain. Based on the above analysis, the dynamic mechanism of the deflection near the Dongsha Islands can be summarized as follows: near the Dongsha Islands, due to the strong density gradient distribution along the isobath, the negative center of the combined effect of baroclinic and topography (Jebar) is formed. Under the action of Jebar, the potential vorticity of seawater decreases. Since the potential vorticity near the Dongsha Islands is mainly controlled by topography, the current must flow across the isobath to the deep water to meet the constraint relationship of Eq. (4.3) (Fig. 4.17).

4.1.4 Summary In this Section, we review and summarize the climatic state characteristics of the middle waters mass in the South China Sea and its interannual variation, and find

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Fig. 4.17 The schematic of the deflection of the Dongsha Islands inter-middle current. The red current denotes the deflection currents discussed in our paper Wang et al. (2013)

that the temperature near the core depth of the middle waters mass in the South China Sea has shown an increasing trend in the past 20 years, but the water temperature has shown a decreasing trend in the lower part of the middle waters mass below 700 m and the upper part of the deep waters mass. The change of salinity is different from that of temperature, and the trend of salinity on all layers below 300 m is basically the same, all experiencing an increasing to decreasing process in the middle and late 1980s, and mainly showing an increasing trend from the early 1990s to the present. The variation of waters mass properties in the South China Sea is not a monotonous and linear process, in some time the change is more drastic, there are “jump” changes; in some time, the change is not very significant, the evolution of water mass properties is relatively slow. The origin of the middle layer waters and its contribution to the three-layer circulation in the South China Sea are still unclear, and researchers need to continue their efforts in this area.

4.2 Deep Water Mass and Circulation in the South China Sea The classical deep circulation theory assumes that one or several point sources, the uniform distribution of sink that maintains the thermocline structure, and that there is no change in the deep-sea topography, it is concluded that large-scale circulation in the deep sea satisfies the Sverdrup relationship, and there is a polar flow with low speed. According to the conservation of mass, there is a strong western boundary current in the deep ocean (Stommel 1960a, b). As for the research on the South

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China deep Sea, first of all, it should focus on the research of deep waters sources. Since the South China Sea is a tropical sea, there is no deep convection process itself. The overflow of the North Pacific deep waters is very important for the deep ocean circulation in the South China Sea. Observations have shown that in the South China Sea Basin, the temperature and salinity characteristics of deep waters are relatively uniform, and are similar to those of Pacific water around 2000 m near the Philippines (Nitani 1972; He and Guan 1984; Broecker et al. 1986). This indicates that the deep waters of the South China Sea are the deep waters of the Pacific from the sill of the Luzon Strait. The deep water of the Pacific Ocean on the east side of the Luzon Strait is denser because of its lower temperature and higher salinity, so it will sink when it flows through the Luzon Strait (Wyrtki 1961). To compensate for this sinking movement, the deep waters of the South China Sea will be renewed. The few deep-sea flow observations in the Luzon Strait in the 1970s and 1980s supported the judgment that high-salt Pacific water entered the deep-sea basin of the South China Sea. Wang (1986) used a one-dimensional vertical advection diffusion equation to calculate. The results show that a vertical flux of about 0.7 Sv is used to maintain the deep waters stratification of the South China Sea. The measurement results of Liu and Liu (1988) show that the deep ocean overflow of the Luzon Strait is 1.2 Sv. Qu et al. (2006b) used NODC (National Oceanographic Data Center) hydrological data to estimate that the deep-sea overflow of the Luzon Strait was 2.5 Sv. Tian et al. (2006) used the collected hydrological data to verify that the current in the Luzon Strait forms a “sandwich” structure, in which the deep transport is 2 Sv. Yang et al. (2010) used the hydrological data observed in the Luzon Strait in July 2007 and October 2005 and found a deep westward current with 2 Sv. Chang et al. (2010) analyzed the measurement results in two canyons in the Luzon Strait and found that the transportation volume of the southern canyon is 1.06 Sv. Tian and Qu (2012) summarized the above observation results and proposed a future observation concept for the deep circulation in the South China Sea. In addition, the relevant observations of marine geology have also confirmed the invasion of deep waters overflow from the Pacific Ocean in the Luzon Strait. Lüdmann et al. (2005) found that in the sediment samples collected in the northern part of the South China Sea, there are sedimentary belts along the southwest of Taiwan to the Dongsha Islands in the South China Sea. These sedimentary belts indicate that the the North Pacific Ocean deep water flows up when its flow northwest through the Luzon Strait along the northern slopes of the South China Sea. The sediments from eastern and southern Taiwan resuspended during the upflow process and finally settled down to form these belt structure. Shao et al. (2007) inferred from the distribution characteristics of the continental shelf in the northeastern part of the South China Sea, the deep water in the South Sea from the Luzon Strait flows northwest along the northern slope of the South China Sea until it turns into the interior of the South China Sea. Zheng et al. (2012) summarized the discovered deep channels in the northeastern South China Sea basin by reflection seismic methods. Due to the deep overflow of the Pacific Ocean entering the Luzon Strait in the South China Sea, the South China Sea has a similar structure to the thermohaline circulation, which is consistent with the Stommel deep-sea circulation theory. Li and Qu (2006)

4.2 Deep Water Mass and Circulation in the South China Sea

183

proposed a conceptual diagram of the thermohaline circulation in the South China Sea, which includes the three-layer, cross-basin exchange cell through the Luzon Strait, that is, the rising structural cell along the upper and middle layers of the northern slope, the deep-sea renewal cell, and the deep-sea internal cyclone structural units. The density structure and oxygen content distribution show that both potential vorticity and high oxygen content invade from the Luzon Strait, while the salinity distribution shows that it also invades from the Luzon Strait at a depth of 2000 m. Cyclone circulation around the South China Sea to the eastern border decreases. The deep ocean circulation is basically a cyclonic structure, which is consistent with Stommel’s deep ocean circulation theory. Wang et al. (2011) found based on GDEM3.0 (generalized digital environment model 3.0) data that the distribution of potential temperature, salinity, and potential density in the 3000 m layer all show that deep water in the North Pacific has invaded from the Luzon Strait. And they used the dynamic diagnosis to give the circulation situation of the South China Sea from 2400 m to the bottom. The deep-sea north of the South China Sea is a cyclonic circulation, there is a strong deep-sea west boundary current, and the south is a weak cyclonic circulation. So far, few models have been used to study the deep circulation in the South China Sea. Mao et al. (1992) used a three-dimensional ocean current model to numerically simulate the seasonal average currents in the South China Sea using a semi-implicit format combined with a C-grid. The results show that at a depth of 1200 m, the basic circulation in winter, spring, and summer is exactly the opposite of the upper-middle circulation. Chao et al. (1996) used a 0.4°*0.4° free surface ocean model, using climatic wind stress and open boundary conditions, and proposed for the first time that the renewal process of the deep water of the South China Sea was completed with the deep water overturning in the northeastern part of the South China Sea and southeastern Vietnam. The deep-sea circulation structure is roughly southwestward over-flow from the western boundary, and the bottom water renewal time is about 83 years. Yuan (2002) used the MOM (modular ocean model) model (with a horizontal resolution of about 0.16°× 0.16°), and only considered the influence of the Luzon Strait on the deep-sea circulation structure of the South China Sea, ignoring wind stress to simulate the sandwich structure of the South China Sea circulation: that is, the Pacific Ocean watert flow into the South China Sea through the Luzon Strai in the surface and deep layers, while the intermediate South Sea water flows out of the Luzon Strait. This outflow and inflow are accompanied by a cyclonic circulation structure in the surface and deep layers of the South China Sea, and an anticyclonic circulation in the middle structure.

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4 Middle and Deep Waters Mass and Circulation …

4.2.1 Characteristics of Intermediate Circulation and Deep Circulation in the South China Sea Simulated by Various Models 4.2.1.1

Introduction of Date

The monthly average output data of the eight models are shown in Table 4.1, with SODA (simple ocean data assimilation) (version v2.2.4) as the control data. It can be seen from Table 4.1 that the atmospheric forcing field and the initial temperature and salinity field of different models are not the same. The horizontal resolution of most model data is about 0.1°. In addition, temperature-salt date WOA2001 and GDEMv3 (Generalized Digital Environment Model) are also used.

4.2.1.2

Simulation of Deep Waters in the South China Sea

Figures 4.18 and 4.19 are the relative deviations of temperature and salinity corresponding to the WOA01 at the 2800 m layer and each mode. From the distribution of temperature relative deviation (Terr ), most of the current models have negative deviations in the 2800 m layer. Among them, the relative deviation of LICOM (LASG/IAP climate system ocean model) is relatively small, while the deviation of SODA and JPL-R is −60 to −50%, and the relative deviation of ECCO2, OCCAM, HYCOM, OFES and BRAN is close to −40%. Look at the relative deviation of salinity in the 2800 m layer (Serr ), it has both positive and negative deviations in the horizontal distribution, and the magnitude is smaller than the relative temperature deviation, and the absolute value is mostly about 20%. Then Terr and Serr are averaged in the South China Sea basin at each level to obtain a profile of relative deviation, as shown in Fig. 4.20a and b. The relative deviation of temperature is negative below 1500 m. From 1500 to 2800 m, the relative deviation is around −100%, and at 2800 m, the deviation becomes larger, approaching −200%. The distribution of relative deviation of salinity is obviously different from the distribution of relative deviation of temperature. Except for LICOM, the relative deviation of salinity of other modes swings between positive and negative as the depth increases, and the greater the positive relative deviation in the deeper layers. On the whole, the temperature and salinity of each model in the deep layers of the South China Sea are relatively low (Fig. 4.20c and d,). The possible reason is that the deep waters of the South China Sea come from the deep water of the North Pacific on the east side of the Luzon Strait. In the model, the temperature and salinity of the deep water on the east of the Luzon Strait are relatively low.

WOA1994

1986–2008

Thermohaline initial field

Data time range

yes

yes

ERA-40

Assimilation

Atmospheric forcing field

KPP

KPP

Mixed scheme

0.25°

1992–2008

WOA1998

NCEP/NCAR

40

0.4° × 0.25°

40

Horizontal resolution

Vertical layer

ECCO2 MITgcm

SODA

POP

Date

Ocean model

Table 4.1 Information of date Xie et al. (2013a, b) OCCAM

1988–2004

WOA1998

NCEP/NCAR

no

PP

66

0.08°

GFDL gcm

HYCOM

2004–2009

GDEMv3

NOGAPS

yes

KPP

33

0.08°

Hycom

JPL-R

2001–2009

WOA2001

NCEP/NCAR

no

KPP

30

0.125°

ROMS

LICOM

2000–2007

WOA1998

NCEP/NCAR

no

Canuto

55

0.1°

LICOM2.0

OFES

41–50

WOA1998

NCEP/NCAR

no

KPP

54

0.1°

MOM3

BRAN

1994–2006

WOA2001

ERA-40

yes

KPP

47

0.15°

MOM4.0

4.2 Deep Water Mass and Circulation in the South China Sea 185

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4 Middle and Deep Waters Mass and Circulation …

Fig. 4.18 Relative deviation of 2800 m layer temperature (%) Xie et al. (2013a, b); a SODA; b ECCO2; c OCCAM; d HYCOM; e JPL-R; f LICOM; g OFES; h BRAN

4.2.1.3

The Deep Overflow Through Luzon Strait

Table 4.2 shows the strait fluxes of the upper, intermediate and deep waters of the Luzon Strait. The transport estimates of the entire Luzon Strait derived from these models are consistent with existing studies (Fang et al. 2005). Except for the JPL-R mode, the flux of deep layer is about 0.50 Sv, and all are westward, which is obviously weaker than the observation result. The average flux value of the deep layer of the 8 modes is 0.36 Sv, and the deviation between modes is 0.22 Sv. Besides, the seasonal variability is large. Figure 4.21 shows the seasonal changes of water exchange in the depths of the Luzon Strait (below 1500 m). It can be seen that the assimilated models have relatively large seasonal changes. The deep over-flow reaches its maximum in winter and minimum in spring. Assimilated data such as SODA, ECCO2, HYCOM, and BRAN and unassisted data (OCCAM, LICOM, and OFES) all show west inflow in July and October. These characteristics are similar to Tian et al. (2006) and Yang et al. (2010). From the perspective of deep transport in the Luzon Strait, SODA,

4.2 Deep Water Mass and Circulation in the South China Sea

187

Fig. 4.19 Relative deviation of 2800 m layer salinity (%) Xie et al. (2013a, b); a SODA; b ECCO2; c OCCAM; d HYCOM; e JPL-R; f LICOM; g OFES; h BRAN

ECCO2, HYCOM, and BRAN are better in the assimilated data, and main problem is that the flow is weak.

4.2.1.4

The Vertical Integral Streamfunction of the Deep South China Sea

Using the GDEMv3 climatic temperature and salinity dataset, we select 2400 m as the zero potential energy surface, and calculate the geostrophic flow of each layer deeper than 2400 m, and then calculate the vertical integral streamfunction from 2400 m to the bottom; At the same time, the corresponding streamfunction is obtained by vertical integration of each model at a depth of 2400 m, as shown in Fig. 4.22. Compared with the geostrophic streamfunction of GDEMv3, except for JPL-R, the streamfunctions of other modes are weaker. There are large-scale cyclonic

188

4 Middle and Deep Waters Mass and Circulation …

Fig. 4.20 The average temperature and salinity deviation in the South China Sea (a, b) and the temperature and salinity deviation profile on the west side of the Luzon Strait (c, d) Xie et al. (2013a, b)

Table 4.2 Water quality transport and monthly average standard deviation in the Luzon Strait Xie et al. (2013a, b). (Unit: Sv) Models

SODA ECCO2 OCCAM HYCOM JPL-R LICOM OFES BRAN 平均

Full layers

−1.70 −4.86 (0.87) (2.23)

−4.06 (1.13)

−5.22 (1.96)

−6.02 −5.86 (3.89) (2.46)

−3.42 −5.50 (1.48) (2.01)

−4.92 (0.81)

Upper layers (0–500 m)

−1.69 −4.56 (1.19) (1.71)

−3.78 (1.48)

−5.55 (2.33)

−5.63 −5.66 (3.44) (1.93)

−3.45 −7.14 (1.68) (1.18)

−5.33 (1.37)

0.01 (0.46)

0.39 (0.34)

1.03 (0.49)

−0.60 0.05 (1.13) (0.70)

0.06 1.91 (0.38) (0.62)

0.77 (0.79)

−0.71 −0.31 (0.30) (0.45)

−0.67 (0.39)

−0.70 (0.72)

0.21 −0.25 (0.23) (0.68)

−0.03 −0.26 (0.14) (0.30)

−0.36 (0.22)

Middle layers 0.70 (500–1500 m) (0.36) Deep layers (>1500 m)

Note The value without parentheses indicates the quality of seawater transport, the positive value indicates the outflow of the South China Sea, and the negative value indicates the inflow into the South China Sea; the value in the bracket is the monthly average standard deviation

circulations in the deep layers of the South China Sea, but there is a big difference in the amplitude and spatial distribution of the stramfunction. The geostrophic current streamfunction of GDEMv3 shows that its negative cyclone area mainly exists in the middle region, and there is also a weakly negative cyclone area in the southwest corner. For the negative cyclone area of the streamfunction in the middle region, the

4.2 Deep Water Mass and Circulation in the South China Sea

189

Fig. 4.21 Seasonal changes of water exchange in the deep (under 1500 m) of the Luzon Strait Xie et al. (2013a, b)

model results are all to the west. LICOM and BRAN are also mixed with a high positive area (corresponding to anticyclonic circulation) near the negative cyclone area (corresponding to cyclonic circulation). It is worth noting that there is outflow at a depth of 1500 m in the Luzon Strait in JPL-R model, but the bottom circulation is a cyclonic circulation, which is quite different from other models of Stommel deep sea circulation theory driven by inflow. Because JPL-R has strong eddy motion in deep layers, the interaction between the eddy and the bottom topography of the South China Sea can also trigger the deep large-scale cyclonic circulation, which is consistent with the eddy-flow interaction theory of Holloway (1992).

4.2.1.5

Summary

Xie et al. (2013a, b) initially analyzed the deep-layers and bottom circulations of the South China Sea simulated by eight quasi-global high-resolution ocean models, and summarized the basic characteristics of the deep layers and bottom circulations in the South China Sea. The analysis of temperature and salinity error shows that the relative deviation of deep waters temperature are uniformly negative, indicating that the deep water is uniformly colder, and the salinity deviation first becomes negative deviation

190

4 Middle and Deep Waters Mass and Circulation …

Fig. 4.22 Vertical integral streamfunction from 2400 m to the bottom Xie et al. (2013a, b); a GDEMv3; b SODA; c ECCO2; d OCCAM; e HYCOM; f JPL-R; g LICOM; h OFES; i BRAN

and then positive deviation as the depth increases. The deviation of temperature is greater than salinity, and there is a tendency of homogenization of temperature and salt in the deep layer.) The water exchange average value of 8 modes in the depths of the Luzon Strait (under 1500 m) is 0.36 Sv, which is lower than the observed value. Both the assimilated model and the unassimilated model (OCCAM) show that deep water exchange in the Luzon Strait is minimal in spring and reaches its maximum in winter. The vertical integral streamfunction of most models at 2400 m show that the deep South China Sea is a cyclonic circulation on a large scale, but the distribution of the streamfunction is quite different from the streamfunction diagnosed by the climatic temperature and salinity dataset (GDEMv3).

4.2 Deep Water Mass and Circulation in the South China Sea

191

4.2.2 Sensitivity Test of the Deep Circulation in the South China Sea to Topography 4.2.2.1

Theoretical Analysis

To theoretically explore the relationship between the deep circulation and topography of the South China Sea, the shallow water equation is: τ R u ∂ u  + k × f u = −g∇η + − ∂t ρH H

(4.6)

where, u is the flow velocity, f is the Coriolis parameter, g is the acceleration of gravity, η is the sea surface height, H is the depth, τ is the shear stress, ρ is the density, and R is the friction coefficient. Take the curl of Eq. (4.6) to get the vorticity equation as   τ R u ∂ f =ν× −∇ × (∇ × u) + J ψ, ∂t H ρH H

(4.7)

wher ψ is the streamfunction. Making the equation dimensionless, we get ε

  τ u ∂ f =ε× − ε∇ × (∇ × u) + J ψ, ∂t H H H

(4.8)

In the formula, ε = f0RH0 is a dimensionless parameter. According to the actual characteristics of the South China Sea, take R = 0.0008, f 0 ≈ 10−5 , H0 ≈ 1000m, The magnitude of ε is 10−11。ε ε is very small, the zero-order approximate equation is   f =0 (4.9) J ψ0 , H Equation (4.9) indicates that in the zero-order approximation, the streamfunction is parallel to the contour of Hf . Since the potential vorticity Hf of the deep layers of the South China Sea are mainly determined by H , there is |u| ≺

|∇ H | H2

(4.10)

Considering the actual stratification in the deep layers of the South China Sea, integrating a certain layer, the resulting vorticity equation is     1 τ ∂ f R u = J χ, +∇ × −∇ × (∇ × u) + J ψ, ∂t H H ρH H

(4.11)

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4 Middle and Deep Waters Mass and Circulation …

0

where, χ = ρ10 −H gρzdz; J χ , h1 is JEBAR item. When this item is integrated along a certain contour of H , the result of the closed loop integration is 0, then the vorticity equation in integral form is ¨

∂ (∇ × u)d xd y + ∂t

¨

  ¨ ¨ f τ R u J ψ, d xd y = ν× d xd y − ∇× d xd y H ρH H

(4.12)

Using a dimensionless method similar to the barotropic vorticity equation, the Eq. (4.10) can also be obtained. It can be seen from Eq. (4.10) that the deep horizontal circulation in the South China Sea has a strong dependence on the depth and slope of the topography.

4.2.2.2

Mode Test

To test the rationality of formula (4.10), the Princeton ocean model (POM) is used to do two sets of sensitivity tests topo_h and topo_l of the deep circulation of the South China Sea to the topography. Figure 4.23a shows the topography used in the topo_h test. The corresponding mode uses high-resolution topography. Figure 4.23b shows the topography used in the topo_l test. The corresponding mode uses low-resolution topography. Other conditions are the same: the initial model temperature and salinity conditions are taken from the climatic GDEMv3 temperature and salinity data, the open boundary velocity conditions are taken from the climatic SODA reanalysis data, the heat flux conditions are taken from the climatic NCEP/NCAR data, and the wind field is taken from Climatic QuikScat wind field data. The model selects the fixed temperature and salinity diagnostic model. Figure 4.23c, d respectively show the 2000 m flow field corresponding to topo_h test and topo_l test (velocity less than 1 cm/s is omitted, the 2500 m flow field is similar). It can be seen that the deep circulation in the South China Sea is a cyclonic circulation, and the larger flow velocity is basically concentrated in the deep slope area with steep topography. The only difference between the two experiments is that the deep flow velocity of the topo_h test is greater than the deep flow velocity of the topo_l test. From Eq. (4.10), we can see that the larger topography |∇HH2 | , the larger corresponding velocity |u|. Figure 4.24a and c are the distribution of topography |∇HH2 | and 2000 m |u| in the topo_h test, while Fig. 4.24b and d are the distribution of the topography |∇HH2 | and 2000 m |u| in the topo_l test. It can be clearly seen that from the high-resolution topographic test to the low-resolution topographic test, distribution of topography |∇HH2 | decreases, and the corresponding flow velocity also decreases. From the above theoretical analysis and POM sensitivity test experiment, it can be known that the deep circulation of the South China Sea is more sensitive to the topography, and the difference of the model topography can obviously cause the change of the circulation intensity.

4.2 Deep Water Mass and Circulation in the South China Sea

193

Fig. 4.23 The topography of the two sets of experiments and the corresponding 2000 m flow field Xie et al. (2013a, b); a topo_h test topography; b topo_l test topography; c 2000 m flow field corresponding to topo_h test; d 2000 m flow field corresponding to topo_l test

4.2.3 Diagnostic Model of the South China Sea Bottom Circulation in Condition of Tidal Mixing, Eddy-Induced Mixing and Topograph 4.2.3.1

Introduction to Diagnostic Model

Combining the actual characteristics of the South China Sea, Xiao et al. (2013) rederived new diagnostic model of deep and bottom circulation in the South China Sea by adding the effects of mesoscale eddies, tides, and the overflow in the Luzon Strait into the vertical velocity. The diagnostic model in this section is similar to the wind-induced barotropic flow model in the Arctic Ocean (Nilsson et al. 2005; Nøst and Isachsen 2003; Aaboe and Nøst 2008).)

194

4 Middle and Deep Waters Mass and Circulation …

Fig. 4.24 Topography |∇HH2 | and corresponding 2000 m layer velocity (unit: m/s) distribution Xie et al. (2013a, b); a. Topo_h test topography; b. Topo_l test topography; c. 2000 m layer velocity corresponding to topo_h test; d. 2000 m layer velocity corresponding to topo_l test

The flow rate can be written as: vg = vs + vb

(4.13)

where vb is the bottom velocity, vs is the thermal wind caused by the difference in density (the bottom is selected as the reference surface), which can be expressed as g  vs = − k× ρ0 f

z0

ρr + ρ  dz

(4.14)

−H

In the formula, ρr = ρr (H ) is the reference density, which is defined later. The bottom speed can be written as vb = vρb + v0

(4.15)

4.2 Deep Water Mass and Circulation in the South China Sea

195

where, g  ρ k × ∇H ρ0 f b

(4.16)

1  k × ∇ p0 ρ0 f

(4.17)

vρb = − v0 =

Assuming that P0 is just a function of H , it is proportional to the near-bottom streamfunction, so that the contours of the bottom streamfunction coincide with the contours of H . . This assumption has certain reliability. Bretherton and Haidvogel (1976) extended the two-dimensional classical turbulence theory to quasigeostrophic turbulence under two-dimensional small-scale topography, and found that the contours of the streamfunction will eventually coincide with the isobath. Relevant studies have concluded that there is a clear correlation between the bottom streamfunction and the topography, that is, an anticyclonic circulation will appear in the upper part of the seamount, and a cyclonic circulation will appear in the trough (Holloway 1987 and 1992). At the same time, the flow velocity observed near the bottom also shows a strong trend of coincidence between the bottom flow and the topography (Holloway 2008).  z0 Integrate v vertically, V = −H vdz, where h = H + z 0 , z 0 is a certain standard layer, and V can be decomposed into V = VQ + h v0 + Va

(4.18)

In the form, VQ =

z0



vs + vρb dz = VS + h vρb

(4.19)

−H

VS =

z0 −H

g  vs dz = − k× ρ0 f

z0 z0



∇ ρr + ρ  dzdz 

(4.20)

−H −H

Equation (4.18) mainly considers the decomposition of steady flow. For each tidal cycle component, the long-term average can be regarded as 0, so the horizontal transport of the tide is not considered. Va is to consider bottom Ekman layer transport or surface Ekman layer transport. As it is assumed that the bottom flow is along the bottom isopotential vorticity line u b · ∇ H = 0, (approximately the isobath), the bottom vertical velocity is Wb = − and the vertical velocity at a certain horizontal plane z 0 can be taken as Wt = W0 + Weddy + Wtide. Where Wt is the vertical suction rate at the top of the layer, and W0 is the background vertical rising speed (W0 is the simulation of the uplift of caused by the “overflow” in the Luzon Strait, taking 2.83 × 10−6 m/s, then for a

196

4 Middle and Deep Waters Mass and Circulation …

2000 m, the total vertical flux is 2.40 Sv), W eddy is the vertical velocity caused by eddy mixing and Wtide is the vertical velocity caused by tidal mixing. According to ∇ · V = Wt , the divergence of Eq. (4.18) can be obtained: −∇ · (h v0 ) = −VQ ·

∇f + ∇ · Va + Wt f

Here we use the ∇ · ( f v0 ) = 0, thus −VQ ·

= ∇ · VQ , In addition

∇f f

⎛ ⎜ ∇ · Va = Ws − Wb = curl ⎝

(4.21)



τ s

ρ0 f

⎞

⎛

⎜ ⎟ ⎠ − curl ⎝



τ b

ρ0 f

⎞ ⎟ ⎠

(4.22)

where, the Ws is the upper Ekman pumping and the Wb is the bottom Ekman pumping. If we intergrate from the bottom to the sea surface, consider the upper ocean Ekman pumping. If we integrate into a certain layer, the upper ocean Ekman pumping is not considered. Integrate along hf , because hf is mainly determined by h, it can be approximately integrated along the contour of H . According to the assumption that P0 is only a function of H , eliminate the first term of Eq. (4.21), so  C(H )

τb · tds = ρ0 f

 ¨  ∇f −VQ · + Wt d A f

(4.23)

A(H )

According to the assumption that p0 is a single-valued function of H , we have   g  1 d p0 (H )  ρb + vb = − k × ∇H ρ0 f ρ0 f dH

(4.24)

Assuming that τb = Rρ0 vb , and R is the coefficient of friction. Substituting into the formula, there are   ˜ Q · ∇ f + Wt dA − V f ρ0 A(H ) dp0 

+ gρb  (4.25) = 1  dH R  k × ∇ H · tds C(H ) f 2



Define

( (

) )

1   C(H ) f 2 ρb k×∇ H ·t ds  1   C(H ) f 2 k×∇ H ·t ds

, then ρb  = 0, we can get

  Q · ∇ f + Wt d A − V A(H ) f 

k × ∇ H + vρb  1   k × ∇ H · t ds C(H ) f 2

 vb =

1 Rf

(4.26)

4.2 Deep Water Mass and Circulation in the South China Sea

197

In Eq. (4.26), −VQ · ∇f f will be called baroclinic forcing, and the Weddy and Wtide in Wt = W0 + Weddy + Wtide are called eddy forcing and tidal forcing, respectively. W0 is the uplift of the water caused by the “ overflow” in the Luzon strait. The density flow vρb is mainly caused by the difference in the density of the bottom layer. Because of the scarcity and homogenization of the bottom layer observation data, its influence is not considered. It can be seen from Eq. (4.26) that the bottom flow field has a great relationship with ∇ H , and where the topography slope is large, the corresponding velocity should be relatively large, and where the topography slope is small, the corresponding velocity should also be relatively small. If the contour H is p0 along the opening not closed, such as in a strait, it is also assumed that the contour ddH d p0 vb is a constant, then dH = −ρ0 f |∇ H | , where vb is the measured velocity of the strait. The secondary friction rate can also be used to derive the corresponding formula, which is qualitatively consistent with the linear friction rate, but the expression is more complicated. Integrate from the seabed to a certain standard layer z 0 , and then calculate the flow field diagram on the contour of z 0 according to Eq. (4.26). This section only calculates the bottom flow field of the South China Sea basin enclosed by the closed isobath of 2000–4200 m (When calculating, take g = 9.81 m/s2 , ρ0 = 1025 kg/m3 , R = 8 × 10−4 m/s).

4.2.3.2

Equivalent Vertical Velocity Caused by Tides W tide

The tide parameterization scheme proposed by St. Laurent (2002) is adopted. This scheme is finally transformed into a vertical mixing coefficient, in which the principles of work and energy conversion is used. According to the idea of finally transforming tidal energy into gravitational potential energy, and finally expressed by improved vertical mixing speed. Considering the periodic flow on the topography, the damping produced by it is D=

1 u Nb κr 2  2

(4.27)

where Nb is the buoyancy frequency at the bottom; κ is the topographic wave number → u is the velocity vector generated by internal waves; r is the topographic roughness; − of the barotropic tide. The total energy extracted by the internal wave from the barotropic tide can be expressed as E tide =

1 ρ0 Nb κr 2 u2 2

(4.28)

The effective energy used for mixing can be written as E eftide = qΓ E tide

(4.29)

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4 Middle and Deep Waters Mass and Circulation …

In the formula, q is the ratio of internal wave energy used for the bottom layer mixing, generally taken as 1/3; Γ is the mixing efficiency, generally taken as 0.2. This part of the effective energy is described according to the following distribution in the entire water column. e−(H +z)/ξ E ztide = E eftide F(z) = E eftide

ξ 1 − e−H/ξ

(4.30)

In the formula, ξ is the tidal vertical dissipation scale, the range is 300–1000 m, here ξ = 500 m. Consider the two-layer fluid enclosed by the horizontal plane z 1 , z 2 , z 3 , and the average density of the water enclosed by z 1 and z 2 is ρ1 , and ρ2 > ρ1 . Now calculate the vertical mixing rate Wtide of the interface z 2 according to the work and energy tide tide − E z1 ) is conversion. Because ρ2 > ρ1 , , the effective energy flux of the tide (E z3 used to lift heavy water into light water, and static instability will occur, and mixing occurs naturally. The vertical thickness of the water mixing (βφ) is expressed by the product of the total tidal height of the barotropic tide φ and the correction factor β, , where the value of the correction factor ranges from 3 to 10, and β = 8 is used here. In this way, according to the work and energy conversion, the vertical mixing rate of the interface (Wtide ) can be obtained, and the expression is finally Wtide =

4.2.3.3

tide tide E z3 − E z1 (ρ2 − ρ1 )gαφ

(4.31)

Eddy-Induced Equivalent Vertical Velocity W eddy

Assuming that the sea surface height anomaly η measured by the satellite altimeter mainly represents the first baroclinic mode, there is 

p1 (x, y, 0, t) = ρ0 gη

(4.32)

The pressure disturbance structure function pˆ n can be expressed as 

p1 (x, y, z, t) = ρ0 gη

pˆ n (x, y, z) pˆ n (x, y, 0)

(4.33)

Then the energy flux represented by it is ⎛ ⎜ ⎜ E tide = ∇h · ⎜ ⎝

 0 0 d −H

β

 2 f 2 ρ0

−H

∂ p12 ∂x

⎞ d

→ ⎟   ⎟ u 1 1⎟ ⎠

(4.34)

4.2 Deep Water Mass and Circulation in the South China Sea

199

Substituting formula (4.33) into formula (4.34), we have E tide Make Q =

ρ0 g 2 β ∂ =− 2 f 2 ∂x

∫0−H pˆ 12 (x,y,z)dz , pˆ 12 (x,y,0)



∫0−H pˆ 12 (x, y, z)dz 2 η pˆ 12 (x, y, 0)

 (4.35)

According to γ ≈ γW E K , we can get Q=

π 2 c12

(4.36)

2N (0)Nz H

where is c1 the phase velocity of the first baroclinic mode; N is the buoyancy frequency. Substitution (4.35), there is E eddy

ρ0 g 2 β ∂ =− 2 f 2 ∂x



π 2 c12 η2 2N (0)Nz H

 (4.37)

The parameters F(z), q, Γ and ξ used in the process of calculating the equivalent eddy-induced vertical velocity W eddy are consistent with the tide parameterization scheme, and the value β range is 10–20. Here, we take 16 and finally get eddy

Weddy =

4.2.3.4

E z3

eddy

− E z1

(ρ2 − ρ1 )gβ|η |

(4.48)

Sources of Date

The temperature and salinity data uses the latest GDEMv3 climatic temperature and salinity dataset published by The Naval Research Laboratory (NRL). GDEMv3 has a horizontal resolution of 0.25° × 0.25° and is divided into 78 layers vertically. It is currently a publicly available South China Sea temperature and salt dataset with better quality control and higher resolution. The climatic annual average data of Quickscat wind field, ETOPO2 topography data, and OSU tide data (version tpxo6.2. http://volkov.oce.orst.edu/tides/global.html) are also used. In addition, the sea surface height anomaly data uses the AVISO TOPEX/ERS/Jason1 fusion data of IPRC (International Pacific Research Center), with a time resolution of 1 week and a time length of November 1, 1992 to March 31, 2010).

200

4 Middle and Deep Waters Mass and Circulation … e o

24 N

o

21 N 0.1m/s

o

18 N

15oN

o

12 N

o

9N 111oE

114oE

117oE

120oE

123oE

Fig. 4.25 Spatial distribution of “overflow” and baroclinic forcing and corresponding bottom flow field (Xiao et al. 2013); a 2400 m; b 2800 m; c 3200 m; d 3600 m

4.2.3.5

The Bottom Flow Field Driven by Baroclinic Forcing and “Overflow”

Only the “overflow” and baroclinic forcing in the Luzon Strait are considered, and the tidal and mesoscale eddy forcing are not considered. This situation corresponds to most previous numerical simulation results without tidal mixing. Figure 4.25a–d are the spatial distribution diagrams of the sum of “overflow” and baroclinic forcing in the 2400 m, 2800 m, 3200 m and 3600 m layers respectively. It can be seen that the sinking movement area is mainly concentrated in the central South China Sea basin, and the distribution is similar to the baroclinic forcing. According to the above model, the the spatial distribution of the bottom flow field determined by baroclinic effect and the “overflow” can be calculated (Fig. 4.25e). From the Fig. 4.25e, we can know that there are cyclonic circulations on the 2400–4200 m isobath of the South China Sea. The maximum value of the velocity is about 0.09 m/s, and its magnitude is 0.1 m/s.

4.2.3.6

The Bottom Circulation of the South China Sea Under the Influence of Tides and Mesoscale Eddies

Under the action of the “overflow” in the Luzon Strait, the circulation at the bottom of the South China Sea is a cyclonic circulation. According to Eq. (4.28), it can be roughly judged that the combined effects of tidal forcing and eddy forcing will trigger the cyclonic circulation at the bottom of the South China Sea. Therefore, tidal forcing and eddy forcing both play the role of strengthening the cyclonic circulation in the bottom of the South Sea. Under the action of the “overflow”, tidal forcing and eddy forcing will not change the overall shape of the flow field. Combining baroclinic forcing, eddy forcing, tidal forcing and “overflow”, we get Fig. 4.26a–d.

4.2 Deep Water Mass and Circulation in the South China Sea

201

It can be seen from the figure that after considering the effects of the tidal forcing and eddy forcing, the vertical velocity is significantly enhanced in the steep topography near the western boundary of the basin and the Luzon Strait. According to the tidal mixing parameterization and eddy-induced mixing parameterization schemes in the article, the energy of tide and mesoscale eddies is mainly used to increase the gravitational potential energy of water bodies. The equivalent vertical velocity is always upward, and the induced circulation is in a cyclonic direction. Therefore, tidal mixing and eddy-induced mixing play the role of strengthening cyclonic circulation. Based on the above model, the spatial distribution of the circulation at the bottom of the South China Sea can be calculated (Fig. 4.26e). The basic flow pattern is similar to Fig. 4.25e. It can be seen from Fig. 4.26 that the 2400–4200 m isobaths of the South China Sea are all cyclonic circulations. The red vector in Fig. 4.26e is the bottom-layer observed velocity of the three stations in the South China Sea. Among them, the bottom velocities of the two observation stations (C01 and E07 observation stations) near the Luzon Strait are obtained from the “2008 National 863 Standardized Offshore Experiment”. For details, please refer to the doctoral dissertation by Xie (2009). They are 0.09 and 0.13 m/s, and the corresponding mode flow rates are 0.06 and 0.11 m/s, respectively. An observation value in the inner area of the South China Sea Basin comes from a continuous station 20 m from the bottom in the 2006 South China Sea Branch of the State Oceanic Administration. The velocity of the residual current is about 0.04 m/s, which corresponds to flow rate of the mode is 0.02 m/s. The direction is roughly along the direction of the isobath.

e 24oN

o 21 N

0.1m/s

o 18 N

15oN

12oN

9oN o 111 E

114oE

117oE

120oE

123oE

Fig. 4.26 The spatial distribution of the total forcing affected by tides and mesoscale eddies and the corresponding bottom flow field (Xiao al. 2013); a 2400 m; b 2800 m; c 3200 m; d 3600 m. The red vector is the measured flow velocity)

202

4.2.3.7

4 Middle and Deep Waters Mass and Circulation …

Conclusion

In this section, a diagnostic model of the bottom circulation of the South China Sea is constructed considering the influence of topography, mesoscale eddies and tides. The model adds dynamic constraint factors such as the bottom Ekman layer, thermal wind relationship, volume conservation, tides, and mesoscale eddies. Starting from the scale analysis, the applicability of the model is analyzed, and the model has a certain practicability. The following conclusion is drawn: the flow field at the bottom of the South China Sea is a cyclonic circulation. Tidal mixing and eddyinduced mixing increase the intensity of cyclonic circulation. The speed has a close relationship with the slope of the topography, that is, the area with a larger slope of the topography has a larger flow velocity.

4.3 Deep Meridional Overturning Circulation in the South China Sea The Luzon Strait (2500 m depth) is the only deep channel between the South China Sea and the Pacific. Its flux and current structure have a significant impact on the South China Sea deep circulation and meridional overturning circulation. Water mass analysis shows that the nature of the water mass deeper than 2000 m in the South China Sea is similar to that of the deep-water mass of the North Pacific Ocean 2000 m east of the Philippine Sea on the east side of the Luzon Strait (Nitani 1972; Broecker et al. 1986). The density of the deep water of the South China Sea is significantly lower than that of the deep water of the North Pacific due to mixing and change. The pressure difference caused by the difference in the density of the deep water on both sides of the Luzon Strait will drive the deep water of the North Pacific to invade the South China Sea, forming a “overflow” in the Luzon Strait (Qu et al. 2006b). The flux of the “overflow” in the Luzon Strait into the South China Sea is 0.7–2.5 Sv (Wang 1986; Liu and Liu 1988; Qu et al. 2006b; Tian et al. 2006; Yang et al. 2010, 2011; Chang et al. 2010; Zhou et al. 2014). The latest understanding of the deep circulation of the Luzon Strait is: the deep pressure difference between the two sides of the Luzon Strait drives about 0.8 Sv of the deep water of the North Pacific to cross the sill of the Luzon Strait to form the “overflow” of the Luzon Strait, and then the “overflow” along the main axis of the Luzon Strait channel flows to the Luzon Trench, and finally mainly flows from the western gap of the Luzon Trench to the inner basin of the South China Sea (Tian and Qu 2012; Zhao et al. 2014a, b; Zhou et al. 2014). Under the influence of the net flux “sandwich” structure of the Luzon Strait and the deep mixing of the South China Sea, the meridional overturning circulation in the South China Sea may have the following structure: in the upper layer of the Luzon Strait, the tropical Pacific subsurface water flows into the South China Sea, forming South China Sea throughflow (Qu et al. 2005; 2006a; Wang et al. 2006; Yu

4.3 Deep Meridional Overturning Circulation in the South China Sea

203

et al. 2007), while the deep waters of pacific ocean in the Luzon Strait flows into the South China Sea, uplifts in the southern South China Sea, driving the formation of the South China Sea deep overturning circulation (Qu et al. 2006a; Liu et al. 2008; Fang et al. 2009). The deep waters of the Pacific and subsurface waters mix in the South China Sea and flow out from the middle layer of the Luzon Strait to form the meridional overturning circulation in the middle of the South China Sea. The “sandwich” structure of the meridional overturning circulation in the South China Sea is mutually configured with the upper cyclonic circulation, middle anticyclonic circulation and deep cyclonic circulation in the South China Sea, forming a very complicated circulation dynamical system. Wang et al. (2004) simulated the upper meridional overturning circulation in the South China Sea in winter and summer under the ideal flat-bottomed seafloor under the conditions of closed boundary and open boundary, using a rigid-lid approximate ocean circulation model under the z coordinate. The simulation results show that the range of the Kuroshio affecting the meridional overturning circulation in the South China Sea can reach about 10° N, which drives the formation of an unclosed meridional overturning circulation in the South China Sea. In winter (summer), seawater is transported from north to south from about 500 m (200 m), and gradually rises, returning to the north at the surface. This meridional overturning circulation describes the movement path of the middle and subsurface waters in the South China Sea. Zhang et al. (2014) found that there is a clockwise overturning circulation below 400 m in the South China Sea. This overturning circulation sinks in the northern part of the South China Sea, moves southward in the subsurface layer, rises in the southern South China Sea, and then moves northward in the surface layer. Among them, the northward movement of the surface layer is mainly related to the zonal wind in the South China Sea basin, and the sinking in the north and the ventilation process in the northern part of the South China Sea. However, the uplift in the south is mainly related to the summer upwelling in central Vietnam induced by Ekman and the local upward movement outside the Vietnam. Fang et al. (2009) used MOM2 model simulation results to show that the westward net flux of Pacific subsurface water intruding into the South China Sea in the upper layer of the Luzon Strait is 5 Sv, forming the South China Sea throughflow, while in the deep layer of the Luzon Strait, the Pacific deep water invades the South China Sea westward and net flux is 0.31 Sv. The subsurface water of the Pacific Ocean mixes the middle waters of the South China Sea in the middle layer and and flow out of the South China Sea from the middle of the Luzon Strait and the net flux is 0.56 Sv. This “sandwich” transport structure in the Luzon Strait will drive the unclosed South China Sea meridional overturning circulation to form. Liu et al. (2008) used SODA data to calculate the multi-year average meridional overturning current streamfunction, and found that the meridional overturning circulation in the middle and upper layers of the South China Sea is similar to the results of Wang et al. (2004). At the same time, the deep and bottom meridional overturning circulations in the South China Sea are also unclosed. The “overflow” of the Luzon Strait moves south along the bottom of the South China Sea and it is raised due to the elevation of the topography near the southern part of the South China Sea. One part flow out

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4 Middle and Deep Waters Mass and Circulation …

of the Karimata Strait, and the other part merges with the subsurface water of the Pacific Ocean invaded by the Luzon Strait, then returns to the surface and enters the South China Sea surface circulation. Liu et al. (2012) further used the temperature and salinity observation data of the South China Sea for many years and found that the middle waters of the South China Sea were lighter than that in the 1960s and 1980s, which is related to the weakening of the deep overturning circulation in the South China Sea.

4.3.1 South China Sea Meridional Overturning Circulation Streamfunction Simulated by Multiple Models Figure 4.27 shows the annual average South China Sea overturning circulation streamfunction derived from each model. Compared with the assimilated SODA data, Xiao et al. (2013) found that the meridional overturning circulation streamfunction shallower than 1000 m in each model are more consistent, that is, there is an anticyclonic center at 8°–18° N and an anticyclonic center at 20°–22° N. Cyclone center corresponds to the invasion of Kuroshio, which is more consistent with the research results of Liu et al. (2008). But for depths below 1500 m, there are big differences in the spatial distribution and size of the meridional overturning circulation streamfunction of each mode. Compared with the meridional overturning circulation streamfunction of the GDEMv3 below 2400 m, the anticyclonic structure is only found in the 5 modes of HYCOM, BRAN, ECCO2, OFES and OCCAM, but they are all weaker. The JPL-R model shows the anticyclonic structure at 10°–12° N, while the cyclonic and anticyclonic structures appear at 12°–18° N. The deep meridional overturning circulations in the South China Sea derived from the above models are quite different. The difference in the meridional overturning circulation structure in the deep layers of the South China Sea reflects the difference in the process of overturning of deep water in the Pacific Ocean after entering the South China Sea.

4.3.2 Diagnostic Analysis of Meridional Overturning Circulation in the South China Sea Based on TRACMASS Shu et al. (2014) used the Lagrangian particle tracking method to study the structural characteristics of the meridional overturning circulation in the South China Sea, and gave the main regional distribution areas of deep water rising in the South China Sea. The Lagrangian particle tracking program TRACMASS is developed by Döös. TRACMASS uses Euler’s velocity field to calculate the position of Lagrangian particles (Döös 1995; Döös et al. 2008). The tracer particles (water mass) can be integrated forward or backward over time, which represents the net transport into

4.3 Deep Meridional Overturning Circulation in the South China Sea

205

Fig. 4.27 Annual average meridional overturning circulation streamfunction Xie et al. (2013a, b). a GDEMv3; b SODA; c ECCO2; d OCCAM; e HYCOM; f JPL-R; g LICOM; h OFES; i BRAN

or out of any grid. The meridional overturning circulation streamfunction can be obtained by integrating the transport volume in the zonal and vertical directions. When enough particles are released, the Lagrangian flow function converges to the Euler flow function. The Lagrangian flow function can be written as y

 j,k −  j,k−1 = T j,k =

 i

y

Ti, j,k,n or  j,k −  j−1,k =

n

 i

Ti,z j,k,n (4.39)

n

y

where  j,k is the Lagrangian streamfunction; T j,k is the meridional volume transport y of the zonal integration; Ti, j,k,n and Ti,z j,k,n is the volume transport of the tracer particles in the meridional and vertical directions, respectively; n represents the time step. Correspondingly, the meridional streamfunction in Euler space is defined as xe (y, z) =

z vdz

dx xw

(4.40)

−H

In the formula, (y,z) represents Euler’s meridional streamfunction, and xe and xw represents the east–west boundary respectively.

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4 Middle and Deep Waters Mass and Circulation …

Tracer particles are released from the straits of the South China Sea until they flow out of the South China Sea. At the same time, the transport volume of all tracer particles is summed on each grid, and then divided by the number of particle releases in the strait to get Lagrangian streamfunction. Using the HYCOM (1/12) ° reanalysis data set for 7 years from 2004 to 2010, the Euler meridional overturning stream function (EMSF) and the Lagrange meridional overturning stream function (LMSF) are obtained by repeated cyclic calculations, as shown in Fig. 4.28a, b Shown. Although there are a few differences between LMSF and EMSF, their macrostructure characteristics are the same. The difference between LMSF and EMSF may be caused by the cyclic use of the 2004–2010 HYCOM velocity field when Lagrangian integration. In order to evaluate the error caused by the return of data from 2010 to 2004 during the Lagrangian integration process, the Lagrangian meridional stream function was calculated using the average (climatic) data from 2004 to 2010 (Fig. 4.28c). The results show that the LMSF calculated using climatological data and daily HYCOM GLBa0.08 data is structurally consistent with the EMSF calculated using HYCOM GLBa0.08 data. This shows that using HYCOM GLBa0.08 data repeatedly to calculate the Lagrangian meridional overturning stream function will not affect the study of the meridional overturning circulation (MOC) structure.

Fig. 4.28 Meridional overturning stream function and meridional transport (Shu et al. 2014). a Euler meridional overturning stream function calculated using HYCOM GLBa0.08 data; b Lagrangian meridional overturning stream function calculated using HYCOM GLBa0.08 data; c Lagrangian meridional overturning stream function obtained from the integration of the climatic flow field averaged over many years; d Lagrangian meridional transport; The negative value in a–c represents the clockwise circulation

4.3 Deep Meridional Overturning Circulation in the South China Sea

207

From Fig. 4.28a–c, MOC in the South China Sea is strongest in the upper layer, sinking in the Luzon Strait and rising in the southern part of the South China Sea. Another notable feature of the South China Sea MOC is the “sandwich” structure, which is similar to the three-layer structure of the basin-scale South China Sea circulation and the three-layer structure of the Luzon Strait inflow: a strong clockwise MOC appears at a shallower than 500 m. The water sinks at north of 18° N and then gradually rises from north to south. The weak counterclockwise MOC structure appears in the middle layer of 500–1000 m, and its strength gradually weakens from south to north; the third layer of the “sandwich” is clockwise and located at a depth of 1000 m or more. The deep clockwise MOC is divided into three celld: deep southern meridional overturning circulation (DSMOC), deep middle meridional overturning circulation (DMMOC) and deep northern meridional overturning circulation (DNMOC). It should be noted that since the depth of the Luzon Strait exceeds 2000 m, DNMOC is not closed at the Luzon Strait. The MOC structure of the three cells in the deep South China Sea shows that the deep South China sea water that sinks in the northern part of the South China Sea not only rises in the south, but also the south side of each MOC is also a rising area. The zonal integral Lagrangian meridional volumetric transport [Eq. (4.39)] intuitively characterizes the three-layer structure of the meridional transport of Pacific water intruding through the Luzon Strait in the South China Sea, that is, the upper and deep layers are transported to the south, and the middle layer is transported to the north, which is consistent with the “sandwich” structure of the South China Sea MOC (Fig. 4.28d). The Lagrangian overturning stream function can be decomposed into partial stream functions to describe the contribution of different water mass to the MOC (Döös et al. 2008). Figure 4.29 describes the contribution of different strait inflows to the South China Sea MOC. The structures in Figs. 4.29a and 4.38a–c are similar, indicating that the inflow of the Luzon Strait dominates the MOC structure in the South China Sea. This is understandable because the inflow into the Luzon Strait (using HYCOM data, the outflow part is not considered, only the inflow part is considered) is 16.19 Sv, which is much larger than the inflow from the other three straits. That is, the contribution of the inflow from the other three straits to the MOC in the South China Sea is relatively small (Fig. 4.29b–d). Similarly, Fig. 4.30 reveals the contribution of different depths of the Luzon Strait inflow to the meridional overturning circulation of the South China Sea. The upper inflow of the Luzon Strait dominates the upper and middle layers of the “sandwich” structure of the meridional overturning circulation in the South China Sea. Moreover, the upper inflow of the Luzon Strait also contributes a lot to the deep meridional overturning circulation in the South China Sea, which is about 0.5 Sv. The contribution of the middle-level inflow of the Luzon Strait to the upper MOC is about 1 Sv, and the contribution to the deep MOC is about 0.2 Sv (Fig. 4.30). This shows that although the net transport in the middle layer of the Luzon Strait is outflow, the inflow from this layer also has a considerable effect on the South China Sea MOC. The impact of the deep inflow of the Luzon Strait on the deep MOC is mainly manifested in DNMOC, but its contribution to DSMOC and DMMOC is very limited.

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4 Middle and Deep Waters Mass and Circulation …

Fig. 4.29 The contribution of different strait inflow to the South China Sea MOC (Shu et al. 2014); a Luzon Strait; b Taiwan Strait; c Karimata Strait; d Mindoro Strait

Figure 4.31 represents the change of the normalized proportion of tracer particles trapped in the South China Sea over time. In Fig. 4.31a, the particles are released from different depths in the Luzon Strait, while the particles in Fig. 4.31b are released from the horizontal plane at different depths in the South China Sea. For comparison, the exponential decay curves with theoretical time scales of 12 and 21 years are also plotted in the figure. Figure 4.31a shows that the average residence time of the inflowing water from the Luzon Strait in the South China Sea is about less than 12 years. Moreover, the average residence time of the deep inflow water is slightly shorter than the average residence time of the middle and upper inflow water. The reason may be that after the deep inflow of the Luzon Strait sinks in the west and south of the strait, a large part of it will rise in the north (Fig. 4.30d). Part of the inflowing water from the upper and middle levels of the Luzon Strait will mix into the Deep South (Fig. 4.30b, c). Qu et al. (2006b) divided the volume of the basin below 1500 m in the South China Sea by the net deep transport volume (2.5 Sv) of the Luzon Strait, and estimated that the renewal time of the deep water in the South China Sea is about 24 years. This calculation means that all the deep waters of the

4.3 Deep Meridional Overturning Circulation in the South China Sea

209

Fig. 4.30 Contributions of different layer inflows through the Luzon Strait to Lagrangian meridional overturning stream function (units: Sv) (Shu et al. 2014): a the total inflow, b the upper layer inflow, c the middle layer inflow, and d the deep layer inflow

South China Sea come from the deep net inflow of the Luzon Strait. However, as shown in Fig. 4.30, the source of deep water in the South China Sea revealed by HYCOM reanalysis data is not limited to the deep inflow of the Luzon Strait. It is worth noting that the 12-year time scale does not equal the residence time of the deep waters of the South China Sea in the South China Sea. Strictly speaking, it represents the average residence time of the invading North Pacific water in the South China Sea. In addition, as shown in Fig. 4.31b, after particles are released from horizontal planes at different depths in the South China Sea, it takes approximately 21 years for the 3000 m deep water to leave the South China Sea, which is similar to the estimation result of Qu et al. (2006b). The formation of deep water is an important factor related to MOC (Stommel and Arons 1960a; b). Due to its location at low latitudes, the South China Sea cannot produce deep water on its own (Xie et al. 2013a, b). The “overflow” in the Luzon Strait is considered the only source of deep water in the South China Sea (Qu et al. 2006b). Moreover, this “overflow” drives the deep cyclonic circulation in the South China Sea and the deep clockwise meridional overturning circulation (Yuan 2002). However,

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4 Middle and Deep Waters Mass and Circulation …

Fig. 4.31 Normalized number of tracer particles staying in the South China Sea (Shu et al. 2014). The black solid lines in (a) and (b) represent the exponential decay curves with theoretical time scales of 12 and 21 years, respectively

the above research results further indicate that the third layer of the South China Sea MOC “sandwich” structure is divided into three cells, and the deep inflow into the Luzon Strait mainly contributes to DNMOC (Fig. 4.30d). In addition, the upper inflow of the Luzon Strait also has a greater impact on the deep MOC circulation structure in the South China Sea, especially DMMOC and DSMOC (Fig. 4.30b). This means that the formation of deep water in the South China Sea is the result of vertical mixing of the entire South China Sea basin. Although the vertical mixing cannot be obtained directly from the HYCOM glba0.08 data, it can be reflected in the tracer particle trajectory simulated by the Lagrangian method to a certain extent. Count the rising (positive) and sinking (negative) particles on each horizontal grid, and then divide by the number of released particles to obtain the average distribution of the upward and downward movement of the tracer particles at a depth of 2000 m (Fig. 4.32). The average downward movement of the tracer particles in the northwestern part of Luzon represents the “overflow” in the Luzon Strait. However, there is a strong rising center at 18.5° N, 119.5° E, which corresponds to the rising part of DNMOC. In addition, at the edge of the ocean basin, that is, the ascending motion of the tracer particles is strong on the 3000 m isobath. In addition, there seem to be three belt-shaped areas sloping from northeast to southwest (the red arrow in Fig. 4.32), and the upward movement is relatively strong in these three belt-shaped areas. There is a strong sinking motion between these three bands. The bands create the interleaving sinking and upwelling zones that constitute the three cells of deep SCS MOC shown in Fig. 4.28. It is worth noting that in addition to the three northeast-southwest sloping belts, the upward movement along the 3000 m isobath of the western basin is also very strong, especially in the east of the Zhongsha Islands (Fig. 4.32). These intensified upwelling areas can be explained by the interaction between topographically trapped waves on the slope and Rossby waves (Rhines 1970; Anderson and Gill 1975; Liu et al. 1999a, 1999b; Wang et al. 2003). Perturbations in the upper ocean (e.g., transitions of the seasonally reversed monsoon, typhoons) can produce topographically trapped waves, which propagate cyclonically along the steep continental slopes in the SCS.

4.3 Deep Meridional Overturning Circulation in the South China Sea

211

Fig. 4.32 Distribution of ensemble-averaged, net number of rising (positive) and sinking (negative) trajectories in each model grid at the 2000 m depth (Shu et al. 2014). Three boxes represent the three deep MOC cells of DNMOC, DMMOC, and SDMOC. The three arrows highlight the three upwelling zones at 2000 m depth, and L represents the middle upwelling zone, the middle red arrow

The slope-trapped waves tend to excite Rossby waves at the eastern boundary. As the Rossby waves arrive at the western boundary, part of their energy is dissipated by the friction; part is reflected as short Rossby waves to be dissipated quickly, which in turn enhances the western boundary current; the remaining energy could excite the slope-trapped waves. The westward planetary Rossby waves are demonstrated clearly by the phase diagrams of the density anomaly shown in Fig. 4.33. The westward propagating signals are prominent at all three depths of 1000, 2000, and 3000 m. Moreover, they have almost the same phase and intensity. It takes about 3 months for these signals to propagate from the east to the west with the speed of about 5.5 cm/s that is close to the propagation speed of the first-mode baroclinic Rossby wave in the SCS. The cyclonically propagating waves on the slope can be seen from the phase diagram of the density anomaly at 3000 m depth along the 3500 m isobaths (Fig. 4.34a). There are two kinds of topographically trapped waves on the northern slope from the west of Luzon Strait to the north of Zhongsha Islands: fast moving ones at about 26 cm/s (dotted arrow) and slow moving ones at about 7.6 cm/s (solid arrow). What is discussed above is one possible mechanism of the SCS MOC such that the Luzon Strait overflow upwells along the continental slope and the three tracks across the basin via interactions between counterclockwise slope-trapped waves and the westward planetary Rossby waves. Many details still need to be addressed in

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4 Middle and Deep Waters Mass and Circulation …

Fig. 4.33 Time series of density anomaly along the line L at depths of a 1000, b 2000, and c 3000 m, respectively

future studies. For example, ➀ Is there a discernable dispersion relation for the slopetrapped waves? ➁ Do the slope-trapped waves conform to the wave solution of Rhine (1970)? ➂ What determine the specific regions along the eastern boundary where Rossby waves are emanated? ➃ What drive the interannual variation of the westward Rossby waves? Moreover, there might be some other possible driving mechanisms for vertical exchanges, which are excluded from the HYCOM reanalysis data, e.g., the mixing induced by tide and internal waves especially when they encounter abrupt topography. Of course, in the case of very limited observational data, the error of the adopted HYCOM reanalysis data may also cause certain uncertainty in the above results.

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Fig. 4.34 Time series of density anomaly (unit: kg/m3 ) at a 3000 m depth along the 3500 m isobath and at b 2000 m depth along the 3000 m isobath (Shu et al. 2014). In the Figure a, the left side of the plumb line represents the part from the starting point along the 3500 m isobath to the Xisha Islands, and the right side represents the remaining part

4.3.3 High-Frequency Variability of the Deep Meridional Overturning Circulation in the South China Sea 4.3.3.1

Features in Daily Output Data

Figure 4.35 is a typical spatial distribution diagram of the MOC difference between two adjacent days in the daily output data of LICOM and HYCOM modes. It can be seen that the daily output data of the LICOM and HYCOM modes show that the spatial distribution of the high-frequency changes of SCSMOC is alternating positive and negative in the meridian direction and dominated by a single cell in the vertical direction. This unity in the vertical direction mainly represents the first baroclinic mode of the ocean, while the alternating distribution in the meridian direction indicates that this may be a kind of fluctuation. Figure 4.36a shows the first 9 modes after decomposition of the empirical orthogonal function (EOF) of MOC deviation in HYCOM. Their explained variances are: 19.95, 12.26, 8.52, 8.24, 7, 5.53, 4.63, 3.87, 3.59%. As can be seen from Fig. 4.36a, the second to ninth modes all show alternating positive and negative changes. From the time coefficient spectrum analysis diagram of the 9 modes (Fig. 4.36b), it can be seen that there are 1–3d periods that pass the 95% confidence test in all 9 modes. Figure 4.37a shows the first 9 modes after the EOF decomposition of MOC deviation in LICOM. Their explained variances are respectively: 24.85%, 16.01%, 12.51%,

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Fig. 4.35 The typical spatial distribution of the MOC difference between two adjacent days in the daily output data of LICOM and HYCOM modes Xiao (2016)

Fig. 4.36 The spatial distribution of the EOF of the MOC deviation in HYCOM and the spectral analysis of the time coefficient (Xiao 2016)

9.92%, 7.36%, 4.76%, 3.43%, 2.59%, 2.07%. As can be seen from Fig. 4.37a, the 2nd to 9th modes all show positive and negative alternate changes. From the time coefficient spectrum analysis diagram of the 9 modes (Fig. 4.37b), it can also be seen that there is 1–3d periods that pass the 95% confidence test in all 9 modes. Comparing Fig. 4.36 with Fig. 4.37, it can be found that the two modes have similar changes in spatial distribution and have similar periods.

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Fig. 4.37 The spatial distribution of the deviation of MOC in LICOM and the spectral analysis of the time coefficient after EOF decomposition Xiao (2016)

Fig. 4.38 Climatic SCSMOC in daily output data (GLBa0.08) and three-hour output data (GLBu0.08) of HYCOM Xiao et al. (2016)

4.3.3.2

Features in HYCOM Three-Hour Mode Output Data

(1) Data verification Figure 4.38 shows the average South China Sea meridional overturning stream function from 2004 to 2010 based on HYCOM daily output data (GLBa0.08) and threehour output data (GLBu0.08). GLBa0.08 is driven by NOGAPS, and the driving field of GLB0.08 is CFSR (climate forecast system reanalysis). It can be seen from Fig. 4.38 that both models have a meridional overturning circulation circle with upper semi-closed clockwise, middle counterclockwise and deep clockwise. The main difference is that the flow field of the middle circulation circle obtained by GLBu0.08 is stronger, the upper circulation circle can reach a deeper depth, and the deep circulation circle obtained by GLBa0.08 can extend to lower latitudes.

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Fig. 4.39 HYCOM three-hour output data and current meter’s zonal velocity a and meridional velocity b power spectrum analysis (Xiao et al. 2016). The red line in the figure is the local nearinertia period, the black line is the result of the measured data, the blue line is the result of the model, and the dashed line is the 95% confidence test

Compared with the daily output of GLBa0.08, the three-hour output of GLB0.08 is more conducive to the study of high-frequency motions in a few days. Therefore, this section selects 2010 GLB0.08 to analyze the near-inertial variation characteristics of the meridional overturning circulation in the South China Sea. Figure 4.39 shows the power spectrum of the zonal and meridional velocity of the three-hour output data of HYCOM and the measured data of the mooring current meter. The mooring points are located at 17.99° N, 114.57° E. The current meter is placed 300 m above the bottom. The sampling time is from March 21 to September 19, 2006, and the sampling interval is 1 h. The 120d model data and observation data since April 1, 2006 are used in the research of this section. It can be seen from Fig. 4.39 that there are inertial oscillations in the model output data and the zonal and meridional velocities observed by the current meter. Both observations and model data show that the period of this oscillation is slightly smaller than the local near-inertial oscillation). Based on the above analysis, it can be seen that the three-hour output data of HYCOM has a certain degree of credibility and can be used for high-frequency oscillation studies of meridional overturning in the South China Sea. (2) Spectral characteristics Figure 4.40 shows the 14° N 1500 m depth SCSMOC time series from January to April 2010 and the wavelet power spectrum and Fourier power spectrum of the sequence. It can be seen from the SCSMOC time series that there is an obvious intraseasonal change and persistent high-frequency fluctuations in the series. The wavelet analysis of the sequence shows that there is a full-time period of 1–3d and an intraseasonal period of 16–32d. The Fourier power spectrum further confirms that the sequence has a significant 1–3d period. Figure 4.41 shows the power spectrum of the SCSMOC at a depth of 1500 m at different latitudes in January 2010. There are significant periods of 1–3 d at different latitudes. Figure 4.42 shows the power

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Fig. 4.40 SCSMOC time series a and wavelet power spectrum b and Fourier power spectrum c of the sequence at 14° N 1500 m from January to April 2010 Xiao et al. (2016). In c, the red line is the local near-inertia period, and the dashed line is the 95% confidence test

spectrum of the SCSMOC at different depths at 14° N in January 2010. There are significant periods of 1 to 3 d at different depths. Figure 4.43 shows the power spectrum of the SCSMOC in different seasons at 14° N and 1500 m depth in 2006. It can be seen from Fig. 4.43 that there are significant periods of 1–3 days in different seasons. The period of this oscillation is slightly lower than the local near-inertia period. It can be seen that this kind of near-inertial oscillation has always existed in this set of data. Figure 4.44 shows the period corresponding to the peak of the power spectrum in the SCSMOC time series and its ratio to the period of local inertia. Towards the equator, the period corresponding to the peak of the power spectrum in the SCSMOC time series becomes longer, and the period is 1d at 20° N. The period is 2.5d at 10° N. The near inertial zone of the South China Sea is 10°–20° N, and its periods correspond to 3.59d and 1.46d, respectively (Chen et al. 2014). From the ratio of the period corresponding to the peak of the power spectrum in the SCSMOC time series to the local inertial period of the South China Sea, it can be seen that the period of the deep meridional overturning circulation in the South China Sea is smaller than the period of local inertia, while the shallow meridional overturning circulation period of the South China Sea is related to the local inertial period. However, at 8°–10° N, the near-inertial period of the meridional overturning circulation in the South China Sea is greater than the local inertial period. (3) Spatial structure characteristics In order to extract the near-inertial signal of the meridional overturning circulation in the South China Sea, the Butterworth filter is used to filter the time series of the meridional overturning circulation in the South China Sea at each latitude and depth.

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Fig. 4.41 Power spectrum analysis of the SCSMOC sequence at a depth of 1500 m at different latitudes in January 2010 Xiao (2016). The red dotted line in the figure is the local near-inertial period, and the dotted line is the 95% confidence test

The frequency is set to [0.33, 1] cpd, which is consistent with the period of 1–3d. Figure 4.45 shows the standard deviation of SCSMOC and the standard deviation of 1–3d signal in the three-hour output data of HYCOM mode. Figure 4.45b shows that the maximum standard deviation of the filtered signal of the meridional overturned circulation in the South China Sea is nearly 4 Sv, which is half of the maximum standard deviation of the meridional overturned circulation in the South China Sea in 2010 in Fig. 4.45a. There is the largest near-inertial signal of the meridional overturning circulation in the South China Sea at the 500–2500 m layer. 16°–20° N in the north and 12°–14° N in the south are the centers of two high standard deviations, and there is a maximum value of the change of the shallow meridional overturning circulation in the South China Sea at about 20° N near the Luzon Strait, which is located in the 100–500 m layer. In Fig. 4.45b, the near-inertial change mode of the meridional overturning circulation in the South China Sea is very similar to the change modes of the Pacific and Atlantic (Komori et al. 2008; Blaker et al. 2012; Sévellec et al. 2013). For example, the near-inertial variability of the meridional overturning circulation in the Atlantic Ocean appears at 10°–40° N, and there is an obvious high-value center at a depth of 500–4000 m, indicating that the near-inertial wave activity in this area is relatively strong.

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Fig. 4.42 Power spectrum analysis of SCSMOC sequence at different depths at 14° N in January 2010 Xiao (2016). The red line in the figure is the local near-inertia period, and the dashed line is the 95% confidence test

It can be clearly seen from Fig. 4.46a that the vertical meridional velocity field integrated from the seabed to 1000 m has regular positive and negative alternating phenomena. Further use the Butterworth filter to obtain the SCSMOC anomaly (Fig. 4.46b), and it can be seen that there is a regular positive and negative alternation phenomenon in the SCSMOC anomaly, with a maximum amplitude of 5 Sv. Most circulation circles are concentrated at 10°–20° N, and the depth is between 1000 and 3000 m. In the upper ocean, the circulation circle is not obvious. These circulation circles are stretched in the vertical direction instead of in the meridional direction, indicating that each circulation circle contains strong upwelling branches and downwelling branches. 4°–10° N and 20°–22° N also have weak circulation circles. Predecessors used high-resolution models to simulate upwelling and downwelling in the middle layers of open seas (such as the Atlantic Ocean and the Pacific Ocean) (Komori et al. 2008; Von Storch 2010). (4) Propagation characteristics In order to study the meridional propagation of the near-inertial signal at the depth of 500–2500 m in the meridional overturning circulation in the South China Sea,

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Fig. 4.43 Power spectrum analysis of the SCSMOC sequence at a depth of 14° N 1500 m in January, April, July and November 2006 Xiao (2016). The red line in the figure is the local near-inertia period, and the dashed line is the 95% confidence test

Fig. 4.44 The period corresponding to the power spectrum peak in the SCSMOC time series a and its ratio to the local inertia period b Xiao et al. (2016)

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Fig. 4.45 The standard deviation of SCSMOC a and the standard deviation of 1–3d signal b in the output data of HYCOM mode every three hours Xiao et al. (2016)

Fig. 4.46 The vertical meridional velocity a and SCSMOC anomaly b from the seabed to the 1000 m integral at 24:00 on January 15, 2010 (Xiao et al. 2016)

Fig. 4.47 shows the meridional structure of the filtered near-inertial signal at a depth of 1500 m in the four typical months (January, April, July and October). It can be seen from Fig. 4.47 that in these different months, most of the signals are propagated from the Luzon Strait, and the propagation speed is 1–3 m/s. Near-inertial gravity waves are usually close to the Coriolis frequency and propagate southward due to the β dispersion effect (Anderson and Gill 1979; Garrett 2001). Figure 4.48 shows the vertical propagation of near-inertial signals filtered at 14° N in the four typical months (January, April, July, and October). It can be seen that the SCSMOC anomaly does not have a significant vertical tilt in the vertical direction, and appears to be single cell distribution. According to the definition of the meridional overturning stream function, this indicates that the upper and lower flow velocity are

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Fig. 4.47 The meridional propagation of SCSMOC anomalies in the 1500 m layer in January a, April b, July c and October d 2010 (Xiao et al. 2016)

reversed, so the near-inertial signal of SCSMOC is dominated by the first baroclinic mode in the vertical direction. (5) Possible energy source Figure 4.49 shows the monthly average wind-induced near-inertial energy flux in January, April, July and October 2010. It can be seen that the near-inertial energy flux caused by wind produces the largest energy on the west side of the Luzon Strait (Li et al. 2015). In spring, strong high-frequency winds excite near-inertial gravity waves in the Luzon Strait. In addition, on average, about 7 typhoons enter the South China Sea from the Northwest Pacific through the Luzon Strait (Wang et al. 2007; Ling et al. 2015) each year. Taking 2010 as an example, there were two typhoons in July and one typhoon in October entered the western side of the Luzon Strait. Typhoons can input a large amount of near-inertial energy flux into the ocean (Figure 4.49c, d), so the Northwest Pacific typhoon passing through the Luzon Strait can also drive near-inertial gravity waves. The horizontal distribution of the average near inertial energy from the bottom integral to 1000 m is basically consistent with the near inertial energy input of the wind field (Figs. 4.49 and 4.50), which shows the important role of the wind field on the SCSMOC near inertial disturbance. In

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Fig. 4.48 The vertical propagation of SCSMOC anomalies in January a, April b, July c and October d at 14° N in 2010 (Xiao 2016)

addition, the Kuroshio usually forms a strong density front in the Luzon Strait (Wang et al. 2001a, b), which induces the formation of a positive vorticity zone in the west of the Kuroshio and a negative vorticity zone to the east of the Kuroshio. On the one hand, frontal disturbances (Kuroshio) can trigger near-inertial gravity waves through geostrophic adjustment (Kunze 1985; Wang et al. 2009; Whitt and Thomas 2013). On the other hand, the existence of the negative vorticity field is conducive to the propagation of near-inertial energy to the deep sea (Lee and Niiler 1998; Zhai et al. 2005). When the near-inertial gravity wave leaves the density front, due to the β dispersion effect, the near-inertial energy will propagate to the equator (Anderson and Gill 1979; Garrett 2001). Therefore, the strong near-inertial gravity wave energy near the Luzon Strait was found in the high-frequency variability of the deep meridional overturning circulation in the South China Sea from the southwest of the Luzon Strait to 10° N.

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Fig. 4.49 The spatial distribution of near-inertial energy input in January a April b July c and October d of 2010 Xiao et al. (2016). The black line is the best typhoon path issued by JTWC (Joint Typhoon Warning Center)

4.4 Summary and Outlook In this chapter, we review the distribution characteristics of the midwater in the South China Sea and its correlation with water exchange in the Luzon Strait. In this chapter, the distribution characteristics of the midwater in the South China Sea and its correlation with the water exchange in the Luzon Strait are reviewed, and the distribution characteristics of the midwater in the South China Sea are analyzed from the perspective of the meridional overturning circulation. The results show that there is a significant interannual and interdecadal variation of the midwater in the South China Sea. In the case of the East China Sea mid-level detachment flow in autumn, the POM model is used to reproduce the detachment flow, and it is pointed out that the negative center of the joint effect of oblique pressure topography (JEBAR) is the key factor driving the East China Sea mid-level flow. The basic characteristics of the deep and bottom circulation in the South China Sea are analyzed, and it is pointed out that the difference of the model topography can obviously cause the change of the circulation intensity, and then a diagnostic model of the bottom current in the South

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Fig. 4.50 The distribution of the average near-inertial energy from the seafloor integral to the 1000 m layer in January a April b July c and October d of 2010 Xiao et al. (2016)

China Sea considering the influence of tides and mesoscale eddies is constructed; in terms of the deep meridional overturning circulation in the South China Sea, the structural characteristics of the meridional overturning circulation (SCSMOC) in the South China Sea are studied based on the HYCOM reanalysis data, and it is considered that the Luzon Strait inlet is the most important driver of the SCSMOC. It is also suggested that the high frequency variability of the wind field near the Luzon Strait plays an important role in the near-inertial variability of the meridional overturning circulation in the South China Sea. Some progress has been made in the research on the mid-deep circulation, but there are still some unresolved issues. (1) At present, the results of studies on deep circulation and meridional overturning circulation in the South China Sea are almost all based on numerical models or diagnostic models, except for the deep circulation in the Luzon Strait, where some observations have been made. (2) The three layers of circulation in the South China Sea are not independent, but are interconnected. However, it is not known how the momentum, eddies, heat and salinity are exchanged among the three circulation layers. The exchange of momentum, eddy, heat and salinity between the three circulation layers is not

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known, and it is not clear how this exchange of material and energy contributes to the maintenance and variability of each. The role of this material-energy exchange on the maintenance and variability of each is also not clear. To solve these problems, in addition to strengthening in situ observations, theoretical considerations of tidal mixing, topography, vertical water exchange, and surface atmospheric pressure are needed. The role of tidal mixing, topography, vertical water exchange, and surface atmospheric pressure in driving the three-layer circulation needs to be considered theoretically in addition to strengthening in situ observations. (3) Using the reflection seismic method to infer the subsurface flow channel of the South China Sea, marine geologists have achieved fruitful research results. Combined with more high-precision reflection seismic data and with the help of finer deep-water sedimentary systems, it is possible to infer the large-scale circulation pattern of the South China Sea in previous years and the small-scale circulation in the inner trough and seamounts of the South China Sea, which can further enhance the understanding of the deep circulation in the modern South China Sea. And understanding of the meridional inversion circulation.

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Chapter 5

Mesoscale Eddy and Mesoscale Process in the South China Sea

The first mesoscale eddy mentioned by scholars in the South China Sea is the cold eddy off the central part of Vietnam in summer (Huang et al. 1992). Xu et al. (1982) gave the climatical (seasonal average) results of the South China Sea such as the winter cyclonic eddy in the northwest of the Luzon Island and the summer anticyclonic eddy off southeastern Vietnam. Zhong (1990) studied multiple cold and warm eddies in the central and northern South China Sea. Li et al. (1997) held that a warm eddy that entered the northern South China Sea was generated by shedding of the Kuroshio intrusion into the South China Sea. In the southern South China Sea, Huang (1994) pointed out, based on the cruise observation, that there are many eddies near the Nansha Island, such as the cyclonic circulation (eddy) in the upper layer of the Nansha Trough in winter and summer. In general, the research on mesoscale eddies in the South China Sea in the twentieth century were mainly based on ship observation, and the contingency was relatively large. However, the characteristics of the multi-eddy structure of the South China Sea have begun to be recognized and highlighted, and a preliminary impression of the complexity of the eddy has also been given. This chapter will conduct statistical analysis of current observation data, describe the characteristics of typical mesoscale eddy, briefly expound the physical and ecological effects of mesoscale eddies, and discuss the energy transfer of mesoscale eddies and near-inertial oscillations induced by typhoons.

5.1 General Characteristics and Individual Case Studies of Mesoscale Eddies in the South China Sea The mesoscale eddies in the South China Sea are active (Su 2001; Guan and Yuan 2006), due to background circulation and unstable Kuroshio (Li and Wu 1989; Li et al. 1998; Metzger and Hurlburt 2001; Jia and Liu 2004; Yuan et al. 2006; Gan and Qu 2008), advection transport of vorticity (Wang et al. 2006b), wind stress curl © Science Press and Springer Nature Singapore Pte Ltd. 2022 D. Wang, Ocean Circulation and Air-Sea Interaction in the South China Sea, Springer Oceanography, https://doi.org/10.1007/978-981-19-6262-2_5

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea

(Chi et al. 1998; Yang and Liu 2003; Wang et al. 2008b) and other factors induced. With the increasing availability of hydrological and satellite remote sensing data, the statistics, and individual characteristics of eddies in the South China Sea are gradually being recognized. Combining satellite altimeter data and numerical simulations, the statistical characteristics of the generation, extinction, and evolution of eddies in the South China Sea have been revealed by many researchers (Hwang and Chen 2000; Wang et al. 2003; Chen et al. 2011; Xiu et al. 2010; Lin et al. 2007, 2015). Based on hydrological observations, several cases of eddies have also been reported, such as a cold eddy in the northwest of the Luzon Island in 1998 (Chu and Fan 2001), an anticyclonic eddy in the northeastern South China Sea in 2003/2004 (Wang et al. 2008a), a warm eddy in the southwest of Taiwan Island in 2006 (Zu et al. 2013), a strong warm eddy in the western South China Sea in 2010 (Chu et al. 2014), and a mesoscale eddy dipole in the southwest of Taiwan Island in 2012 (Zhang et al. 2013) and so on. Several eddies with seasonal characteristics have also been reported, such as the Luzon cold eddy that occurs in northwest of the Luzon Island in autumn and winter (Yang and Liu 1998; Shaw et al. 1999; Qu 2002), and the Luzon Warm eddy generated in northwest of the Luzon Island in summer and autumn (Yuan et al. 2007; Wang et al. 2008b, 2012a; Chen et al. 2010a; Jiang and Hu 2010), a warm eddy at section 18° N in the summer and autumn (Nan et al. 2011), the Dongsha cold eddy (Chow et al. 2008), Vietnam eddy dipole (Wu et al. 1999; Wang et al. 2006b; Chen et al. 2010b; Hu et al. 2011), the warm eddy in western South China Sea in the spring (He et al. 2013) and so on.

5.1.1 General Characteristics of Mesoscale Eddies in the South China Sea Based on the altimeter data from October 1992 to October 2009 and using the Winding-angle algorithm, Chen et al. (2011) systematically studied the frequency, radius, period, dynamic properties, and evolution characteristics of eddies in the South China Sea, and he also discussed the seasonal and inter-annual changes of mesoscale eddies and their influence on the Thermocline.

5.1.1.1

Basic Characteristics of Mesoscale Eddy

(1) Generation and occurrence probability of mesoscale eddy From October 1992 to October 2009, a total of 434 anticyclonic eddies (AE) and 393 cyclonic eddies (CE) in the South China Sea were identified and tracked (Chen et al. 2010a, b, 2011). Eddies are mainly generated in the northeast-southwest diagonal of the South China Sea and the southwest of the Luzon Island, but less in the southeast and northwest of the South China Sea (Fig. 5.1). The west of the Luzon Strait is

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a frequent area of mesoscale eddies. The generation of eddies in this area may be related to changes in wind stress curl, instability of the Kuroshio intrusion front (Wang et al. 2000), and the Kuroshio shedding (Li et al. 1998; Wang et al. 2008a), the westward advection of vorticity and the winter monsoon jets (Wang et al. 2008b). Seasonal eddies, such as Luzon cold eddy (Shaw et al. 1999; Qu 2000; Yang and Liu, 2003) and the Luzon warm eddy (Yuan et al. 2007; Chen et al. 2010a), also generated in this area. The east of Vietnam is another eddy-prone area in the South China Sea. Some observational studies have shown that there is a mesoscale eddy dipole in this area during the southwest monsoon (Chen et al. 2010b). The generation of this mesoscale eddy dipole is closely related to the local wind stress curl. In addition, the instability of strong coastal currents is also an important cause in this area. In the southeast of the South China Sea, the number of anticyclonic eddies is twice the number of cyclonic eddies. Cai et al. (2002) pointed out that the interaction between the strong barotropic shelf current and the topography is conducive to the generation of anticyclonic eddies in this area. It is worth noting that during the 17 years from October 1992 to October 2009, only 11 eddies were transported into the South China Sea from the Pacific Ocean. Figure 5.2a shows the spatial distribution of the probability of mesoscale eddy occurrence in the South China Sea. The mesoscale eddies probability is defined as:

22

14

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18

10

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6 108

1 1 1 3 11 3 5 9 11 1 3 2 9 8 13 8 5 5 8 8 5 5 7 3 3 4 3 6 6 8 2 15 9 10 1 2 4 11 3 7 10 4 5 4 11 5 3 12 8 8 2 6 10 9 3 5 1 5 11 2 3 3 13 8 7 10 8 17 13 8 3 3 11 3 5 4 12 2 5 6 5 9 3 4 5 6 13 6 3 4 6 13 4 11 1 5 6 3 4 3 3 1 2 5 5 1 2 11 2 3 6 5 2 2 1 4 112

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CHINA

Ta

iw

an

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Fig. 5.1 The distribution of the number of mesoscale eddies generated in the 1° × 1° area of the South China Sea from October 1992 to October 2009 (Chen et al. 2011)

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea

the proportion of time that a certain area is within the mesoscale eddy during the observation time. It can be found that the variation range of the mesoscale eddy probability in the South China Sea is 0–73%, and the average mesoscale eddy probability is 27%. Mesoscale eddies not only frequently occur in the east of Vietnam, with the mesoscale eddy probability of 40–70%, but also frequently occur in the northeast of the South China Sea, with the mesoscale eddy probability of 35–60%. Larger eddy kinetic energy (EKE) is also located in these two regions (Chen et al. 2009), which should be related to the distribution of the mesoscale eddy probability. Since there are only a few mesoscale eddies generated and propagated in the southeast of the South China Sea, the probability of mesoscale eddy is relatively small. The smallest probability of mesoscale eddy (less than 10%) occurs on the coast of the South China Sea. This is mainly because the mesoscale eddy is difficult to fully develop along the coast, and the data of depths less than 100 m are ignored, so the Winding Angle algorithm cannot capture the closed streamlines. The mesoscale eddy polarity represents the probability that a certain point in the mesoscale eddy is inside the anticyclonic eddy (mesoscale eddy polarity > 0) or inside the cyclonic eddy (mesoscale eddy polarity < 0) (Chaigneau et al. 2009), and the calculation formula is: (FAE − FCE)/(FAE + FCE), where FAE and FCE are the probability that the point is within the anticyclonic eddy and the cyclonic eddy, respectively. Figure 5.2b shows the distribution of the mesoscale eddy polarity in the South China Sea. The most significant polarity is located in the southeast of the South China Sea, although the frequency of mesoscale eddy in this region is low. The other three negative mesoscale eddy polarity regions are in southwest of the Taiwan Island, the 12.5°–16° N and 113.5°–115.5° E regions in the central South China Sea, and the 9.5°–11° N and 110°–112.5° E regions in the southeast of Vietnam. The mesoscale eddy polarity of the area is −15 to −5%. However, (a) Eddy frequency o

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Fig. 5.2 Climatic mesoscale eddy probability and polarity distribution in the South China Sea (Chen et al. 2011)

5.1 General Characteristics and Individual Case Studies …

235

Wang et al. (2003) pointed out that the southwest of the Taiwan Island is mainly occupied by anticyclonic eddies. The inconsistency of the conclusions is because their results mainly focus on longer-lived mesoscale eddies, and therefore ignore more cold eddies. As anticyclonic eddies have longer lifespans, most areas of the South China Sea are occupied by anticyclonic eddies for more time, especially in the 12.5°–15° N and 109°–113° E regions in the east of Vietnam, and 13.5° southwest of the Luzon Island. The ~16° N, 117°–119° E area and the northwest of South China Sea are more obvious, and the mesoscale eddy polarity reaches 20–40%. (2) Size and lifespan of mesoscale eddy The probability density function of the radius of mesoscale eddies in the South China Sea presents a Rayleigh distribution with a peak value of 130 km (Fig. 5.3a). 64% of mesoscale eddies have the radius of 100–200 km; mesoscale eddies with the radius greater than 200 km are fewer, accounting for only 14% of the total. The size of the radius has a certain relationship with the change of latitude, increasing from about 100 km at 21° N to 160 km at 9° N. But as the latitude decreases further, the mesoscale eddy radius gradually decreases to 110 km at 6° N. Chaigneau et al. (2009) studied the mesoscale eddies radii of four upturned regions on the eastern boundary of the world, and pointed out that the radii in these four regions increase in an equatorial direction. This is different from the conclusion that the radius in the South China Sea changes. The smaller radius in the south of the South China Sea may be restricted by the local narrower area and shallower water depth, so the mesoscale eddy cannot be fully developed. Figure 5.3c describes the relationship between the eddy energy density EI = EKE and the eddy radius, where EKE is the eddy kinetic energy and πr 2 r is the eddy radius. The EI decreases as a Gaussian function with the increase of the eddy radius, from 2.5 × 10−2 cm2 /(s2 km2 ) when the eddy radius is 50 km to 2 × 10−3 cm2 /(s2 km2 ) when the eddy radius is 300 km. The mesoscale eddy has a parabolic relationship with the eddy radius, and the maximum vorticity is about 6 × 10−6 s−1 , which corresponds to an eddy with a radius of 170 km. Figure 5.4a shows the lifespan distribution of the tracked 827 mesoscale eddies. The average lifespan is 8.8 weeks (62 days); the anticyclonic eddy has a longer life of 9.3 weeks, and the cyclonic eddy is 8.1 weeks. The cumulative rate distribution shows (red line in Fig. 5.4a) that the number of mesoscale eddies with the lifespan shorter than 10 weeks accounted for 74% of the total, and the number of mesoscale eddies decreased rapidly with the increase of life. The longest-lived mesoscale eddy was an anticyclonic eddy that occurred in east of Vietnam in January 1993. The eddy was active for 48 weeks near the location where it was generated, until it disappeared in December 1993. In mesoscale eddies with a life shorter than 10 weeks, the number of anticyclonic eddies (white histogram in Fig. 5.4a) and cyclonic eddies (gray histogram in Fig. 5.4a) are equal; while for mesoscale eddies with the lifespan longer than 10 weeks, the number of anticyclonic eddies is twice the number of cyclonic eddies, and about 12.5 eddies are generated every week. This is more consistent with the results of Wang et al. (2003), indicating that the difference between the results mentioned above and the results of Wang et al. (2003) is mainly because their research focuses on mesoscale eddies with the longer lifespan

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea (b)

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Fig. 5.3 Variation characteristics of mesoscale eddy parameters with radius (Chen et al. 2011). a Probability density function of eddy radius. b Variation of eddy radius with latitude. c EI change with eddy radius. d Vorticity change with eddy radius

and ignores those with a shorter lifespan. The eddies with a lifespan longer than 31 weeks are all anticyclonic eddies. What is interesting is that when the average life cycle of the mesoscale eddy increases from 4 to 30 weeks, the radius increases from 110 to 150 km accordingly (Fig. 5.4b). This means that the smaller eddy has more concentrated energy (Fig. 5.3c), but has the shorter lifespan. In addition, the length of the eddy lifespan has a certain relationship with the location of the eddy. The eddy produced at 9°–19.5° N has an average life cycle of 8.2–10.7 weeks; while the eddy produced at more north or south has a quasi-linear decline in lifespan. (3) The propagation and evolution of eddies Vector synthesis of the mesoscale eddy propagation velocity from October 1992 to October 2009 on the grid points in the South China Sea, the propagation velocity field of the mesoscale eddy can be obtained (Fig. 5.5). In the northern part of the South China Sea, the eddy mainly propagates along the southwest direction of the continental shelf, with a velocity of 5.0–9.0 cm/s. In the central part of the South China Sea (13°–17° N, 108°–121° E), the eddy propagates in a quasi-westward direction,

5.1 General Characteristics and Individual Case Studies …

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b. Variation of mesoscale eddy lifespan with eddy radius c. Variation of mesoscale eddy lifespan with latitude

Fig. 5.4 Related features of mesoscale eddy life (Chen et al. 2011)

but with slight divergence, with a velocity of 2.0–6.4 cm/s. To the south of 8° N, the eddy mainly propagates in a west or southwest direction, with a propagation rate of 2.0–7.7 cm/s. The South China Sea also has two regions where the eddy propagation velocity is relatively low. One is located on the eastern coast of the South China Sea, and only a few eddies pass through this area. The other is located at 8°–12.5° N and 111°–114° E in the southeast of Vietnam. Although eddies appear frequently in this area, because it is located in the southwestern part of the South China Sea, the eddies generated in this area do not have a uniform propagation direction. In addition, there are fewer eddies on the east side of the area, so few eddies pass by. The above results indicate that the South China Sea mesoscale eddy is not a free Rossby wave, because the first baroclinic mode of the Rossby wave travels in the South China Sea at a speed of about 7.1 cm/s and propagates in a westward direction (Yuan et al. 2007). In order to better understand the propagation characteristics of eddies, mesoscale eddies with the lifespan of more than 5 months (22 weeks) are further studied. These analyses are based on 24 (14) long-lived anticyclonic eddies (cyclonic eddies). Figure 5.6 shows the trajectory of these eddies. In order to facilitate the discussion,

238 Fig. 5.5 Climatic mesoscale eddy propagation velocity field (Chen et al. 2011)

5 Mesoscale Eddy and Mesoscale Process in the South China Sea o

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we divide these eddies into 4 parts according to the place where they are generated. The division of regions is the same as that of Wang et al. (2003). In the Z1 area, 3 of the 4 long-lived eddies are anticyclonic eddies, and these eddies are all produced during the northeast monsoon period, which may be related to the instability of the background flow caused by the Kuroshio intrusion. The mesoscale eddy in this area mainly propagates along the southwest of the continental shelf slope to the southeast of Hainan Island, the propagation distance (straight-line distance from the start point to the end point) is about 778 km, and the propagation speed (average of the weekly Lagrangian rate) is 6.1 cm/s. Most of the anticyclonic eddies in the Z2 area are generated in the northwest of the Luzon Island, while most of the cyclonic eddies in this area are generated in the west of the Luzon Island. Some eddies disappeared on the northern shelf or the Dongsha Islands, and other eddies spread to the west coast. The average propagation distance is 657 km, and the propagation speed is 5.5 cm/s. Most of the long-lived eddies in the Z3 area are produced in the southwest of the Luzon Island. Without the influence of the continental shelf, the anticyclonic eddy and the cyclonic eddy propagate freely, and each shift in the polar or equatorial direction. The propagation distance of the eddy in this area is about 617 km, and the propagation speed is 4.0 cm/s. The overall directionality of eddy propagation in Z4 area is poor, especially in the area south of 12.5° N. The propagation distance of the eddy is relatively small, only 278 km, but the propagation speed is 4.6 cm/s, which is not significantly lower than the propagation speed of the eddy in other regions. This further shows that the low eddy propagation velocity in the central and western basin in Fig. 5.5 is mainly due to the fact that eddies in this area do not have a consistent propagation direction.

5.1 General Characteristics and Individual Case Studies …

239

Fig. 5.6 The propagation trajectory of the mesoscale eddy (Chen et al. 2011). The squares and dots represent the generation and disappearance of these eddies; the red and blue lines represent the propagation paths of anticyclonic eddies and cyclonic eddies, respectively

Due to the β effect, anticyclonic eddies and cyclonic eddies tend to have smaller equatorial and polar deviations, respectively. However, the situation in the South China Sea is somewhat different. In the north of 18° N and south of 13° N, the eddy path is obviously affected by geographical location (Figs. 5.5 and 5.6). In the 13°– 18° N region, the anticyclonic eddy tends to shift northward (polarity) (Fig. 5.7). In the 25th week, it shifted by 1.2 latitudes; the cyclonic eddy continued to travel westward 19 weeks before slight southward (equatorial) shift. Wang et al. (2003) also pointed out that the anticyclonic eddy in this area tends to propagate westward and northwestward. This may have a certain relationship with the circulation structure in the area. This special eddy path divergence also appears in other regions of the world. As stated by Chelton et al. (2007), the global anticyclonic eddy equatorial direction, pure zonal (0 ± 1) and polar deflection accounted for 60% and 9% respectively. And 31%, while cyclonic eddies accounted for 34%, 8%, and 58%, respectively. Using these 38 long life eddies, we further study the evolution characteristics of mesoscale eddis. The eddy radius increased at a rate of 10 km per week in the first 3 weeks, and then the growth rate slowed down to approximately 3 km per week. The eddy began to weaken after 12 weeks of propagation, and the eddy radius decreased at a rate of 2 km per week (Fig. 5.7b). Eddy energy density (EI) dropped by 30% in the first 3 weeks, and then dropped by 15% in the next 8 weeks, with a minimum of 2.196 × 10−6 s−1 . After 12 weeks, EI began to increase, and the rate of increase was only 2/3 of the rate of decline (Fig. 5.7c). In addition, the vorticity changes little during the generation and extinction of the eddy (Fig. 5.7d), which can be regarded as a quasi-conserved quantity.

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea (b) 180

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Fig. 5.7 Average properties of long-lived eddies (Chen et al. 2011)

5.1.1.2

Seasonal and Inter-annual Variation of Mesoscale Eddies and Their Influence on Temperature Distribution

The time variation of the mesoscale eddies discussed below is based on the tracked 434 anticyclonic eddies and 393 cyclonic eddies. Figure 5.8 shows the seasonal variation of the average characteristics of the eddy. It can be found that cyclonic eddy and anticyclonic eddy have different seasonal characteristics. In the four seasons of spring, summer, autumn and winter, the generation rates of cyclones are 26, 17, 24, and 33%, while the generation rates of anticyclonic eddies are 28, 29, 23, and 20%, which means more cyclonic eddies are produced in winter, and more anticyclonic eddies are produced in summer. In fact, the seasonal variation of the number of eddies in the South China Sea is mainly controlled by the seasonal variation of the number of eddies in the Z2 and Z4 regions. In winter, the strong cyclonic wind stress curl (Qu 2000) and the westward advection of vorticity caused by the Kuroshio front are conducive to the generation of eddies in the northwest of the Luzon Island. The interaction between the southward coast of Vietnam and the convex shape of the coast is conducive to the generation of cyclones (Gan and Tang, 2008). In summer,

5.1 General Characteristics and Individual Case Studies … (a) 3

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Fig. 5.8 Seasonal variation of mesoscale eddy properties (Chen et al. 2011)

the northeastward offshore current separated from central Vietnam is conducive to the generation of anticyclonic eddies (Gan and Tang, 2008). The west side of the Pabuyan Islands (located in the Z2 zone) is also a high incidence area of anticyclonic eddies (Metzger and Hurlburt 2001). Similar to the change in the number of eddies, the cyclones with the smallest average eddy radius (118 km) and the shortest average lifespan (6.9 weeks) occur in summer, and the cyclones with the largest average eddy radius and the longest average lifespan appear in winter. The average radius of the winter cyclonic eddy is 127 km, and the average lifespan is 8.6 weeks. Unlike cyclonic eddies, anticyclonic eddies formed in autumn have the smallest average radius and the shortest average lifespan, 121 km and 8.1 weeks, respectively; while anticyclonic eddies appearing in winter have the longest average radius and average lifespan, 125 km and 10.9 weeks. As mentioned earlier, the lifespan of anticyclonic eddies is longer than that of cyclonic eddies, except for October and November (Fig. 5.8c). The EI of the anticyclonic eddy is 37% higher than the average in winter, and lower than the average by 18% in the spring. In the other two seasons, the change is weak, not exceeding 10% (Fig. 5.9d). The EI of the anticyclonic eddy changes half a year, and it is 58% higher in the second half of the year than in the first half of the year. Interestingly, although the long-life eddies in the Z1 region are mainly anticyclonic eddies, there is no significant difference in the number of the two types of eddies in this region. As mentioned earlier, the lifespan of anticyclonic eddies is longer than that of cyclonic eddies. This is mainly due to the longer life of anticyclonic eddies in Z1 and Z4 regions than cyclonic eddies. EKE is much larger in Z1 and Z4 than in Z2 and Z3, and the largest EKE in Z1 and Z4 occurs in winter and summer, respectively.

5 Mesoscale Eddy and Mesoscale Process in the South China Sea 20

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Fig. 5.9 Interannual variation of mesoscale eddy (Chen et al. 2011)

This is consistent with the EKE distribution and change results analyzed by Chen et al. (2009) using altimeter data for 15 years. The number of eddies showed weak interannual variation. The number of eddies showed a positive phase from 1999 to mid-2001, followed by a negative phase in 2002, and a positive phase in 2003 and from 2004 to mid-2005. The inter-annual change rate of the eddy number is only −10 to 10% (Fig. 5.9a). We began to calculate the trend of the eddy number from April 1995 (the ERS-1 data from January 1994 to March 1995 is missing), and the results show that the eddy number dropped by 6% from April 1995 to October 2009. The eddy radius also shows a weak interannual variation, with a variation range of less than 5%. The eddy radius increased by 2% from April 1995 to October 2009 (Fig. 5.9b). The significant positive phase of the eddy lifespan appeared from 1995 to 1999, and showed an obvious downward trend in 1996. Over the past 15 years (1995–2009), it has dropped by 21%. EI dropped significantly in 1994 by 25% (Fig. 5.9d). This is more consistent with the 30% decline in global EKE in 1994, mainly because of the lack of ERS-1 data at this time. Similar situations have been observed in the four major upturn regions in the world (Chaigneau et al. 2009) and the coast of Brazil (Chaigneau et al. 2008). EI increased sharply from 1995 to 1997 with a range of 10–45%. Two other positive phases appeared in 2000–2002 and 2006–2008, and three negative phases appeared in 1997–2000, 2002–2005 and 2008–2009. In order to understand whether the interannual variability of EI is related to certain climates, we performed a November sliding filter on the sea surface temperature anomaly (SSTA) in the Niño3 area (5° S– 5° N, 90°–150° W), and we will get correlation analysis between the results and EI interannual signals. The results showed that when the SSTA in the Niño3 region led the EI variation by one month, their correlation coefficient reached −0.42 (with a confidence level higher than 95%). So, how does El Niño affect EI in the South China

5.1 General Characteristics and Individual Case Studies …

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Sea? Chen et al. (2009) pointed out that El Niño influences the inter-annual variation of EKE in the South China Sea through atmospheric bridge-wind stress curl. In order to understand the relationship between wind and EI, we also performed November sliding filtering on the monthly QuickSCAT wind stress curl and meridional wind in the South China Sea. Correlation analysis results show that when the wind advances by one month, the correlation coefficients of EI and wind stress curl and meridional wind reach 0.30 and 0.32 respectively (the confidence level is higher than 95%). The weaker correlation may be due to the shorter time series of wind data. A preliminary explanation is that the South China Sea wind field weakened significantly during the El Niño period, and the wind stress curl and meridional wind were correspondingly weakened (Chen et al. 2009), and the weaker wind stress curl and meridional wind resulted in smaller EI. In order to better explain these phenomena, further research is necessary. Using the temperature profile data of the matched 763 buoys affected by the mesoscale eddies, we obtained the probability distribution of the maximum temperature anomaly caused by the eddy (Fig. 5.10a). The anticyclonic eddy drove a maximum increase in sea temperature of 2–5 °C, with a peak value of 4 °C. The cyclonic eddy can cause the sea area temperature to decrease with a maximum range of 0–3 °C, and a peak value of −1 °C. Further, we studied the distribution of the average temperature anomaly caused by the eddy with depth (Fig. 5.10b). At the surface, both types of eddies have little effect on the temperature distribution. As the depth increases, the difference becomes obvious. The temperature anomaly caused by the anticyclonic eddy increases rapidly in the 110 m layer and gradually weakens in the next 400 m. The temperature anomaly caused by the cyclonic eddy drops sharply below the 80 m layer, and then rises sharply in the next 80 m. Below 160 m, the cyclonic eddy has little effect on the temperature distribution. The above results show that the subsurface temperature can better reflect the existence of eddies than the surface temperature. In addition, anticyclonic eddies can cause temperature anomalies in the upper 500 m, and the most significant impact depth is around 110 m; while cyclonic eddies can cause temperature anomalies in the upper 160 m, and the most significant impact depth is around 80 m. These results are consistent with the case of the mesoscale eddy dipole in the Vietnam. Further analysis results show that the depth of the thermocline inside the anticyclonic eddy and cyclonic eddy is about 110 m and 80 m, respectively. This is mainly because the anticyclonic eddy depresses the thermocline, and the cyclonic eddy raises the thermocline.

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea (a) 0.4 CE AE

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b. The distribution of the average temperature anomaly caused by the eddy with depth

Fig. 5.10 Abnormal temperature caused by eddy (Chen et al. 2011)

5.1.2 Individual Mesoscale Eddies in the South China Sea Observed by Satellites and Cruise 5.1.2.1

Seasonal Mesoscale Eddy

This section introduces three seasonal eddies of the Luzon warm eddy, the Vietnam eddy dipole and the spring warm eddy in the western South China Sea. The Luzon warm eddy is generated in the northwest of the Luzon Strait, and often carries high salt water in the Luzon Strait across the northern part of the South China Sea, which has important influence on the water mass and the climatology in the northern South China Sea (Yuan et al. 2007; Chen et al. 2010a); The Vietnam eddy dipole is closely

5.1 General Characteristics and Individual Case Studies …

245

related to the South China Sea wind stress curl, the South China Sea circulation and El Niño (Wang et al. 2006a; Chen et al. 2010b; Li et al. 2014b; Chu et al. 2014), it also makes an important contribution to the summer water bloom in eastern Vietnam (Chen et al. 2014); the warm spring eddy in the western South China Sea is a recently discovered seasonal eddy (He et al. 2013), and preliminary studies have shown that it has a significant impact on the air-sea interaction, but its related characteristics are not yet clear, and further research is needed. (1) Luzon Warm eddy The northeastern South China Sea is a region with high frequency of mesoscale eddies (Su et al. 2002; Wang et al. 2003; Lin et al. 2007). Previous studies have shown that the eddy in this area may originate from the Kuroshio (Li et al. 1998; Wang et al. 2008a) shedding or local generation. Due to the lack of hydrological data, the vertical structure and evolution characteristics of these eddies are rarely studied. By analyzing the characteristics of seawater temperature and salinity, Li et al. (1998) pointed out that in early September 1994, an anticyclonic Kuroshio separation ring was captured in the northern South China Sea. The flow ring is an anticyclonic eddy centered at 21° N and 117.5° E, with a diameter of about 150 km and a vertical dimension of more than 1000 m. However, Yuan et al. (2007) analyzed the altimeter data of the same period and pointed out that this anticyclonic eddy was the “Luzon Warm Eddy” (LWE) propagating westward and generated on the northwest side of Luzon. Yuan et al. (2007) also pointed out that LWE is a seasonal eddy, which is closely related to the meridional wind. In order to better understand LWE, Chen et al. (2010a) carried out the EOF decomposition on the sea surface height anomaly (SLA) in June for a total of 16 years from 1993 to 2008. The same method was also applied to the months of July to December and January. Since EOF decomposition is sensitive to the selection of regions, in order to avoid interference from other regions, when decomposing SLA in different months, different regional data are selected (Fig. 5.11). The results show that the weights of the first mode from June to February of the following year are 66%, 79%, 83%, 82%, 82%, 61%, 71%, 55%, and 52%, respectively. Therefore, the first mode of each month can describe the main characteristics of the area’s SLA. Figure 5.11 shows that LWE usually begins in June, formed in July, and gradually strengthened in August and September. LWE began to separate from the Luzon Island in October and spread westward, then weakened in December, and disappeared in February of the following year. The propagation speed of LWE varies from month to month, and the speeds from August to January of the following year are 3.0, 2.1, 3.9, 6.3, 14.3 and 9.9 cm/s. The large difference in speed between winter and summer may be due to the reversal of the monsoon. In winter, the north-northeast monsoon prevails in the South China Sea, and the northern part of the South China Sea presents a strong cyclonic circulation, which may help the eddy to propagate westward. The average diameter of LWE is 305 km, which is consistent with the 307 km estimated by Wang et al. (2003) and larger than the result reported by Yuan et al. (2007). In 2006, LWE captured an Argo buoy (No. 2900391). Chen et al. (2010a) used this buoy to study the vertical structure of the LWE and established a coordinate system

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea

Fig. 5.11 The first spatial mode distribution of SLA in different months (Chen et al. 2010a)

that moves with the LWE (the origin of the coordinate is the eddy center position). According to the relative position of the buoy and the LWE and the distribution of temperature and salt anomalies, Chen et al. (2010a) obtained the distribution map of the zonal temperature and salinity anomalies of LWE (Fig. 5.12a, b). Since the buoy is always located to the east of the LWE center, only the eastern zonal structure of the LWE is obtained. As shown in Fig. 5.12a, LWE has the largest temperature anomaly of 5 °C near the thermocline. This means that the temperature distribution of the subsurface layer can better reflect the existence of LWE. The abnormal distribution of thermohaline indicates that the influence of LWE on thermohaline structure is mainly located at a depth of 50–200 m. According to the internal temperature and salinity distribution of the LWE, the depth of 1000 m is taken as the zero velocity reference depth, and the velocity distribution caused by the LWE is obtained by using the geostrophic relationship (Fig. 5.12c). It can be seen that the LWE exceeds 500 m vertically, the larger geostrophic velocity is 200 m in the upper layer, and the maximum velocity is 0.6 m/s. The flow velocity gradually increased from the center of the eddy to the area of 0.6 longitudes away from the center of the eddy, and then gradually decreased. Figure 5.13 is the T-S diagram of the buoy. The highest salinity observed in the fifth profile is about 34.8 psu, which corresponds to a temperature of 24 °C, which is obviously not the characteristic of the South China Sea. However, the seawater with a geopotential density exceeding 26.0 kg/m3 (approximately 250 m deep) present

5.1 General Characteristics and Individual Case Studies …

247

Fig. 5.12 Distribution of zonal temperature and salt anomalies and geostrophic velocity of LWE (Chen et al. 2010a)

obvious characteristics of the South China Sea. The temperature and salinity curve of the 9th profile (which has been captured by LWE when the buoy observes this profile) shows that LWE is involved in high temperature and high salt water. Although the 13th, 15th and 16th sections are all located near the eddy center of LWE, their temperature and salinity characteristics are obviously different. Section 15 is the typical characteristics of the South China Sea, while the seawater of Sections 13 and 16 show the characteristics of a mixture of South Sea and West Pacific Ocean. The different water features of these profiles mean that LWE has been involved in the seawater of the West Pacific Ocean, and the involved seawater has not been mixed well, only being carried westward. (2) Vietnam mesoscale eddy dipole The upper circulation in the South China Sea is mainly driven by the monsoon (Qu 2000; Su 2004). Driven by the monsoon and the influence of the topography, the east of Vietnam show significant multi-eddy characteristics (He et al. 2002; Wang et al. 2003; Chen et al. 2009). In summer, the positive wind stress curl in the northern South China Sea and the negative wind stress curl in the southern South China Sea drive the cyclonic circulation in the northern South China Sea and the anticyclonic circulation in the southern South China Sea, accompanied by an offshore current leaving the eastern coast of Vietnam (Fang et al. 2002; Shaw et al. 1999; Wu et al. 1998, 1999). The north and south sides of this eastern jet are often accompanied by an anticyclonic eddy and a cyclonic eddy, which is called an eddy dipole. Wu et al.

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea

Fig. 5.13 T-S diagrams of different sections (Chen et al. 2010a). The gray lines are isopycnics

(1999) assimilated the altimeter data into the model and believed that the eddy dipole did exist in the east of Vietnam. They also pointed out that the eddy dipole weakened or disappeared during the El Niño period from 1994 to 1995. Wang et al. (2006b) pointed out that the eddy dipole is related to the eastward offshore currents in this area. The strong offshore currents along the coast of central Vietnam extend to the northeast and form dipole-like backflows on both sides, corresponding to a cold eddy on the north side and a warm eddy on the south side. The eastward offshore current changes on various time scales are related to the Asian monsoon, such as intra-season (Xie et al. 2007), season (Fang et al. 2002), inter-annual (Chen and Wang 2015; Li et al. 2014b), decadal (Wang et al. 2010). Wang et al. (2006b) conducted a sensitivity test using a 1.5-layer reduced gravity model, and concluded that wind stress curl is the key factor driving the eddy dipole here; Chen et al. (2010b) pointed out that the inter-annual variation of eddy dipole strength is related to wind stress curl. The eddy dipole and the eastward offshore current have significant effects on the physics and ecology of the South China Sea (Xie 2003; Tang et al. 2004; Xie et al. 2007; Chen et al. 2014). The SLA distribution from the end of June to the beginning of November 1997 showed that there was a cyclonic eddy and an anticyclonic eddy in the east of Vietnam (Fig. 5.14). This is the eddy dipole mentioned above. The eddy dipole was formed at the end of June. The center of the cold eddy is located on the coast of Vietnam at 12° N and 109° E. The SLA value of the eddy center is about −12 cm, while the center of the warm eddy is located at 9° N and 110° E. The SLA value of the eddy center is about 8 cm. Subsequently, the eddy dipole gradually became stronger and expanded eastward to a certain extent. As of August 27, the SLA values of the cold and warm eddy centers reached −20 cm and 20 cm, respectively, and the zonal diameters of the two eddies exceeded 400 km and 450 km, respectively. The eddy dipole starts to weaken at the end of September and tends to move southward. On November

5.1 General Characteristics and Individual Case Studies …

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5, as the warm eddy moved southward and disappeared, the eddy dipole eventually disappeared. Further research shows that the eddy dipole is a pair of seasonal eddies. The eddy dipole usually occurs at the end of June or the beginning of July. It gradually strengthens from August to September, begins to weaken in October, and disappears at the end of October. Moreover, the warm eddy dissipates earlier than the cold eddy. At the end of October, the South China Sea was controlled by the northeast monsoon, and the formation and development of the surface cyclonic circulation in the South China Sea (Shaw et al. 1999) should be the cause of the eddy dipole disappearing in the south direction. In early September 2007, the cold eddy of the eddy dipole was observed by the Dongfanghong 2 research ship (Fig. 5.15). Figure 5.16 shows the observed three-dimensional distribution of eddy temperature, vorticity, and vertical velocity, where the vertical velocity is calculated using the quasi-geostrophic Omega equation (Martin and Richards 2001). It can be seen from Fig. 5.16 that the radius of the surface cold eddy is about 90 km, and the radius does not decrease significantly with depth, and there is still 65 km at the 500 m layer. The maximum vertical velocity appears approximately at the 80 m. The positive vorticity of the cold eddy decreases rapidly with the increase of depth. It is greater than 2.0 × 10−5 s−1 at the surface layer, and decreases to less than 0.6 × 10−5 s−1 at the 100 m layer. The distribution of vorticity is consistent with the position of the jet stream, with positive vorticity and negative vorticity on the north and south sides of the jet stream. The rising speed is basically 14°N

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Fig. 5.14 SLA distribution in the east of Vietnam from the end of June to the beginning of November 1997 (Chen et al. 2010b). The distance between contour lines is 5 cm; the water depth in the white area in the picture is less than 100 m

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea

Fig. 5.15 Distribution of CTD stations in the South China Sea southwest cruise in the autumn of 2007 (Hu et al. 2011)

related to the positive value of vorticity, but the falling speed is not related to the negative vorticity. The upward arching of isotherms and isotherms can be caused by the ascending motion near the center of the eddy and the sinking motion on the west and east sides (Hu et al. 2011). Figure 5.17 further shows the variation characteristics of the regional average eddy radius, ascent and sink speed with depth. The eddy dipole has significant interannual variation. Empirical Orthogonal Decomposition (EOF) based on the sea surface height anomaly (SSHA) of the SODA data in September in Eastern Vietnam for 50 years (1958–2007) (decomposition area is 6°–15° N, 106°–115° E, excluding the data where the water depth is less than 100 m), the weights of the first three modes are 47.3%, 29.9% and 10.0% respectively. Therefore, the first and second modes can describe the main characteristics of the interannual variation of SSHA in the region. The first mode (Fig. 5.18a, c) shows that there was a mesoscale eddy dipole in the east of Vietnam in September. The southern warm eddy center was located at 10° N and 111° E, and the northern cold eddy center was located at 12.5° N and 111° E. And the warm eddy is stronger than the cold eddy. The second mode (Fig. 5.18b, c) shows an eddy in the northern part. If the time coefficient of the first mode and the time coefficient of the second mode are in opposite phase, then a significant eddy dipole appears in the area, such as 1994; if the time coefficient of the first mode is in phase with the time coefficient of the second mode, then a strong warm eddy will appear in the sea, such as in 1998. The EOF decomposition result further proves the existence of the summer eddy dipole in the east of Vietnam and the correctness of the above analysis of the interannual variation of the eddy dipole. The power spectrum analysis of the first-time mode shows that the most significant interannual variation periods of the eddy dipole are 5.6 and 3.6 years. At the same time, it is noted that the significant periods of the first-time modal interannual variation of the wind stress curl field in this region are 3.7 and 5.6 years. The spatial distribution and interannual variation period of the first mode of wind stress curl are basically the same as the spatial distribution and interannual variation period of the first mode of SSHA. Therefore, the interannual variation of wind stress curl in this region has an effect on the interannual variation of the eddy dipole.

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Fig. 5.16 The three-dimensional structure of the eddy (Hu et al. 2011). The vertical velocity is positive upward; the black line in the figure is the eddy boundary

(3) Spring warm eddy in western South China Sea In the western of the South China Sea which is in the east of Vietnam, in addition to the eddy dipole that appears in summer and autumn, historical data from field hydrological observations and satellite remote sensing data all reveal the structure of a warm eddy that appears in spring. This warm eddy generally begins to form in the east of central Vietnam in February. First, a small closed area with the sea level anomaly greater than 5 cm appears (Fig. 5.19); in March, the area with the sea level anomaly gradually expanded and moved northward. It moved and rapidly developed

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea

Fig. 5.17 Vertical section of eddy (Hu et al. 2011). The vertical speed is greater than 0 and upward is positive, and the average range is determined by the Okubo–Weiss parameter

into an independent warm eddy structure; in April, the range of high sea level anomaly continued to expand, and the warm eddy reached its peak; in May, the range continued to expand to include the entire northern South China Sea basin from west to east, with a mesoscale eddy structure begins to decline, showing the characteristics of a larger-scale “warm pool”. The center of the eddy has a relatively high temperature and low salinity (Fig. 5.20). Although its intensity and spatial extent show significant inter-annual variability (Fig. 5.21), its appearance time (February–May) and location (12°–16° N, 110°–114° E) is relatively stable. Through numerical sensitivity tests and analysis of the characteristics of wind stress distribution in climatic wind fields, He et al. (2013) pointed out that the seasonal transition from spring to summer wind stress and its curl change are important reasons for the formation of this warm eddy, and the release of potential energy caused by the winter monsoon also makes an important contribution. He et al. (2013) also found that the warm eddy has a good correlation with the distribution of precipitation over it. The high precipitation value corresponds to the center of the warm eddy (Fig. 5.22). The higher SST accompanying the warm eddy can enhance the atmospheric convection over it, thereby increasing local precipitation.

5.1.2.2

Observations of Anticyclonic Eddy Cruises in the Northern South China Sea

This section introduces examples of anticyclonic eddies observed by the South China Sea Institute of Oceanology, Chinese Academy of Sciences, including the three anticyclonic eddies observed in the northeastern South China Sea in the winter of 2003/2004 (Wang et al. 2008a) and the 18° N section in the summer of 2007.

5.1 General Characteristics and Individual Case Studies … 14°N

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Fig. 5.18 The first and second spatial and temporal modes of SSHA in the southeast of Vietnam (Chen et al. 2010b)

Cyclonic eddy observations (Nan et al. 2011) and individual observations of extreme anticyclonic eddies in summer 2010 (Chu et al. 2014). (1) Observations of anticyclonic eddies in the northeastern South China Sea in the winter of 2003/2004 In December 2003 and January 2004, the South China Sea Institute of Oceanology, Chinese Academy of Sciences, respectively deployed two buoys near Taiwan in the northern South China Sea. The buoys were labeled 22918 and 22517. Using these two buoys and the observational and remote sensing data collected during the same period, Wang et al. (2008a) analyzed the characteristics and sources of individual anticyclonic eddies in the northeastern South China Sea. Figure 5.23 shows the sea level anomaly in the winter of 2003/2004 and the trajectory of the buoy 22517 (defining the day of launching the buoy as the 0th day), and defines two anticyclonic eddies AE1 and AE2. From the distribution of sea level anomalies, it can be seen

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Fig. 5.19 The climatical sea level anomaly (contour, unit: cm) and sea surface temperature anomaly (color filling, unit: °C) from January to May (He et al. 2013)

Fig. 5.20 The distribution of temperature (unit: °C) and salinity (unit: psu) on the 14.5° N section (He et al. 2013)

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Fig. 5.21 Range of sea level anomaly of the warm eddy in the western South China Sea from 1993 to 2006 (He et al. 2013)

Fig. 5.22 Relationship between precipitation rate and sea level anomaly distribution of warm eddy (He et al. 2013)

that AE1 may have originated from the anticyclonic eddy near the Dongsha Islands and gradually moved southwest. The two buoys were captured by the anticyclonic eddy, and moved under the combined action of the local eddy and the large-scale circulation. The buoy 22918 was released on December 4, 2003, and it circled twice in AE1 from the 4th to the 23rd (Fig. 5.24a), and then escaped from AE1 and drifted southwest. After AE1, another anticyclonic eddy AE2 occurred in the middle of the Luzon Strait (January 14, 2004). Buoy 22517 was deployed on the north side of AE2 on January 20. Figure 5.24b shows the trajectory of the buoy 22517 every 7 days from the 4th day to the 85th day. AE2 basically moves to the southwest along the slope, and the buoy rotates inside AE2 after being captured by AE2. As AE2 moved westward, its intensity continued to weaken. After the 81st day, AE2 was already very weak, and the buoy had fallen out of AE2’s control and landed behind it. Buoy 22517 entered AE2 on the 8th day and began to rotate inside it. From the 20th to the 30th day, the trajectory of the buoy and the trajectory of AE2 began to show a large deviation, indicating that AE2 was

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Fig. 5.23 Distribution of sea level anomaly and trajectory of buoy 22517 (Wang et al. 2008a). a Sea level anomaly on January 14, 2004. b Buoy 22517 trajectory from day 4 to 11 and sea level anomaly on January 28. c Buoy 22517 trajectory from day 27 to 34 and sea level anomaly on February 18. d The buoy 22517 trajectory from the 45th to the 53rd day and the sea level anomaly on March 10. e The buoy 22517 trajectory from the 66th to the 73rd day and the sea level anomaly on March 31. f The trajectory of the buoy 22517 from 81 to 88 days and the sea level anomaly on April 14

moving in a large southwest direction during this period. From the 40th to the 50th day, the buoy moved rapidly southwest with AE2. From the 50th to the 85th day, the rotation of the buoy began to gradually weaken. After the 85th day, the buoy left AE2 and finally entered the Luzon cold eddy. In addition, it can be seen from Fig. 5.23 that another eddy was generated in the southwest of Taiwan Island and the Luzon Strait in March 2004, which proves from the side that the Luzon Strait and the northeastern South China Sea are areas of high incidence of eddies.

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Fig. 5.24 Buoy trajectory (provided by Canada MEDS) (Wang et al. 2008a). a The trajectory of the buoy 22918, the black dots indicate the position every 5 days from December 4, 2003 to January 3, 2004. b The trajectory of the buoy 22517, the blue line is the center trajectory of the anticyclonic eddy extracted from the satellite sea level anomaly data (the same period as the buoy)

During the evolution of the eddy, AE1 and AE2 were observed on three sections of the South China Sea Institute of Oceanology, Chinese Academy of Sciences (Fig. 5.25). The observation time of section A and B is from February 27 to March 4, 2004, and the observation time of section D is from February 18 to 19, 2004. Figure 5.26 shows the temperature and salt distribution of the three sections. In section A, there are low-salt and high-temperature tongues from 20.4° N to nearshore at 50 m level. The temperature at station A1 is the highest, reaching 23.2 °C, indicating that the station is close to AE2. Relatively low-salt, high-temperature water has been extended to A5 station. Section B is closer to AE2 than section A. The distribution of thermohaline sections at stations B2 to B5 is similar to that of A1 to A5, but with lower salinity and higher temperature. Figure 5.26c shows the temperature and salt distribution of section D. Near D3, the upper layer also shows the characteristics of low salt and high temperature, which shows that AE1 is located near the 50 m layer of D3 station. Figure 5.27 is the T-S diagram of sections B and D. The inner and outer positions of AE2 and AE1 are respectively drawn to compare the difference between the inside and outside of the eddy. It can be seen from Fig. 5.27a that the potential density of stations B3–B5 is larger than that of stations B1 and B2, indicating that the buoyancy inside AE2 is greater than that outside. The low-salt and high-temperature characteristics of the eddy center may originate from the surface. In the deep layer (sigma23.6 to sigma24.8) the difference between B1 and B2 stations and B3–B5 stations still exists, indicating that AE2 is still strong in the deep layer. Figure 5.27b shows the difference between the internal and external characteristics of AE1 obtained from section D. It can be seen that the difference between stations D2, D3 and stations D1, D4, and D5 is smaller than that of section B, and above sigma23.9, the difference of characteristics of the water mass decrease gradually, until sigma24.4. This decreasing difference indicates that the observation of section D is in the AE1 decay stage.

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Fig. 5.25 Distribution of observation stations (Wang et al. 2008a). a The observation time of section A and B was from February 27 to March 4, 2004, and the superimposed sea level anomaly was on March 4, 2004. b The observation time of section D was February 18–19, 2004, the superimposed sea level anomaly was on February 18, 2004

(2) Observations of three anticyclonic eddies on section 18° N in summer 2007 At the end of August 2007, the research ship of the South China Sea Institute of Oceanology, Chinese Academy of Sciences observed three anticyclonic eddies at the 18° N section of the South China Sea (Fig. 5.28), from left to right, ACE1, ACE2 and ACE3 (Nan et al. 2011). Figure 5.29 shows the temperature, salinity, density, and sound velocity of the 18° N section obtained by CTD. Above the thermocline, temperature, salinity, density, and sound velocity are relatively uniform due to the effect of mixing; below the thermocline, temperature and sound velocity gradually decrease with increasing depth. The maximum salinity layer (~34.65 psu) appears at

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Fig. 5.26 Vertical distribution of temperature and salinity (Wang et al. 2008a). The picture above shows the salinity (psu), the picture below shows the temperature (°C), the black triangle indicates the station position

about 150 m, the minimum salinity layer (~34.45 psu) is about 500 m; the maximum sound velocity layer (~1540 m/s) is on the surface, and the minimum sound velocity layer is distributed in the 1000–1200 m layer. In the upper 300 m layer, there are two peaks and three valleys in the distribution of temperature, salinity, density, and sound velocity at the 18° N section. The peaks are located near 114° E and 116.5° E, and the valleys are located near 112° E, 115° E, and 118.5° E, respectively. Among them, the valley value is the center of the three anticyclonic eddies. The difference between the temperature and sound velocity at the center of the anticyclonic eddy and the surroundings is much greater than the difference in salinity, density, and surroundings. At 300–1500 m, the distribution of peaks and valleys is similar to that of the upper layer. Figure 5.30 shows the vertical distribution of the geostrophic velocity of the observation section. The core velocity of ACE1 is relatively small, about 0.15 m/s; ACE2 is about 0.60 m/s. ACE3 has two cores, namely ACE3(1)

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Fig. 5.27 T-S diagram of sections B and D (Wang et al. 2008a). The green dots are stations B1, B2, and stations D2, D3; the black dots are stations B3–B5 and stations D1, D4, D5, and the black line is the potential density contour

and ACE3(2), the speed of which is about 0.15 m/s and 0.40 m/s, respectively. The significant influence depth (0.05 m/s contour) of ACE2 and ACE3(2) is close to 900 m. (3) Observations of extreme anticyclonic eddies in the summer of 2010 Data from tide stations for more than 20 years show that the sea level in the Xisha Sea area had an extreme high value event in August 2010, far exceeding the historical record of the sea level there (Chu et al. 2014). The ship observation data and altimeter data of the South China Sea Institute of Oceanology, Chinese Academy of Sciences show that the extreme sea level was caused by a strong anticyclonic eddy with a horizontal scale greater than 400 km (Fig. 5.31). Eddy tracking shows that the eddy moved from the eastern seas of Vietnam to the Xisha seas, and its life cycle was more than 8 months. Studies have shown that the 2009/2010 El Niño event changed the South China Sea summer monsoon and the western boundary current. Starting from May, the southwest monsoon in the South China Sea is weaker, the northwest monsoon is stronger, and the wind direction in the west of the South China Sea is generally northerly. This abnormal monsoon affects the spatial distribution of wind

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Fig. 5.28 Sea surface characteristics of three anticyclonic eddies (Nan et al. 2011). a The distribution of three anticyclonic eddies on August 22, 2007 determined by Okubo–Weiss parameters. b The distribution of sea level anomaly on August 22, 2007 and the corresponding surface geostrophic currents

stress curl and the structure of the flow field along the coast of Vietnam. The boundary current in the western part of the South China Sea has changed from a normal eddy dipole structure to a strong northward current. This northward current entrains the eddy to move northward, and transfers energy to the eddy through the barotropic and baroclinic conversion during the northward movement, which causes the eddy to become larger and stronger. Figure 5.32 is the temperature and salt distribution observed at the five stations shown in Fig. 5.31. The temperature at stations 3 and 4 at the center of the eddy is much higher than that at stations 2 and 5; the salinity is just the opposite. Because the South China Sea is in a tropical region, the temperature anomaly caused by the eddy is not obvious in the surface layer, but it reaches 7.7 °C at the 75 m layer. The largest anomaly of salinity is also located near 75 m, about −0.78 psu. The seasonal thermocline was deepened by more than 40 m by the eddy. Using the reconstructed thermohaline field, Chu et al. (2014) revealed the three-dimensional

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Fig. 5.29 The vertical distribution of temperature (a), salinity (b), density (c) and sound velocity (d) at the 18° N section (Nan et al. 2011)

structural characteristics of the anticyclonic eddy (Fig. 5.33). The strong current caused by the eddy can extend to a depth of more than 600 m, and is strongest at the surface; the high temperature, low salt, and high density caused by the eddy mainly appear in the subsurface and mid-deep layers.

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Fig. 5.30 The vertical distribution of the geostrophic velocity of the observation section (north is positive) (Nan et al. 2011)

Fig. 5.31 Observation station position (black box and blue dot) and average sea level anomaly (average during observation period) (Chu et al. 2014)

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Fig. 5.32 The distribution and anomaly of the observed eddy temperature and salt structure (Chu et al. 2014). a Vertical distribution of temperature at 5 stations. b Vertical distribution of salinity. c Distribution of temperature section (unit: °C), the thermocline is defined as the position where the temperature gradient is greater than 0.05 °C/m, and the black line is the observation. The upper and lower boundaries of the thermocline, the white lines are the upper and lower boundaries of the climatic thermocline (WOA09). d Salinity section. e Temperature anomaly section distribution, relative to WOA09 climatological data. f Salinity anomaly section distribution. The 5 stations used in the figure are marked in Fig. 5.31

5.1.2.3

Mooring Observation of Xisha Eddy

(1) Mooring observation of mesoscale eddy energy changes in Xisha From May 2009 to May 2010, a one-year mooring current observation was conducted in the Xisha Islands, and the energy changes of the observed currents have obvious mesoscale characteristics (Wang et al. 2014). Figure 5.34 shows the changes in the kinetic energy of ocean currents, as well as the work done by barotropic pressure and wind stress. u·t 1 ∂u 2 = −g · u · ∇η + ρ0 H 2 ∂t The above formula is a simplified kinetic energy equation. The first term on the right is the work done by the barotropic pressure, and the second term is the work done by the wind stress. It can be seen from Fig. 5.34 that there are four significant stages in the distribution of kinetic energy. The first two stages have a deep impact, the third stage is relatively shallow, and the fourth stage starts to be relatively shallow and then suddenly deepens. From the comparison of the kinetic energy curve with the wind stress work curve and the pressure work curve, the kinetic energy is mainly

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Fig. 5.33 The three-dimensional structure of the warm eddy (Chu et al. 2014). a Temperature distribution. b Salinity distribution. c Density distribution. d Geostrophic flow. All data comes from reconstructed data

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Fig. 5.34 Observed current kinetic energy (Wang et al. 2014). a Kinetic energy (multiplied by 103 ), barotropic work (multiplied by 2 × 107 ) and wind stress work (multiplied by 4 × 108 ) calculated based on the current data of Xisha. b Average vertical integral kinetic energy and its time average kinetic energy and standard deviation of (all multiplied by 103 ). c The vertical distribution of kinetic energy over time (multiplied by 103 ), the value of kinetic energy greater than the average plus standard deviation is drawn, the blue line represents the limit of the average energy, and the vector is the current velocity (northward is positive)

affected by the pressure work. The pressure work is mainly affected by the sea level gradient. It can be seen from the superimposed sea level anomaly that the first stage is affected by cyclonic eddies, the second stage is anticyclonic eddies, and the third stage is two consecutive cyclonic eddies, and the fourth stage is alternating cyclonic eddy and anticyclonic eddy effects. (2) Mooring observation of deep-sea eddies in the South China Sea Based on mooring observations (positions shown in A and B in Fig. 5.35), Chen et al. (2015) first discovered the South China Sea deep-sea eddy (a eddy with no

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267

track in the upper ocean). The deep-sea eddy occurred in the Xisha Island from April to May 2012, with a radius of 23–28 km, and moved westward at a speed of (1.27 ± 0.45) cm/s. The velocity of the eddy in the deep ocean is as high as 0.18 m/s (Fig. 5.36b, f), which is much higher than the average velocity of 0.03 m/s and the median velocity of 0.02 m/s. The eddy caused the isotherm at a depth of 1200 m to sink up to 120 m (Fig. 5.36g), which significantly enhanced deep sea mixing and doubled the sediments in May 2012. Studies have shown that the deep-sea eddy is generated when strong current flows through seamounts (Fig. 5.35b, c) induced by a strong upper cyclonic eddy (Fig. 5.35a, b). Numerical simulations show that the strong cyclonic eddy in the upper layer of the Xisha Sea has induced strong northwestward currents (Fig. 5.35b). When the northwestward current flows through the seamount, it induces a strong deep-sea eddy at a depth of 600 m north of the seamount (Fig. 5.37c–e). The sensitivity test showed that when the seamount was removed, the deep-sea eddy disappeared (Fig. 5.37f). This is because when the vertical shear current flows through the seamount, the friction between the seamount and the current weaken the stratification near the bottom layer, forming a bottom mixed layer or bottom boundary layer, and leads to the formation of horizontal density fronts and rapids, which are unstable and induce deep-sea eddies. Previous studies have shown that strong currents can induce eddies by passing through islands. The observations and simulations of Chen et al. (2015) show that strong upper currents passing through seamounts can also cause eddies, but the eddies occur in the deep rather than the surface. The Xisha Island is the only place where the western boundary current of the South China Sea must pass, and it is also the place where many mesoscale eddies in the South China Sea are generated and routed (Chen et al. 2011). Simulation studies have shown that under the influence of the west boundary current of the South China Sea and mesoscale eddies, the Xisha Trough generates many deep-sea eddies. These eddies propagate in different directions due to the influence of the β effect and deep background currents. The Xisha Trough is just like one of the birthplaces of deep-sea eddies in the South China Sea. Due to its high energy and strong mixing, deep-sea eddies have a great impact on submarine optical cables, submarine oil pipelines, deep-sea exploration, deep-sea sediments, and deep-sea ecology. Due to the limitation of observation technology, as well as the variation characteristics of deep-sea eddy itself and the characteristic of no track in the upper ocean, deep-sea eddy observations are very few and extremely difficult to be discovered; the impact of deep-sea eddies is rarely revealed, and further research is urgently needed. The deep strong currents in the South China Sea may also come from the excitation of topographic Rossby waves. Taking the Nansha Islands (Fig. 5.38) as an example, the evolution and vertical structure characteristics of topographic Rossby waves in the deep sea are studied by using long-term mooring data on the north side of Yongxia Reef. It is found that in the deep sea at 1400 m north of Yongxia Reef, there is an oscillation of the current with a period of 9–14 days. This oscillation has an obvious bottom intensified feature (Fig. 5.38), and this bottom intensified character can be seen in the time series of the last 5 years.

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Fig. 5.35 Topography of the northern South China Sea (Chen et al. 2015). a The color in the figure represents the topography of the northern South China Sea, and the arrow is the altimeter sea surface geostrophic flow on April 18, 2012; A and B are the locations of the mooring targets. b The topography and surface geostrophic flow in the area shown in the black box in a. c The vertical profile of the seamount shown by the red line in b

5.1.2.4

Seismic Wave Detection of Eddies and Mesoscale Phenomena

The traditional ocean observation methods have encountered a bottleneck in the observation of the sub-mesoscale to fine scale structures in the ocean, which largely limits the study of ocean dynamic and mixing processes at corresponding scales. However, “seismic oceanography” (i.e., using seismic reflection methods to study

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Fig. 5.36 Ocean currents, temperature and salinity observed by mooring from March 5, 2012 to June 18, 2012 (Chen et al. 2015). a 40–440 m horizontal velocity. b 1000–1450 m horizontal velocity. c 400–950 m temperature (contour) and temperature anomaly (color) observed by mooring A. d The temperature at 1463 m observed by mooring A. h The salinity of 1160–1435 m observed by mooring B. e–g is the same as a–c, but a–c is the observation of mooring A, and e–g is the observation of mooring B, and the observation depth is also different

ocean phenomena) can provide a new perspective for studying fine scale ocean phenomena. For example, the seismic method significantly improves the horizontal resolution by three orders of magnitude compared to the traditional in-situ observation methods for observing eddies, allowing for a fine description of the structure within and around the eddies. Tang et al. (2013) found a lenticular mesoscale structure in the subsurface layer of the Nansha when they studied the fine structure of the water column using multiple seismic history data from the ocean, and combined with the ocean model data, they concluded that the structure was a flow core crosssection of a primary upper layer current rather than an eddy as commonly thought (Fig. 5.39). Huang et al. (2013) used seismic data to estimate the geostrophic current velocity of individual eddy in the South China Sea. The data were collected in the southwest sub-basin of the South China Sea from May 30 to June 1, 2009, and the locations are

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Fig. 5.37 Circulation simulated by the model (Chen et al. 2015). a–e are the simulated circulations of 50 m, 400 m, 600 m, 900 m and 1100 m respectively. Picture f is the same as picture e, but is the result of seamounts removed in c. Color represents water depth, white is land

Fig. 5.38 South China Sea topography (a) and Nansha topography (b) (Shu et al. 2016). The asterisk in b represents the mooring locations. The rosy dashed line represents the observed topographic Rossby wave oscillation velocity (centered on M1 and projected to the surface layer); the gray dashed line represents the possible topographic Rossby wave propagation path

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Fig. 5.39 Seismic image of fine structure and its subsurface mesoscale structure

shown in Fig. 5.40. The survey was interrupted for nearly 5 h to avoid the spring tide period, which is marked in Fig. 5.40 by different colored. The seismic survey used the BOLT gun system with a near-gun check distance of 250 m and a gun spacing of 37.5 m. The seismic data were recorded using 480 channels of hydrophones with a channel spacing of 12.5 m, a total recording length of 12 s, and a sampling interval of 2 ms. The seismic data are first intercepted in the time window 0–6 s and the spatial window 0–6 s, and then the spatial window 1–240 channels are used to intercept the part of the seismic data that can reflect the reflected wave information of the seawater body. The seismic data are then subjected to routine processing, including definition of the observation system, removal of direct waves, filtering, velocity analysis, dynamic correction, and superposition processing. The strong direct wave energy masks the relatively weak reflected wave energy of the water, so the removal of direct waves is necessary. Figure 5.40 shows that the lenticular structure is located in the southwest subbasin of the South China Sea with a central position about 11.4° N, 113.6° E. From the seismic section of Fig. 5.41a, it can be seen that it has a central depth of about 450 m and thickness of about 300 m. Since the detection interrupted for nearly 5 h to avoid the spring tide period, the seismic survey line did not capture the full picture of the lenticular structure, but it can still be inferred that its diameter is 55–65 km, which is a typical mesoscale eddy characteristics. Huang et al. (2013) define it as an anticyclonic structure by referring to the sea level anomaly and geostrophic field. Huang et al. (2013) used black lines to roughly outline the lower boundary of the lenticular structure and its affected area. On the seismic profile, the reflections above the black line are strong and clear, while the reflections below are weak and messy, since the geostrophic shear and the geostrophic current velocity are calculated on the

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Fig. 5.40 The topography and the location of seismic survey lines and the eddy in research area (Huang et al. 2013). The blue and black lines are continuous, but the survey time interval is nearly 5 h. The green line is a part of the blue line, indicating the spatial extent of the eddy

reflection homogeneous axis, the calculated results above the black line are credible than below, while the below one is so severely affected by noise that regarded as an invalid calculation result. The central depth of the eddy is 400–450 m and match well with the seismic image from Fig. 5.41b, d. The result of geostrophic calculation gives that the maximum velocity is about 0.7 m/s, the left side (northwest) is positive, and the right side (southeast) is negative, showing a clockwise rotation as known as anticyclonic structure. At present, “Seismic Oceanography” can observe serval physical phenomena such as ocean fronts, ocean currents, boundary layers, thermoclines, eddies, internal waves and others, highlighting its ability to depict the fine structure of water body, and has advantage like high efficiency and high resolution (~10 m). Relying on the shared voyage of the National Foundation of China, the first domestic seismic-physical ocean observation in the northeastern South China Sea had been organized and captured two internal solitary waves (Fig. 5.42), from the seismic wave data, it can be seen that the vertical and horizontal scales of internal solitary waves scales are 50 m and 1–2 km respectively (Tang et al. 2014). Tang et al. (2014) studied the extraction method of mixing parameters based on seismic wave data, and calculated, analyzed the internal waves of the South China Sea and Mediterranean eddies as examples. The results show that the mixing rate caused by internal waves in the South China Sea can reach about 10−2.79 m2 /s at a depth of 200–600 m, which is over two orders of magnitude higher than the statistical result of 10−5 m2 /s in the ocean. The turbulent mixing rate caused by Mediterranean eddy (Fig. 5.43) can reach about 10−3.44 m2 /s, which is about 1.5 orders of magnitude higher than the statistical result of open ocean, and the mixing of Mediterranean eddy at the lower boundary is stronger than upper. In addition, there is also a high mixing rate above the upper boundary and outside the lateral boundary of the eddy.

5.1 General Characteristics and Individual Case Studies … Fig. 5.41 Seismic image of eddy and relative parameters of velocity field (Huang et al. 2013). a Seismic image of the mesoscale eddy in the South China Sea. The black line roughly outlines the lower boundary of the eddy and its affected area. b The calculated vertical gradient of geostrophic velocity. c The component of the sea surface geostrophic current field perpendicular to the seismic survey line from AVISO. d The absolute geostrophic current field calculated by integration of the vertical gradient of geostrophic current velocity and the sea surface velocity field. The black lines in b and d have the same meaning, and the shading area below the black line means invalid results

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Fig. 5.42 Fine structure seismic image of water column and its shape of internal solitary wave (Tang et al. 2014)

Fig. 5.43 Seismic profile of the Mediterranean eddies (the lenticular structure represents the Mediterranean eddies) (Tang et al. 2014)

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The seismic oceanographic method provides a new observation method and research idea for the future study of mesoscale and fine scale oceanographic phenomena. Due to its advantages of economy, efficiency, and high resolution, it has a wide range of application prospects and is expected to become an important supplement to traditional ocean observation and to bring new breakthrough to physical ocean research.

5.2 Physical and Ecological Effects of Mesoscale Eddy in the South China Sea Mesoscale eddy has significant dynamic, thermal and ecological effects. Mesoscale eddies in the South China Sea are active, contributing importantly to the energy and water transport (Li et al. 1998; Chen et al. 2012; Wang et al. 2012b), to chlorophyll in the South China Sea (Chen et al. 2007; Zhang et al. 2009; Lin et al. 2010; Xiu and Chai 2011; Song et al. 2012; Xian et al. 2012; Liu et al. 2013), to ocean primary productivity (Lin et al. 2010), to sea surface temperature and wind (Chow and Liu 2012), to thermocline (Liu et al. 2001), to ocean mixing (Tian et al. 2009), to near inertial oscillation (Chen et al. 2013) an so on. It also contributes significantly to deep circulation changes in the South China Sea (Zhang et al. 2013) and bottom sediment transport (Zhang et al. 2014).

5.2.1 Thermal and Dynamic Effects of Mesoscale Eddy 5.2.1.1

Energy Transfer in Eddy-Mean Flow Interaction

Normally, eddy energy mainly comes from the release of available potential energy caused by wind-driven large-scale circulation through baroclinic instability (Gill and Niller 1973; Beckmann et al. 1994). Eddy-mean flow interaction not only affects the evolution of eddy itself, but also affects the strength, structure, and stability of largescale circulation. The interaction with western boundary current (Kuroshio, Gulf Stream) and Antarctic Circumpolar Current has always been a hot spot. The South China Sea is one of the largest and deepest marginal seas in the world. Its basinscale circulation shows significant westward strengthening (described in detail in Chap. 2). This westward strengthening current called the South China Sea West Boundary Current and is also the important part of the South China Sea throughflow, the change of the flow has an important impact on material and energy transport, and basin-scale circulation of South China Sea. Meanwhile, in the discussion of Sect. 5.1, we clearly saw the characteristics of the mesoscale eddies in the eastern and northeastern parts of South China Sea moving westward, and most of them eventually disappeared in the western boundary current of South China Sea. How

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does the eddy activities and interaction modulate the evolution of circulation and eddies in the South China Sea? It will be further discussed from the perspective of energy conversion of the interaction next. First, a brief introduction is made to an energy conversion model for studying the eddy-mean flow interaction: the four-box model of mechanical energy budget in the ocean. In the early pioneering work, Lorenz (1955) first proposed the method of estimating the available potential energy of atmosphere and the four-box model of mechanical energy budget between eddy and mean flow, according to the model, the total kinetic energy of the fluid (available potential energy) can be decomposed into the sum of mean flow energy and eddy kinetic energy (effective potential energy), and energy converse between them through barotropic (baroclinic) instability. This model gives the source and sink terms of the fluid system’s mechanical energy and the energy transfer path inside the system, reveals the eddy-flow interaction in perspective of energy, has become the criterion for the energy conservation of the earth’s fluids and is widely used in the study of ocean circulation dynamics (Böning and Budich 1992; Beckmann et al. 1994; Ivchenko et al. 1997; Treguier 1992; Xue and Mellor 1993; Von Storch et al. 2012). Base on Lorenz’s (1955) theory, the four-box model of the conservation of mechanical energy in the ocean can be represented in Fig. 5.44.

Fig. 5.44 Schematic diagram of the four-box model of ocean mechanical energy budget (Böning and Budich 1992). MKE, MPE, EKE, EPE represent mean kinetic energy, mean available potential energy, eddy kinetic energy, and eddy available potential energy respectively; T1, T2, T3, and T4 respectively represent the conversion and transmission between these four energies; WWM and WWE represent wind stress works on the mean flow and eddy respectively; FRIC represents friction term; AMK, AEK, AMP, and AEP represent the advection terms of mean kinetic energy (MKE), eddy kinetic energy (EKE), mean available potential energy (MPE), and eddy available potential energy (EPE); PWM and PWE are the divergence terms of pressure terms; HFM, HFE, FFM, FFE represents the contribution of sea surface heat flux and fresh water flux to the mean flow and eddy available potential energy respectively; DIFF represents the dissipation terms of potential energy

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According to the definition of kinetic energy and available potential energy in the ocean proposed by Oort et al. (1989), combined with the methods of Xue and Bane (1997), the mean kinetic energy (MKE), eddy kinetic energy (EKE), mean potential energy (MPE) and eddy available potential energy (EPE) per unit mass are defined as follows: MKE = EKE =

1 v→m · v→m 2

(5.1)

1 ′ ′ v→ · v→ 2

(5.2)

2

g ρ˜ ) 2ρ ∂ρ θ /∂z

(5.3)

g ρ˜ ′2 ) 2ρ ∂ρ θ /∂z

(5.4)

MPE = − EPE = −

(

(

where ρ(x, ˜ y, z, t) = ρ(x, y, z, t)−ρb (z), ρ is the density of seawater, ρ˜ is the spatia anomaly of ρ, ρ˜ ′ is mesoscale anomaly, ρb (z) is the background density profile, here means the horizontal average of annual mean density. ρ θ is the horizontal average of annual mean potential density, and its vertical partial derivative characterizes the stability of ocean. v→m and v→′ represent background velocity and mesoscale velocity anomaly, respectively. The specific expression of each item in the budget of MKE and EKE can refer to Ivchenko et al. (1997). The source and sink items include sea surface wind stress work (WWM and WWE), friction work (FRIC), energy conversion between kinetic energy and potential energy (T1 and T3) caused by buoyancy work, and the kinetic energy conversion caused by eddy-mean flow interaction (T4). The kinetic energy advection terms (AMK and AEK) and pressure work (PWM and PWE, assuming that the effect of sea surface pressure is negligible) inside the ocean do not produce kinetic energy, only change the spatial distribution of kinetic energy. For MPE and EPE, the source and sink terms include the contribution of sea surface heat flux and freshwater flux to the mean flow and eddy potential energy (HFM, HFE, FFM, FFE), the dissipation term of potential energy (DIFF), T1, T3, and baroclinic conversion between MPE and EPE caused by instability (T2). Advection terms (AMP and AEP) change the spatial distribution of potential energy inside the ocean. The expression of barotropic instability leading to the energy conversion T4 of MKE and EKE is: ( ) ) ( ∂u m ′ ′ ∂u m ′ ′ ∂vm ′ ′ ∂vm +u v + +vv (5.5) T4 = − u u ∂x ∂x ∂y ∂y The expression of baroclinic instability leading to the energy conversion T2 of MPE and EPE is:

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( ) g ′ ′ ∂ ρ˜ ′ ′ ∂ ρ˜ ) u ρ˜ + v ρ˜ T2 = − ( ∂x ∂y ρ ∂ρ θ /∂z

(5.6)

The expression of energy conversion between mean-flow kinetic energy and potential energy T1 is: T1 =

g ρw ˜ ρ

(5.7)

The expression of energy conversion between eddy kinetic energy and potential energy T3 is: g T3 = − ρ˜ ′ w ′ ρ

(5.8)

Thus, to study the interaction between the South China Sea eddies and mean flows, we mainly focus on the distribution and changes of MKE, EKE, MPE, EPE, T2, T4 in the energy four-box model.

5.2.1.2

Spatial Distribution and Seasonal Changes of Eddy Energy in the South China Sea

Larger EKE in the South China Sea appears in the southeastern coast of Vietnam in spring and summer, and southwest of Taiwan Island in winter (He et al. 2002; Chen et al. 2009; Cheng and Qi 2010). Using the simulation results of the global eddy resolution model OFES (OGCM for the Earth Simulator) (Sasaki et al. 2004), the daily wind field from July 1999 to December 2006 from QuickSCAT is selected as a set of data for the dynamic forcing field (abbreviated as OFES_QS), according to Eqs. (5.2) and (5.4), Zhuang (2008) calculated the eddy kinetic energy (EKE) and eddy potential energy (EPE) at each depth, and perform vertical integration to obtain the EKE and EPE of whole water column. The annual average distribution characteristics of EKE and EPE are similar (Fig. 5.45a, b), both of which have two high value areas in the South China Sea (the rectangular area in the figure). The sum of EKE and EPE is total eddy energy (TEE), and its annual average distribution shows that the 1000–3000 m isobath to the west of Luzon Strait and the 1000– 3000 m isobath off the southeast coast of Vietnam exist high energy (Fig. 5.45c) (Zhuang et al. 2010). The high-value area of TEE exactly follows the path of the South China Sea throughflow from northeast to southwest and corresponds to the high-value areas of T2 and T4, which means that the throughflow area in South China Sea is accompanied by active mesoscale eddies, as well as the western boundary, southeastern Vietnam and the western part of the Luzon Strait are the areas where exist most strongly eddy-mean flow interaction, corresponding to the strongest barotropic and baroclinic instability.

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279

(b)

(a)

(c)

Fig. 5.45 The spatial distribution of the average annual vertical integrals EKE (a), EPE (b), and the spatial characteristics of TEE (color filling) and T2 + T4 (white contour) (c) (Zhuang 2008; Zhuang et al. 2010)

The seasonal change of TEE in shallow water areas are smaller while it in deep water areas is more significant as shown in Fig. 5.46. The TEE in the west of Luzon Strait (the northern rectangular area in Fig. 5.45c) reaches its maximum value in winter, decreases in spring, reaches its minimum value in summer, and then increases from autumn. In the offshore of southeastern Vietnam (the southern rectangular area in Fig. 5.45c), TEE reaches its maximum value in autumn, and decreases slightly in winter, but the magnitude is still considerable. TEE reaches its minimum value in spring, and its value in summer is slightly higher than that in spring. The center of high value area is near 11° N. The eddy energies in the two parallelogram regions in Fig. 5.45c above are averaged regionally respectively, and then the results from 2000 to 2006 are averaged over the climatological state for 5-day to obtain the seasonal characteristics of eddy energies and the energy conversion between eddy and mean flow in the two regions

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea

(a)

(b)

(c)

(d)

Fig. 5.46 The distribution of the seasonally averaged vertical integral TEE (Zhuang 2008)

(Fig. 5.47). In the west of Luzon Strait, TEE can reach 15 × 106 cm3 /s2 from January to February, then rapidly decreases in March, and drops to about 4 × 106 cm3 /s2 in August, increases slowly from September to October, and quickly increases to more than 10 × 106 cm3 /s2 from November to December. The energy conversion terms of mean flow to eddy caused by baroclinic and barotropic instability (T2 and T4) is consistent with the change trend of TEE. The high value area of T2 and T4 all appear on the east of the TEE’s high value area (white contour in Fig. 5.45c), the sum of the v ·∇TEE) (Fig. 5.47a). two (T2 + T4) is much larger than the advection term of TEE (→ Therefore, the high value of TEE near Luzon Strait is mainly caused by the changes in the path of Kuroshio intrusion into the South China Sea and the accompanying barotropic and baroclinic instability and propagates to the southwest following the mean flows or fluctuations. The advection term of TEE mainly affects the distribution of TEE in high value areas. Jia and Liu (2004), Jia et al. (2005) were the first to apply energy conversion accompanied by barotropic and baroclinic instability to explore the process and the mechanism of eddy shedding caused by the large bending of

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the Kuroshio mainstream invading the South China Sea near the Luzon Strait. Zu et al. (2013) studied the evolution of the warm eddy in the southwest Taiwan and found that the energy transport from mean flow to eddy caused by the barotropic and baroclinic instability of the Kuroshio invasion is the main energy source for the eddy evolution (Fig. 5.48a), although the change in wind stress intensity corresponds to the growth and decay of eddy, the contribution of wind stress directly work on the eddy kinetic energy (EKE) is weaker than that of T4 (Fig. 5.48b). And as seen from T4 and the work done by wind stress (Table 5.1) during the warm eddy formation period in southwest Taiwan from October and November 1993 to 2006, the mean flow input energy to the eddy through the barotropic instability (T4) is always greater than the energy directly obtained by wind stress (WW). Therefore, it is not difficult to infer that the change of the strength of northeast monsoon has triggered the change of Kuroshio mainstream intrude into the South China Sea and the barotropic and baroclinic instability, the energy conversion caused by instability is the direct factor of the formation of eddy, and wind stress work indirectly affects the formation of eddy. The anticyclonic eddy on the west of Luzon Strait can either continue to move southwest along the continental shelf slope of the northern South China Sea under the advection of the background circulation driven by the monsoon (Zu et al. 2013), or it can propagate southwest in the form of Rossby waves (Wang et al. 2008a). Wang et al. (2008a) studied the development process of two anticyclonic eddies in the northern South China Sea during the winter of 2003–2004, showed that the instantaneous velocity of eddy and eddy intensity are changing during their southward along the western boundary of the South China Sea, it implies that the eddy and the mean flow have a complicated interaction process. On the one hand, the eddy’s energy dissipates during the southwestward movement in the northern South China Sea, or the eddy kinetic energy transfer to the background mean flow through T4 (Yuan et al. 2006); on the other hand, the eddy energy may be supplied from T4 because of the instability of background flow. For the offshore of Vietnam offshore, TEE increases rapidly in autumn and reaches its maximum value at the end of November; TEE decreases rapidly in winter, from the beginning of December to the end of February of the following year, roughly from 1.5 × 107 to 8 × 106 cm3 /s2 , which is about half smaller; in spring and summer, it decreases slowly and remains stable respectively (Fig. 5.47b). The trends of T2 and T4 are roughly the same as TEE. Chu et al. (2014) studied the cause of the abnormal strong Xisha eddy in the spring of 2010 and found this anticyclonic eddy originated from the southeastern Vietnam, which is different from the warm eddies generated locally in Xisha or them propagated from the northeastern South China Sea. A strong Central Pacific El Niño event occurred from 2009 to 2010 caused an atmospheric anticyclonic circulation anomaly above the northwest Pacific in summer (Wang et al. 2006a; Xie et al. 2009), which weakened the intensity of summer monsoon of the eastern and southern South China Sea, enhanced the intensity of summer monsoon in the northwestern South China Sea. Therefore, the western boundary current north of 13° N in southeastern Vietnam changed from a weaker southward current to a stronger northward one (Fig. 5.49). This northward anomalous flow formed in May, reached its strongest in July, and weakened in September, meanwhile, the anticyclone eddy

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Fig. 5.47 Variation of the horizontal advection terms (T + adv) of the 5-day climatological average of TEE, T4, T2, and TEE over time of two parallelogram area in Fig. 5.45c (Zhuang et al. 2010). a The west of Luzon Strait; b Southeast Vietnam

along the coast of Vietnam was brought by this flow to the adjacent area of Xisha, and finally merge with a weaker anticyclonic eddy southwestward along a continental slope area of the northern shelf of South China Sea. From the perspective of the whole life cycle of eddy energy budget (Fig. 5.50), TEE has been increasing during the period from May to July. In detail, before the onset of the summer monsoon, T2 is mostly positive from May to June, which means that the mean flow transfers energy to the eddy through baroclinic instability. During the strongest summer monsoon, the sudden increase of T4 from June to July means that the mean flow transfers energy to the eddy through barotropic instability, and T4 suddenly weakens when the two eddies met and merge. After that, with the weakening and reversing of the monsoon and the boundary current, the eddy gradually weakened, and its TEE gradually decreased. The interaction process between these eddies and large-scale circulations mostly occurs in the strong current area on the western boundary of South China Sea. Through the study of the eddy’s lifetime, it is found that the eddy not only propagate along the path of the mean flow, but also accompanied with energy conversion between mean flows in the evolution.

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Fig. 5.48 Variations of the time integral terms of TEE and T2 + T4 (a) and changes in wind stress (WW) and T4 (b) during the evolution of the anticyclonic warm eddy in southwest Taiwan from October to November 2006 (Zu et al. 2013) Table 5.1 T4 and wind stress work WW during the formation period of Taiwan southwest warm eddy from October and November in 1993 to 2006 (unit: 10−5 m3 /s3 )

Years

T4

1993

1.7

0.01

1995

0.96

0.13

1996

1.1

0.16

1997

1.6

−0.02

2000

0.81

2001

1.6

−0.44

2002

1.2

0.4

2003

1.2

0.08

2004

0.78

0.31

2005

5

1.6

2006

0.82

0.34

WW

0.14

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Fig. 5.49 The structure of wind field and current field (Chu et al. 2014). a Climatology (gray arrow) and wind speed from June to August in 2010 (black arrow) and the difference between them (shading). The closed solid green line represents the edge of the eddy on June 1, 2010. b Same as a but is the distribution of average current field at a depth of 10 m

5.2.1.3

Eddy Induced Transport in the South China Sea

The ocean plays an important role in the global heat balance, and the contribution of mesoscale eddies cannot be ignored. Chen et al. (2012) found that due to the strong mixing of the upper ocean and the small gradients of temperature and salinity in the deep ocean, the thermal and salinity transport caused by eddies mainly occurred in the thermocline and halocline through analyzing the mesoscale eddies observed by altimeter, CTD and Argo data (Fig. 5.51). And due to the barrier layer, the halocline is significantly shallower than the thermocline, so the near-surface salinity transport is still comparable. Since the vertical structure of the mesoscale eddy is not symmetrical about the eddy center, there is a net transport in the meridional direction. Using parametrization, Chen et al. (2012) further revealed the characteristics of eddy transport at the basin scale of South China Sea. Larger poleward eddy induced heat transport occurs in the eastern Vietnam in summer and the western Luzon Island in winter, while large equatorial eddy induced heat transport occurs in the western Luzon Strait in winter (Fig. 5.52). As the temperature tends to decrease from the equator to polar, the eddy induced heat transport is mainly poleward in the South China Sea. The equatorial eddy induced heat transport in the western Luzon Strait in winter is mainly caused by Kuroshio intrusion, which causes the temperature gradient reversing in this area. The spatial distribution of eddy induced salinity transport similar with eddy induced heat transport, but mainly present equatorial

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Fig. 5.50 The daily variations of TEE, T2 and T4 during the lifetime of the eddy from February to October in 2010 (Chu et al. 2014). The gray area indicates the date when the north and south eddy met and merged in Xisha

transport. Because the salinity distribution in the upper layer of South China Sea mainly decreases equatorially, and it may attribute to the South China Sea water mass originating from the Pacific water mass. Theoretical demonstration shows that the seasonal variation of the South China Sea eddy induced thermohaline transport is controlled by the baroclinic instability of the background flow. In winter, due to the weak shear, baroclinic instability occurs in the western Luzon Strait, which increases the eddy kinetic energy in this area, thereby significantly increasing heat transport. The instability in the western Luzon Island is mainly caused by the strong shear in winter. Because eastern Vietnam is located in a low latitude area and the strong stratification in summer, the baroclinic instability in this area comes from strong shear of local currents.

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0

Depth(m)

-200

-400

-600

(a) -800

5

4

3

2

1

0

1

2

3

4

5

3

4

5

Heat T ransport(×10 6Wm -2) 0

Depth(m)

-200

-400

-600

(b) -800

5

4

3

2

1

0

1

2 -2 -1

Salt T ransport(kgm s ) Fig. 5.51 Vertical characteristics of heat and salinity transport in the eddy influenced profile (Chen et al. 2012). The gray lines in the figure are the characteristics of each hydrological profile; the black solid line is the average result; the black dashed line is twice variance of the mean value; the dotted line represents the location of the thermocline and halocline. Positive values represent northward transportation, and negative values represent southward transportation

5.2.2 The Ecological Effect of Eddy 5.2.2.1

The Characteristics and Mechanism of Mesoscale Eddies Influencing Biogeochemical Cycles

As a relatively independent fluid, the impact of mesoscale eddies on the ocean biogeochemical cycle has received widespread attention. The impact of mesoscale eddies on the biogeochemical cycle process depends on the level of nutrients and biomass in the water body captured by the eddy during its formation. At the same time,

5.2 Physical and Ecological Effects of Mesoscale Eddy … Heat Transport(106 W/m)

24

-5

5 -5

5

-5

-5 0

-5

10 8

-5

105

110 -20

-5 -5

0

-5

5

6

0

12

5

8

-5

14

0

10

-40

0

0

-5

12

-5

0

-5

14

16

-5

0 0

0

16

18

-5

-5

-5

18

05

0

20

20

-5

-5

22

-5

22

S alt Transport(kg/ms)

0

24

287

6 115 0

105

120 20

40

-30

110 -20

-10

115 0

10

120 20

30

Fig. 5.52 The spatial distribution of climatological eddy induced thermohaline transport in the South China Sea (Chen et al. 2012)

there are complex horizontal and vertical motions in the life of an eddy, which also reaccommodate nutrients and biomass, thereby affecting the ocean biogeochemical cycle process. There are several mechanisms for the influence of mesoscale eddies on biogeochemical processes, including eddy pumping, Ekman pumping under eddy/wind interaction, horizontal advection, and sub-mesoscale processes. Eddy pumping means the process of forming an upwelling or downwelling in the eddy by uplifting or suppressing the potential density surface during the formation stage. It is known as the first mechanism by which mesoscale eddies affect the biogeochemical cycle process. Earlier studies found that the production calculated based on the oxygen consumption of output biomass is larger than estimated in euphotic layer. The excess nutrients required for the actual production in euphotic layer may come from eddy pumping (McGillicuddy et al. 1998). In the cyclonic eddy, the potential density surface is uplifted, an upwelling is formed in the eddy, and the water body contain high nutrients under the euphotic layer uplifts and enters the layer, which is benefit to the growth of phytoplankton. In the anticyclonic eddy, the potential density surface is suppressed, a downwelling is formed in the eddy, and the water body contain high nutrients under the euphotic layer transport downward, reduced the biological activity of euphotic layer. The relative motion of wind and eddy surface flow produces wind stress, and lead to vertical movement called Ekman pumping under eddy/wind interaction (McGillicuddy et al. 2007; Siegel et al. 2011; Gaube et al. 2013). When a uniform wind passes through the eddy, it interacts with the surface flow and produces a curl opposite to the eddy. Studies have shown that Ekman pumping caused by the eddy/wind interaction is one of the possible mechanisms for the vertical motion of

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea

mesoscale eddy. The interaction produces downwelling inside the cyclonic eddy, and on the contrary, produces an upwelling in anticyclonic eddy, and its scale can reach 1 m/d under strong wind field (Martin and Richards 2001). In the mesoscale eddy ecological observation around Northeast Atlantic, McGillicuddy et al. (2007) found that the diatom bloom phenomenon inside the mode water mesoscale eddies is different from the generation mechanism of cyclonic eddies. The phenomenon is related to the wind speed passing through the eddy surface. It confirms that Ekman pumping under the eddy/wind interaction can generates upwelling in the anticyclonic eddy and promote the occurrence of algal blooms. In Southern Indian Ocean, surface chlorophyll data was obtained by analyzing remote sensing data, and the ecological response under the mechanism was also observed and confirmed (Gaube et al. 2013). Due to the horizontal advection effect of eddy, when the eddy passes through a water body with a nutrient gradient or phytoplankton concentration gradient in horizontal direction, the eddy transports the high-concentration water into lowconcentration area and transport the low-concentration water body into highconcentration area. Through the synthetic analysis of abnormal surface chlorophyll concentration, the level of eddy readjustment has been proved to have an important influence on the distribution of chlorophyll concentration (Chelton et al. 2011). Sub-mesoscale process refers to a process in which the horizontal scale is 1– 10 km, the time scale is O(1d), and the Rossby number is O(1). Numerical simulations show that the vertical motion generated by sub-mesoscale process can reach 100 m/d, which is larger than the Ekman pumping speed under the eddy/wind interaction (Martin and Richards 2001; Mahadevan and Tandon 2006). The generation of sub-mesoscale process may be due to the strengthening of the horizontal density gradient, the instability of the mixed layer, or the enhanced vertical movement after the nonlinear Ekman transport across the front caused by the wind along the front (Legal et al. 2007; Fox-Kemper et al. 2008; Thomas et al. 2013). Earlier the simulation works on the sub-mesoscale and mesoscale processes generated by baroclinic jets found that the sub-mesoscale processes enhanced the primary productivity of phytoplankton (Lévy et al. 2001). Then some studies have found that the sub-mesoscale process can not only temporarily increase the nutrient content of euphotic layer, but also prolong the residence time of phytoplankton in the euphotic layer, thereby increasing the resistance time and thus increasing the primary production (Lévy et al. 2012; Mahadevan et al. 2012). The biogeochemical cycle response of mesoscale eddy in the South China Sea has also received widespread attention. Chen et al. (2007) first reported the ecological effects of cold eddies in the South China Sea. They captured the cold eddy shedding from Kuroshio into South China Sea in the navigation sampling on the east and west sides of the Luzon Strait. Comparing the cold eddy with the stations representing the interior of the South China Sea and the source of Kuroshio, it was found that nutrients, primary productivity, chlorophyll and other biological parameters in surface and euphotic layer of the cold eddy are significantly higher than the sampling points of stations in South China Sea and the Kuroshio source area. Through the simulation analysis of the coupled physical-biogeochemical cycle model, the process of cyclonic eddies enhancing phytoplankton reproduction and anticyclonic

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289

eddies inhibiting phytoplankton reproduction is also reproduced. The observation and simulation support the idea that eddies in the South China Sea have an important influence on the biogeochemical cycle process (Xiu and Chai 2011). There are also some related studies on the other mechanisms of ecological effects of mesoscale eddies in the South China Sea. Studies have also found that when the shape of the anticyclonic eddy in the South China Sea is consistent with the wind direction, the surface chlorophyll concentration is higher, and the wind speed has great correlation with the chlorophyll concentration. It implied that the eddy/wind interaction may lead to increasing the chlorophyll concentration inside the anticyclone eddy in the South China Sea, and the interaction is affected by the shape of eddy and the direction of wind speed (Li et al. 2014a). The research on the ecological effects of sub-mesoscale processes in South China Sea is still lacking at present. In the nutrient-poor sea area of South China Sea, the inspection of the radioactive 234 Th current found that the downward output of 234 Th inside the anticyclonic eddy was 1.6–1.9 times higher than that of the non-eddy occupied area. Numerical simulation experiments believe that the radioisotope originates from the edge of eddy. In the strong sub-mesoscale process, the particles generated by biological activities at the edge of eddy greatly increase and transported to the middle of eddy under horizontal convection. This study indirectly illustrates that the influence of sub-mesoscale processes in the South China Sea on the biogeochemical cycle may be important (Zhou et al. 2013). In addition to the mechanism of spatial influence, the life cycle changes of mesoscale eddies affect the internal biogeochemical variables. Through synthetic analysis of the biogeochemical variables of all cyclonic eddies in the South China Sea simulated by the high-resolution coupling model ROMS-CoSiNE, they found that the physical variables (sea level anomaly SLA), biological variables (microphytoplankton S1, diatoms S2) and chemical variables (silicate SiO4 , nitrate NO3 ) in cyclonic eddies all show different time-varying processes (Guo et al. 2015). Taking phytoplankton as an example, microphytoplankton reaches its extremum earlier than that of diatoms, while the time variation curve of diatoms is coupled well with the change of physical process SLA. At the same time, due to the predation competition, when the diatoms concentration reaches highest value, the amount of microphytoplankton is very small, sometimes even lower than the background concentration outside the cyclonic eddy. The output concentration of particulate matter (particulate nitrogen DD, particulate silicon DDSi) presents a high value during a certain part of the eddy life cycle and is relatively low or lower than the background field at other times. Therefore, the in-situ observation become important for a mesoscale eddy. The eddy exhibits different biogeochemical characteristics during its growth, maturation, and extinction period.

5.2.2.2

The Impact of the South China Sea Eddy on the Ecosystem

Due to the influence of Kuroshio intrusion, monsoon and terrestrial rivers in the northern South China Sea, the variability of its biogeochemical processes is largely related to mesoscale processes in the ocean. Huang et al. (2010) studied the ecological

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea

effects of the warm eddy on the west side of Luzon Strait shedding from the Kuroshio and the warm eddy generated in the northern South China Sea based on the sea level anomaly data from the satellite altimeter, the drifter data and the in-situ observation data and do the comparison. The survey also measured the phytoplankton chlorophyll concentration and phytoplankton population structure outside the warm eddy and found that the water body inside the warm eddy has lower nutrient content than surrounding, and the total chlorophyll concentration of the water body has not obvious change compared with the background field. However, the phytoplankton population structure showed obvious differences. As shown in Fig. 5.53, the phytoplankton in the euphotic layer of warm eddy formed by Kuroshio intrusion is mainly composed of prochloron; while the phytoplankton is mainly composed of flagellates in the warm eddy formed locally in the northern South China Sea affected by the coastal waters. Using satellite data to track the development of these mesoscale eddies, it is found that the differences in the structure of phytoplankton populations within these eddies are mainly determined by the source of mesoscale eddies and the period of the warm eddies during observation. Different structure of the phytoplankton population under the influence of warm eddy plays an important role in the ocean carbon cycle process since it has different effects and efficiencies on the cycle of carbon, nitrogen, phosphorus, and other elements in the water body. Phytoplankton blooms occur every winter in the northwestern Luzon Island. Using satellite remote sensing data to obtain sea surface temperature, sea surface wind speed, chlorophyll concentration and model simulation depth of the mixed layer, Zhao et al. (2012) found that high chlorophyll concentration is usually accompanied by high subsurface water temperature, high sea surface wind speed, high vertical entrainment acceleration and strong vertical Ekman pumping and other environmental factors, and the chlorophyll concentration is related to and have good correlation with these factors on the interannual scale. Based on the statistical correlations, Zhao et al.’s (2012) further study showed that the vertical Ekman pumping caused by wind and the mixing and stirring of the vertical structure of the water body may be the main factors leading to the high chlorophyll concentration in northwestern Luzon in winter (Fig. 5.54). As a relatively strong mesoscale process, typhoons also have a significant impact on the ecosystem structure of upper ocean in the northern South China Sea. Zhao et al. (2013) studied two phytoplankton blooms in the northern South China Sea. One of them occurred near Dongsha Island and was on the path of Tier-II Typhoon Nuri. The bloom began to form one week after Nuri passed the area, and the chlorophyll concentration in the core area reached 0.5 mg/m3 . Through satellite and in-situ observation data, the study found that the sea surface temperature in the area dropped by about 3 °C after the typhoon passed, accompanied by strong wind speed (>20 m/s) and rainfall (>100 mm/d). The changes of environmental factors and the rapid increase of phytoplankton concentration confirm that the upwelling and vertical mixing caused by typhoons can bring sufficient nutrients for the growth of phytoplankton, which are the main factors of bloom occurrence. Considering that multiple typhoons occur every year and passing through the South China Sea, they will have a non-negligible impact on nutrients transport and phytoplankton growth.

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291

Fig. 5.53 The concentration of total chlorophyll a (a) and the proportions of diatoms (b), prochloron (c) and flagellate (d) in all phytoplankton observed in the northern South China Sea in winter 2003/2004 (Huang et al. 2010). The center of warm eddy caused by Kuroshio invasion is about 20.5° N, 116.5° E, and the center of warm eddy formed locally in the northern South China Sea is about 19.5° N, 113.5° E

Chen et al. (2014) studied the roles of physical and ecological effects in the water bloom phenomenon in eastern Vietnam, respectively. In the past, it was believed that the water bloom in the eastern Vietnam was caused by upwelling which caused high nutrients to promote ecological development. However, the research of Chen et al. (2014) showed that the advection transport of water bodies caused by boundary currents and mesoscale eddies in the western South China Sea is the key factor for the occurrence of water bloom in the region. Advection directly transports the high concentration chlorophyll along the coast to the eastern Vietnam (Fig. 5.55) and transports high nutrients and zooplankton there at the same time. Although high nutrients are beneficial to the growth of phytoplankton, high predation inhibits the increase of chlorophyll. Studies have shown that the ecological effect has a negative net contribution to the water in the eastern Vietnam, which is the reduction of chlorophyll. As the distance from the shore increases, the high predation rate caused by advection decreases, and the ecological effect plays an important role in the maintenance of the chlorophyll tongue on the offshore.

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea

Fig. 5.54 The relationship of monthly average sea surface chlorophyll concentration (Chl-a) and sea surface temperature (SST), mixed layer depth (MLD), Ekman pumping velocity (EPV), sea surface wind speed (SP) and vertical entraining speed (EV) (Zhao et al. 2012)

5.3 Near-Inertial Energy Characteristics of the South China Sea Under the Influence of Mesoscale Eddies The near-inertial oscillation phenomenon of upper ocean mainly driven by wind is widespread in the global ocean (Pollard and Millard 1970). Near inertial kinetic energy (NIKE) accounts for half of the kinetic energy of the ocean surface (Pollard and Millard 1970), which is important for maintaining strong mixing in the mixed layer (D’Asaro 1985), deep ocean mixing and internal waves (Gill 1984), etc. The background vorticity field can modulate the near-inertial frequency, making the local Coriolis frequency a significantly shifted (Kunze 1985). The active anticyclonic eddies in the ocean play an important role in the vertical transport of Nike (Young and Jelloul 1997). The South China Sea is the largest deep-water marginal sea in the Northwest Pacific, and the dynamic process is complex. The East Asian monsoon

5.3 Near-Inertial Energy Characteristics of the South China Sea …

293

Fig. 5.55 Concentration distribution of chlorophyll synthesized on 8d from 2002 to August 2011 (Chen et al. 2014). Due to cloud cover, each sub-picture shows the situation of the most extensive period of satellite data coverage in August each year. The arrow represents the corresponding geostrophic

transition has a significant impact on the shape and the changes of circulation in South China Sea (Su 2001), and may also stimulate significant NIKE. The South China Sea is also an area where typhoons are frequently active, typhoons from the Western Pacific and the local will inevitably lead to significant near-inertial oscillations in the South China Sea. At the same time, the mesoscale eddy phenomenon in the South China Sea is active (Wang et al. 2003; Yuan et al. 2007; Hu et al. 2011), and significantly impact the redshift and blueshift of the near inertial frequency, the strength and the dissipation period of NIKE and the propagation of near-inertial waves.

5.3.1 Near-Inertial Energy Characteristics of the Xisha Islands Under the Influence of Mesoscale Eddies and Typhoons NIKE shows obvious seasonal changes. Using the submarine buoy data, Silverthorne and Toole (2009) pointed out that NIKE in the North Atlantic is significantly stronger in winter than other seasons. Based on a model that only retains the depth integrals of the wind-driven term and the dissipation term, they successfully simulated the characteristics of NIKE amplitude and its seasonal changes in the region. Park et al. (2005) used drifter to statistically study the characteristics of near-inertial oscillations in the North Pacific, Southern Ocean, and other regions, and pointed out that the amplitude of near-inertial oscillations in summer is 15–25% higher than that in winter. The near-inertial amplitude of the Caspian Sea reaches 14 cm/s, and it is

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5 Mesoscale Eddy and Mesoscale Process in the South China Sea

Fig. 5.56 A near-inertial oscillation event lasting a month under the influence of mesoscale eddies from August to September 2007 (Chen et al. 2013). The color represents NIKE

almost twice as large in summer as in winter. Using more than 3 years of submarine buoy observation data, Chen et al. (2013) studied the seasonal variation of NIKE in the northwestern South China Sea and the strong near-inertial oscillation events during the observation (NIKE is greater than one standard deviation). The results showed that the significant NIKE on the subsurface (30–450 m) occurred in autumn (defined as August–October). All strong near-inertial oscillation events are strongly induced by past tropical storms, and most of their e-folding time scales exceed 7 days. Furthermore, Chen et al. (2013) systematically studied the phase velocity, vertical wavelength, frequency redshift and blueshift of the strong near inertial oscillation events. During the observation period, the largest NIKE occurred in April 2008 and was induced by Typhoon Neoguri. Orthogonal modal analysis showed that the first four baroclinic modes controlled the vertical distribution of NIKE, which is, NIKE is large in surface or deep ocean and small in 30–70 m (Fig. 5.56). Mesoscale eddy and vorticity fields can significantly affect the propagation of near-inertial waves and have an important impact on the vertical transport of Nike. The near-inertial waves in the mixed layer are more easily captured by the negative vorticity field region and propagate rapidly to the thermocline, while the near-inertial waves in the positive vorticity region mainly enhance vertical velocity shear and entrainment cooling (Jaimes and Shay 2010). The reflection of the near inertial wave induced by the vorticity field causes horizontal variation, which controls the vertical propagation of the near inertial wave (Danioux et al. 2008). The active anticyclonic eddies in the ocean play an important role in the vertical transport of NIKE (Young and Jelloul 1997). They can transmit NIKE from the mixed layer to the deep ocean like a “chimney” (Lee and Niiler 1998), leading to near inertial waves reflected inside the eddy (Byun et al. 2010). Based on numerical simulation studies, Zhai et al. (2005) compared the vertical propagation of NIKE energy in the Southern Ocean under the influence of cyclones and anticyclones and pointed out that anticyclones can significantly promote the propagation of NIKE from the mixed layer to the deep layer, which verified Lee and Niiler’s (1998) results. Observation shows that by means of turbulent dissipation and wave radiation, most NIKE is dissipated in one week (Park et al. 2009). Zhu and Li (2007) studied the near-inertial oscillations in the northern shelf of the South China Sea after typhoon Wayne in 1989 by using submarine buoy data, pointed out that the impact of typhoon transit on local seawater motion can lasted 6–8 d. In the near-inertial oscillation event that occurred in Xisha

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in August 2007 (Fig. 5.56), the e-folding time scale of NIKE reached 13.5 days; and its NIKE not only propagated toward the seabed, but also propagated toward the sea surface (Chen et al. 2013). Chen et al. (2013) used submarine buoy data to study and pointed out that the subsurface NIKE, which is mainly controlled by high modes, lasts longer than the surface Nike and is significantly affected by the anticyclonic eddy. Combined with the ray-tracing model, Chen et al. (2013) pointed out that the enhanced vertical velocity shear and weakened stratification caused by an anticyclonic eddy in the same period caused the near-inertial wave reflected inside the vortex, thus making NIKE persistent and spread to different direction. Although NIKE is driven by wind, the complex propagation and distribution of NIKE are actually controlled by the different water structure characteristics caused by various ocean processes.

5.3.2 Strong Near-Inertial Oscillations Caused by the Onset of Monsoon and Mesoscale Eddies in the South China Sea The tropical cyclone Mirinae formed in the western North Pacific on October 26, 2009 as tropical depression (TD), and then moved westward. It entered the South China Sea after crossing the Philippines at 0:00 a.m. on October 31, 2009, and its intensity from typhoon (TP) before reaching the Philippines attenuated to severe tropical storm (STS). After that, it crossed the South China Sea to the west and attenuated into a tropical storm (TS) when it was closest to the observation point at 0:00 a.m. on November 2, 2009, and finally disappeared in the southern Vietnam in the early morning of November 3, 2009 (Fig. 5.57). Fig. 5.57 The path of tropical cyclone Mirinae (Wan et al. 2015). The pink asterisk is the location of observation point; the thin solid line is isobath (m); the dot line is the location of Mirinae every 6 h, the color represents its intensity (refer to the legend), the red cross is the position that TC is closest to the observation point

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Mirinae possess the characteristics of low intensity, high moving velocity, and is far away from the observation point (star position in Fig. 5.57), its intensity is not enough to stimulate significant near-inertial oscillation at the Xisha observation point (Wan et al. 2015). What factors caused the significant near-inertial oscillations in Xisha area? Studies have shown that when Mirinae was active in the South China Sea, during the South China Sea prevailing winter monsoon, the observation site was controlled by the strong northeast monsoon. During the movement of Mirinae, the northerly wind was basically the same as the direction of northeast monsoon. The two merged and strengthened the northeast monsoon. At the same time, the direction of northeast monsoon also changed due to the westward movement of Mirinae. This change also altered the wind field above the observation point that is mainly controlled by the northeast monsoon, as shown in Fig. 5.58a, d. The Ekman flow driven by the wind above the observation site calculated by the damped-slab model and the near-inertial flow in the mixing layer are shown in Fig. 5.58g. The model results show that Mirinae produced a strong Ekman flow at

Fig. 5.58 Time series of wind vector above the observation site in 2009 and calculation results of damped-slab model (Wan et al. 2015). Time series of wind vector: original (a); after 10-day smoothing (b); the difference between a and b (a minus b) (c). Time series of wind speed: original (d); after 10-day smoothing (e); the difference (f). Time series of speed: original (g); after 10-day smoothing (h); the difference (i). Observed mean near-inertial currents in the mixed layer are also shown as the dashed line in g. The red solid vertical line shows the moment for the nearest location of Mirinae to the observation site

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the observation site, with a maximum value close to 0.4 m/s, and a significant nearinertial flow, with a maximum value close to 0.2 m/s. The result is morphologically in good agreement with the result of anchoring ADCP (shown by the dotted line in Fig. 5.58g, which gives the average value of the observed near-inertial flow in the mixed layer). However, due to some shortcomings of the damped-slab model itself (the simulation is mainly the forced phase, and the relaxation phase after being forced cannot be simulated) and the complexity of the real ocean, the simulated value is lower than the observed value (the maximum value is about 0.5 m/s). It can be inferred that Mirinae produces significant near-inertial oscillations at the observation site, which is closely related to changes in the local wind field. After smoothing the time series of wind field data above the observation site in 2009 for 10 days (Mirinae’s lifetime is close to 8 days in history, take 10 days to smooth it to deduct the fine scale impact on the wind field), and intercept the time series during the study period and drawn in Fig. 5.58b, e, the result after inputting the damped-slab model is shown in Fig. 5.58h. It can be seen that the wind-driven Ekman flow and near-inertial flow under the influence of Mirinae have a slight increase trend but not large, and the maximum value is about 0.05 m/s. The analysis shows that the Ekman flow and the near-inertial flow generated by a single tropical cyclone or the northeast monsoon are weak, but the coupling of the two produces a strong Ekman flow and a more significant near-inertial current. In brief, under the coefficient of the tropical cyclone Mirinae and the winter monsoon, significant near-inertial oscillations occurred in the northwestern South China Sea. Compared with the previous references that studied tropical cyclones inducing significant near-inertial oscillations, although Mirinae is far from the observation site, weak in intensity, and with fast moving speed, it also induced significant near-inertial oscillations at the observation site. The analysis results show that when Mirinae traversed the South China Sea from east to west, the northerly wind merges with the prevailing northeast monsoon, which enhances the wind speed of northeast monsoon and changes its direction, making the wind field above the observation site changed in strength and direction, which is mainly controlled by the northeast monsoon, and the wind speed vector has been deflected clockwise over time, which produced significant near-inertial oscillations in observation site. During the 1998/1999 South China Sea monsoon test period, when the summer monsoon onset was observed by the submarine buoy, a strong near-inertial oscillation was excited in the middle of the South China Sea basin, and the near-inertial velocity reached 0.25 m/s, its intensity was equivalent to the energy of the near-inertial oscillation excited by typhoon. However, during the onset of summer monsoon, the wind speed is significantly lower than that of typhoon, how is the strong near-inertial oscillation triggered? It is found through numerical sensitivity experiments that the shallow mixed layer depth and the varying wind speed and direction are beneficial to stimulate strong near-inertial oscillations in the mixed layer. Before the onset of summer monsoon, the mixed layer depth in South China Sea is unusually shallow (less than 30 m). The changing wind field during the onset period can excite relatively strong near-inertial oscillations in the thin mixed layer. Research based on the ray-tracing model shows that the strong warm eddy (warm pool) existing in the

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Fig. 5.59 Eddy and NIKE observations (Shu et al. 2016). a The distribution of sea surface height and geostrophic flow from May 21 to June 1, 1998, of which M1–M3 are the observation sites of the submarine buoy. b The sea surface height and geostrophic flow distribution from June 1 to 10, 1999. c 20–170 m average NIKE observed by M2 submarine buoy. d NIKE observed by M1 submarine buoy (blue line) and M3 submarine buoy (green line)

central part of the South China Sea in this season ‘trapped’ near-inertial energy transmitted from the surrounding to the eddy (Fig. 5.59), thus the near-inertial oscillation energy in the middle of the South China Sea basin is much higher than the nearinertial energy observed by the submarine buoy in the southern and northern South China Sea. In summary, the three factors of changing wind field, thin mixed layer thickness and mesoscale warm eddy are the main reasons for the strong near-inertial oscillations observed in the central part of the South China Sea during the onset of the 1998/1999 summer monsoon. Using HYCOM’s 3 h reanalysis data, we have further confirmed that strong near-inertial oscillations will also occur in the central South China Sea when the summer monsoon onset in many years. The thickness of mixed layer in the South China Sea is always thin in spring, and spring warm eddies can appear in most years. Therefore, strong near-inertial oscillations can often be observed in the negative vorticity region of the central South China Sea when the summer monsoon onset.

5.4 Summary and Prospect In this chapter, in the aspect of the South China Sea middle water mass and circulation, the distribution characteristics of the South China Sea middle water and its correlation with the water exchange in the Luzon Strait are reviewed, by using the observational data, it is pointed out that the middle water of the South China Sea has significant interannual and interdecadal variations. Aiming at the separation flow in the middle

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layer of Dongsha in autumn, the POM model is used to numerically simulate the separation flow, and it is pointed out that the negative center of the joint effect of baroclinicity and relief (JEBAR) is the key factor driving the middle layer flow of Dongsha. In the aspect of deep-water mass and circulations in the South China Sea, the relative progress of the source of deep water in the South China Sea and the basic characteristics of the deep circulations in the South China Sea is summarized from observation and simulation. Using multiple sets of global high-resolution ocean model data, the basic characteristics of the deep and bottom circulations in the South China Sea are analyzed, and it is pointed out that the difference of model topography can obviously cause the change of circulation intensity, then constructed a diagnostic model of bottom current considering the influence of tides and mesoscale eddies. In terms of the deep Meridional Overturning Circulation in the South China Sea, the structural characteristics of the South China Sea Meridional Overturning Circulation (SCSMOC) are studied based on HYCOM reanalysis data. It is believed that the inflow of the Luzon Strait is the main driving source of the SCSMOC, and is pointed out that the high-frequency variability of the wind field near the Luzon Strait plays an important role in the near-inertial variation of the meridional overturning circulation in the South China Sea. Some progress has been made in the research on the mid-deep circulation at present, but there are still some problems that have not been solved. (1) The research results on the deep circulation and meridional overturning circulation in the South China Sea are almost all based on numerical models or diagnostic models for now. Except for certain observational studies on the deep circulation in the Luzon Strait, there is no direct observation of the deep circulation in the South China Sea. Therefore, it is urgent to carry out corresponding deep hydrological observations. (2) The three-layer circulations in the South China Sea are not independent but interconnected. It is currently unknown how the momentum, vorticity, heat, and salinity of the three-layer circulations are exchanged in what way and on what scale, and how this exchange of material and energy affects their maintenance and variation is still unclear. To solve these problems, in addition to strengthening in-site observations, it is also necessary to theoretically consider the role of factors such as tidal mixing, topography, vertical water exchange, and surface atmospheric pressure in driving the three-layer circulations. (3) Using the reflection seismic method to infer the bottom flow channels in the South China Sea, marine geologists have achieved fruitful research results. Combined with more high-precision reflection seismic data and with the help of finer deep-water sedimentary systems, it is possible to infer the large-scale circulation pattern of the South China Sea in previous years and the small-scale circulation in the inner trough and seamounts of the South China Sea, which can further enhance the understanding of the deep circulation in the modern South China Sea, and understanding of the meridional overturning circulations.

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Wang XD, Li W, Qi YQ et al (2012b) Heat, salt and volume transports by eddies in the vicinity of the Luzon Strait. Deep Sea Res Part I Oceanogr Res Pap 61:21–33 Wang Q, Zeng LL, Zhou WD et al (2014) Mesoscale eddies case study at Xisha waters in the South China Sea in 2009/2010. J Geophys Res Oceans 120(1):517–532 Wu CR, Shaw PT, Chao SY (1998) Seasonal and interannual variations in the velocity field of the South China Sea. J Oceanogr 54(4):361–372 Wu CR, Shaw PT, Chao SY (1999) Assimilating altimetric data into a South China Sea model. J Geophys Res Oceans 104(C12):29987–30005 Xian T, Sun L, Yang YJ et al (2012) Monsoon and eddy forcing of chlorophyll-a variation in the northeast South China Sea. Int J Remote Sens 33(23):7431–7443 Xie SP (2003) Summer upwelling in the South China Sea and its role in regional climate variations. J Geophys Res 108(C8):3261 Xie SP, Chang CH, Xie Q et al (2007) Intraseasonal variability in the summer South China Sea: wind jet, cold filament, and recirculations. J Geophys Res 112(C10):C10008 Xie SP, Hu K, Hafner J et al (2009) Indian Ocean capacitor effect on Indo-Western Pacific climate during the summer following El Niño. J Clim 22(3):730–747 Xiu P, Chai F (2011) Modeled biogeochemical responses to mesoscale eddies in the South China Sea. J Geophys Res Oceans 116:C10006 Xiu P, Chai F, Shi L et al (2010) A census of eddy activities in the South China Sea during 1993–2007. J Geophys Res Oceans 115(C3):C03012 Xu XZ, Qiu Z, Chen HC (1982) An overview of the horizontal circulation in the South China Sea. In: Editorial office of “ocean and limnology”. Proceedings of the 1980 conference of the Chinese society of marine limnology and hydrometeorology. Science Press, Beijing (in Chinese) Xue HJ, Bane JM (1997) A numerical investigation of the Gulf Stream and its meanders in response to cold air outbreaks. J Phys Oceanogr 27(12):2606–2629 Xue HJ, Mellor G (1993) Instability of the Gulf Stream front in the South Atlantic bight. J Phys Oceanogr 23(11):2326–2350 Yang HJ, Liu QY (1998) The seasonal features of temperature distributions in the upper layer of the South China Sea. Oceanol Limnol Sin 29(5):501–507 (in Chinese) Yang HJ, Liu QY (2003) Forced Rossby wave in the northern South China Sea. Deep Sea Res Part I Oceanogr Res Pap 50(7):917–926 Young WR, Jelloul MB (1997) Propagation of near-inertial oscillations through a geostrophic flow. J Mar Res 55(4):735–766 Yuan DL, Han WQ, Hu DX (2006) Surface Kuroshio path in the Luzon Strait area derived from satellite remote sensing data. J Geophys Res Oceans 111(C11):C11007 Yuan DL, Han WQ, Hu DX (2007) Anti-cyclonic eddies northwest of Luzon in summer-fall observed by satellite altimeters. Geophys Res Lett 34(13):L13610 Zhai XM, Greatbatch RJ, Zhao J (2005) Enhanced vertical propagation of storm-induced nearinertial energy in an eddying ocean channel model. Geophys Res Lett 32(18):L18602 Zhang Y, Sintes E, Chen JN et al (2009) Role of mesoscale cyclonic eddies in the distribution and activity of Archaea and Bacteria in the South China Sea. Aquat Microb Ecol 56(1):65–79 Zhang ZW, Zhao W, Tian JW et al (2013) A mesoscale eddy pair southwest of Taiwan and its influence on deep circulation. J Geophys Res Oceans 118(12):6479–6494 Zhang YW, Liu ZF, Zhao YL et al (2014) Mesoscale eddies transport deep-sea sediments. Sci Rep 4:5937 Zhao H, Sui DD, Xie Q et al (2012) Distribution and interannual variation of winter phytoplankton blooms northwest of Luzon Islands from satellite observations. Aquat Ecosyst Health Manage 15(1):53–61 Zhao H, Han GQ, Zhang SW et al (2013) Two phytoplankton blooms near Luzon Strait generated by lingering Typhoon Parma. J Geophys Res Biogeosci 118(2):412–421 Zhong HL (1990) Density circulation structure. In: Ma YL, Xu SG, Zhong HL (eds) A 10-year hydrographic survey report on the adjacent waters of the northern shelf of the South China Sea. Ocean Press, Beijing (in Chinese)

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Chapter 6

Air-Sea Interaction in the South China Sea

6.1 Variation Characteristics of Sea Surface Temperature for the South China Sea Sea surface temperature (SST) is an important indicator of thermal state of the upper ocean, an important factor in the air-sea coupled system, and a sensitive index of climate change. The study of SST variation has become one of the crucial topics in the research of global change and regional climate. In recent years, significant progress has been made, which was to study the effects of the ocean on some important weather systems, atmospheric circulation, climate change and other aspects by using SST, and remarkable results that have been applied to mid-long term weather forecast and operational weather change forecast have been achieved. The temperature variation of the South China Sea has almost all the time-scale changes of the tropical ocean, such as diurnal, intra-seasonal, interannual and interdecadal variations.

6.1.1 Diurnal and Intra-seasonal Variations of Sea Surface Temperature for the South China Sea 6.1.1.1

Diurnal Variation of SST for the South China Sea

Due to the forcing of the sun, the most basic changes are diurnal and seasonal variations in the global climate system. As the most basic variation of climate system, diurnal variation has become the key to verify the correctness of numerical model, and it is of great significance to improve the existing calculation schemes of sea and air flux. However, in the past, due to the lack of high temporal resolution data, it was difficult to study the diurnal variation of sea surface temperature (SST). In 1998, the three ATLAS fixed-point buoys launched in the South China Sea summer monsoon test provided high temporal resolution SST data for the study of the diurnal variation of SST, which made it possible to study the diurnal variation © Science Press and Springer Nature Singapore Pte Ltd. 2022 D. Wang, Ocean Circulation and Air-Sea Interaction in the South China Sea, Springer Oceanography, https://doi.org/10.1007/978-981-19-6262-2_6

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of SST. Zang (2005) took the multi-day average of SST data at three stations within 10 days before and after the onset of South China Sea summer monsoon in 1998 at the same time point and calculated the variance of each time point. The results are shown in Fig. 6.1. Obviously, before the onset of the summer monsoon, SST presents diurnal variation pattern with distinct peaks and valleys. Before the onset of the summer monsoon, the maximum of multi-day average SST at site SCS1 was 30.76 °C at 18:00; the minimum of that was 30.11 °C at 9:00. The maximum of that at station SCS2 was 30.99 °C at 15:00; the minimum of that was 30.49 °C at 7:00. The maximum of that at station SCS3 was 30.95 °C at 15:00; the minimum of that was 30.36 °C at 7:00. Due to the small variation of SST at the same time every day before the onset of summer monsoon, the variance is also small. After the onset of summer monsoon, the diurnal variation curve of SST was relatively flat without obvious peak value. After the monsoon onset, the maximum of the multi-day average SST at SCS1 was 30.12 °C at 18:00; the minimum was 29.70 °C at 9:00. The maximum of that at SCS2 was 30.69 °C at 14:00; the minimum of that was 30.53 °C at 24:00. The maximum of that at SCS3 was 30.23 °C at 00:00; the minimum of that was 30.05 °C at 23:00. After the onset of the summer monsoon, the diurnal variation of SST at SCS2 and SCS3 sites became irregular and the variance increased significantly. Comparing the diurnal variation curves of SST before and after the onset of the summer monsoon, the SST of the three buoy stations in the South China Sea had an obvious peak-valley structure before the onset of the summer monsoon, and the energy in the 24 h period was large, presenting regular diurnal variation pattern. After the onset of summer monsoon, the amplitude of SST decreased, and the energy in the 24 h period decreased, presenting irregular diurnal variation. Before the onset of summer monsoon, SST was in a warming state. After the onset of summer monsoon, the upper ocean is in a state of heat loss and SST decreases. Before the onset of summer monsoon, there is less cloud cover, and the heating effect of solar radiation on SST is dominant, the solar short-wave radiation has obvious diurnal variation, the heat exchange between ocean and atmosphere and the dynamic process of the ocean layer are relatively stable, SST shows regular diurnal variation. After the onset of summer monsoon, the heating effect of solar radiation on the sea surface is blocked because of the enhancement of convection and the increase of cloud cover. At the same time, due to the onset of summer monsoon, the latent heat flux increases, and the one-dimensional thermal balance related to the development of SST changes, but this process is generally not enough to maintain the diurnal variation range of sea surface temperature and sea air flux before the onset, and SST presents irregular diurnal variation. During the whole study period, the surface heat flux has a decisive effect on the variation of SST. Before the onset of summer monsoon, the variation of SST is dominated by solar shortwave radiation, followed by latent heat flux. After the onset of summer monsoon, the contribution of latent heat flux to the variation of SST is increasing, followed by solar shortwave radiation. On the diurnal scale, the horizontal advection heat transport has a good correlation with the variation of SST, but has little influence on SST. The entrainment can cause a short-term cooling of SST, but the number of occurrences during the study period less, little contribution to SST.

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Fig. 6.1 Daily mean SST and its variance at SCS1, SCS2 and SCS3 of the three stations on 10 days before and after the onset of summer monsoon (The fine solid line is before the onset of monsoon. The rough line is after the onset of the monsoon)

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The intra-seasonal variation of SST in the South China Sea

The contribution of tropical SST intra-seasonal variation to annual scale variation is up to about 50% (Jones et al., 1998), which plays a pivotal role in the impact and predictability of climate change, and has therefore attracted much attention in the past decade. In the tropics, the South China Sea has a unique topography and winter, and the winter and summer monsoon activities here are the most significant. Due to the lack of observational data, there are relatively few studies on the intra-seasonal variation of SST for the South Asian monsoon region. By using the traditional Fourier transform, Zhou and Ding (1995) estimated the power spectrum of the observation data from several stations located in the northern part of the South China Sea for only half a year (May to October 1985), and found that there was a significant intraseasonal variation of SST in the South China Sea. The intra-seasonal variation of SST in the South China Sea is a strong signal. In the intra-seasonal scale, if the SST variation is spatially different, it will have an inhomogeneous heating effect on the atmosphere, thus affecting climate change. The SST results of Gao (2002) at the central basin of the South China Sea (113.5° E, 11.5° N) were analyzed by wavelet analysis. Both the wavelet energy spectrum (Fig. 6.2b) and the total wavelet spectrum (Fig. 6.2c) passed the significance test of 95% confidence in the seasonal frequency band (30–90 days). Therefore, there is no doubt that the SST in the South China Sea has significant intra-seasonal variation. The wavelet energy curve of the intra-seasonal scale average (Fig. 6.2d) shows that the intra-seasonal variation of SST in the South China Sea also has annual variation and inter-annual variation. The seasonal mean energy variation of SST is stronger in summer half year and weaker in winter half year. In addition, there is a significant cycle change of 2–4 years. The basic characteristics of intra-seasonal variation and the physical process of SST for the South China Sea have significant monsoon characteristics. Lag correlation analysis shows that there is a significant lag correlation between summer SST disturbance and the variation of 850 hPa zonal wind and Outing Longwave Radiation (OLR) convective variation associated with ITCZ in the intra-seasonal scale. In winter, SST intra-seasonal disturbances of China Sea are mainly related to the intra-seasonal activities of 850 hPa meridional winds. The average lag time is 5– 10 days. In summer, the spatial correlation pattern of intra-seasonal variation of SST is quasi-zonal for the South China Sea and adjacent monsoon regions, which is related to the spatial correlation pattern of intra-seasonal 850 hPa zonal wind anomalies. In winter, the spatial correlation pattern of intra-seasonal variation of SST of the South China Sea was quasi-meridional and related to the spatial correlation pattern of intra-seasonal scale meridional wind, and the correlation center was limited to the South China Sea, which indicated that the intra-seasonal variation of SST was more independent than that in summer. The EOF analysis shows that the intra-seasonal variation of SST over the South China Sea in summer has a significant meridional propagation characteristic from south to north, which is a response to the meridional propagation of the summer monsoon, and the propagation velocity is about 1 m/s. The intra-seasonal variation of SST of the South China Sea in winter is mainly a local

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Fig. 6.2 Morlet wavelet analysis results of SSTA (1982–1997) in the central basin of South China Sea (11.5° N, 113.5° E) (Gao 2002) a Standardized SSTA sequence at (11.5° N, 113.5° E); b Wavelet power spectrum (W.P.S), the range within the contour line indicates over 95% confidence test; c Global wavelet spectrum (G.W.S.) and 95% confidence level (95% C.L.); d 30–90 day Scale average wavelet power (S.A.W.P.) and 95% confidence level (95% C.L.)

oscillation phenomenon with quasi-standing wave characteristics, which is related to the intra-seasonal variation of the winter monsoon system (Gao et al. 2000; Gao and Zhou 2002). The intra-seasonal variations of SST for The South China Sea in summer and winter are both direct responses to the changes of SST net heat flux with the same lag time of 5–10 days. Simultaneously, under different monsoon setting, the physical process that affects the net heat flux of sea surface is different. In summer, the southwest monsoon is prevailing over the South China Sea, and the main components controlling the intra-seasonal variation of the net heat flux of the sea surface are latent heat transport and solar short-wave radiation anomalies, which are mainly determined by the local and intra-seasonal convective anomalies in the South China Sea (Fig. 6.3). In the convective area, there is an anomaly of 850 hPa westerly wind above the south of the center, which strengthens the mean westerly wind and the evaporation of sea surface, that is, the latent heat flux transported increase from ocean to atmosphere. In addition, due to the existence of strong convection and cyclonic circulation anomaly,

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Fig. 6.3 Physical block diagram of intra-seasonal variation of SST in the South China Sea in summer (Gao 2002)

the solar short-wave radiation obtained from sea surface is reduced. The combined effect of the two causes a negative anomaly in the net heat flux at the sea surface, and the SST decreases accordingly. On the contrary, in the convective suppression zone, there is an east 850 hPa wind anomaly above south of the center, which weakens the mean westerly wind and the evaporation of the sea surface, that is, the latent heat flux transported decreases from ocean to atmosphere. Meanwhile, due to the weak convective activity and the existence of anticyclonic circulation anomaly, the solar shortwave radiation obtained from the sea surface is increased. The combined effect of the two causes a positive anomaly in the net heat flux at the sea surface, and the SST rises accordingly. The northeast monsoon prevails over the South China Sea, in winter, main components that control the intra-seasonal variation of net heat flux at the sea surface are the anomalies of latent heat transport and sensible heat transport, which mainly depends on the intra-seasonal variation of the 850 hPa meridional wind and is related to cold surge activities (Fig. 6.4). When the 850 hPa southerly anomaly occurs over the South China Sea, the cold surge activity is relatively small and weak, and the mean northerly wind weakens, which reduces the sea-air temperature difference and the sea-air vapor pressure difference, and the sensible heat flux and latent heat flux transported from the ocean to the atmosphere, and the net heat flux of the sea surface shows positive anomaly, resulting in SST increasingly. On the contrary, when there is the 850 hPa northly wind anomaly over the South China Sea, relatively frequent and strong cold surge activities at this time, the mean northly wind strengthens, which increases the sea-temperature difference and the sea-air vapor pressure difference, both heat flux and latent heat flux increased from ocean to atmosphere correspondingly, the net heat flux of SST showed negative anomaly, resulting in SST decreasingly.

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Fig. 6.4 Physical block diagram of intra-seasonal variation of SST in the South China Sea in winter (Gao 2002)

6.1.2 Interannual and Longer Time Scales 6.1.2.1

Response of SST in the South China Sea to El Niño

El Niño, as a global climate event originating in the equatorial Pacific Ocean, has been the focus of the world’s meteorologists and oceanographers since its discovery. Through such factors as atmospheric circulation and ocean circulation, El Niño signal affect the ocean changes in the South China Sea. Although the South China Sea is a warm pool structure, SST in the South China Sea has obvious inter-annual variation characteristics. (1) Two peaks structure of SST Inter-annual variation in the South China Sea Analyzing the SST anomaly sequence in the year and the following year of the typical El Niño event in South China Sea, it is found that the inter-annual variation of SST in the South China Sea has an obvious two peaks structure. The SST of the South China Sea experienced two warming phenomena in February and August the following year after the El Niño event (Fig. 6.5), which were the result of the combined effects of atmospheric forcing and ocean circulation (Wang et al. 2006). The heat budget diagnosis of the mixed layer in the South China Sea during the El Niño event was carried out to evaluate the relative contributions of net heat flux, advection heat transport and vertical heat mixing to South China Sea SST anomalous two peaks structure. The first peak is caused by the net heat flux anomaly, while the short-wave radiation and latent heat flux anomaly play a dominant role (Fig. 6.6). After the first warming, the net heat flux weakened, and the negative anomalies of Ekman and geostrophic heat transport made the surface of South China Sea cool. The second peak occurred in August after the end of El Niño in the following year, advection heat transport was main factor causing the warming, and meridional geostrophic heat transport played a key role.

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Fig. 6.5 The South China Sea SSTA sequence in the year and following year of typical El Niño event (Wang et al. 2006) [0] represents the year of El Niño event; [+1] represents the year after the El Niño event

Fig. 6.6 Composite analysis of heat budget diagnosis in November of typical El Niño event

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Fig. 6.7 Response mechanism of SST in the South China Sea to the East/Central Pacific type El Niño event (Liu et al. 2014)

(2) Response of the South China Sea SST to East Pacific and Central Pacific El Niño events With the continuous attention to El Niño events, recent studies began to focus on the response of SST in the South China Sea to different El Niño events. For the two different El Niño phenomena of the East Pacific (EP) and the Central Pacific (CP), it is found that the characteristics of SST variation in South China Sea are different (Liu et al. 2014). During these two El Niño events, through heat balance diagnosis analysis, it is found that the largest difference of SST in the South China Sea is shown in the autumn of El Niño development period and controlled by the net heat flux, the eastern Pacific type El Niño is positive SST anomaly, while the central Pacific type El Niño is negative SST anomaly (Fig. 6.7). Affected by autumnal SST anomaly, after the Mid-Pacific El Niño event, the South China Sea can only show a semi-basin warming feature confined to the western boundary region, and it is difficult for the entire South China Sea basin to warm up during the East Pacific El Niño event, and the warming in the western boundary is controlled by the geothermal advection. In addition, the quasi-biennial variation of SST is ± type in the central Pacific type El Niño, while the annual variation of SST is ± / ± type in the eastern Pacific type El Niño, and the corresponding low SST phase in the eastern Pacific type is locked in late autumn. In general, the change of net heat flux is consistent with the SST period. For the Central Pacific type El Niño, in addition to the change in heat flux, the mean Ekman advection anomaly is almost consistent with variation period of SST (Fig. 6.8).

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Fig. 6.8 Parameter synthesis analysis of two El Niño events (Liu et al., 2014) a Sea surface temperature anomaly (SSTA); b Sea surface temperature change (dSST); c Net heat flux (Qnet ); d Mean Ekman advection anomaly. [0] represents the year of El Niño event; [+1] represents the year after the El Niño event

(3) The fall of the South China Sea SST to El Niño, El Niño Modoki I and El Niño Modoki II incident response Recent research show that after the global climate experienced a significant jump in the late 1970s, the frequency of El Niño events decreased, and a phenomenon similar to El Niño appeared with a trend of more frequent occurrence. Ashok et al. (2007) named it El Niño Modoki. Compared with the typical El Niño, the occurrence of El Niño Modoki has a unique impact on the global ocean and atmosphere. According to the different effects on autumn precipitation in southern China, Wang et al. (2013) further divided El Niño event into traditional El Niño, El Niño Modoki I and El Niño Modoki II. In the autumn of these three types of El Niño events, the SST of the South China Sea showed different characteristics (Tan et al. 2016). In the autumn of traditional El Niño and El Niño Modoki I, the South China Sea SST characterized by the abnormal heating, while El Niño Modoki II year autumn showed cold anomaly (Fig. 6.9). The heat budget analysis of SST in the South China Sea shows that the change of latent heat flux is the main reason for the SST change in the South China Sea. Observation and CAM4 model results show that in the autumn of the traditional El Niño and El Niño Modoki I, anticyclonic circulation anomalies appear over the Philippine

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Fig. 6.9 Distribution of autumn SST anomalies (°C) in South China Sea (Tan et al. 2016) Areas enclosed by white contours represent significant test exceeding 90% confidence

sea in the eastern South China Sea, which makes the South China Sea affected by the abnormal southerly winds, weakens the average autumn northeast monsoon and reduces the northeast monsoon of latent heat flux, that is, the South China Sea the heat released into the atmosphere, make the SST anomaly heating. In the autumn of El Niño Modoki II, anomalous anticyclonic circulation moved westward to the western part of the South China Sea, causing anomalous northerly winds over South China Sea, strengthening the northeast monsoon climate state, increasing release of latent heat, reducing the SST of the South China Sea. In addition, because South China Sea is affected by abnormal anticyclones in the autumn of these three types of El Niño events, which suppresses convective activities over South China Sea and increases shortwave radiation, so the traditional El Niño and El Niño Modoki I in shortwave radiation heating, but to El Niño Modoki II, shortwave radiation heating value is lower than latent heat radiation values, which eventually caused SST of South China Sea to drop.

6.1.2.2

Long-Term Variations of SST in the South China Sea Recorded by Coral

Coral in the tropical ocean is a good proxy of climate record, which can indirectly measure the physical and chemical characteristics of the environment. Now they has been widely used in the study of palaeoclimate change. SST and SST salinity data reconstructed from coral skeletons have been extensively used to study climate change by establishing the relationship between the ratio of 18 O/16 O in corals and temperature. Research on corals in South Coast has shown that coral growth rates are highly linearly correlated with SST (Wang et al. 2010b). As one of the important meteorological elements, cloud cover can directly affect the radiation balance, heat balance and temperature and humidity distribution of the

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earth-atmosphere system, and can participate in a variety of positive and negative feedback processes in the climate system. In terms of changes of local cloud cover in the South China Sea, the cloud cover is relatively less from February to April, generally less than 50%. After the establishment of summer monsoon, the cloud cover gradually increases, and gradually decreases from January. In contrast, the gray value of corals was lower in summer and higher in winter, which indicated that the light low-density zones with large gray value grew in winter, while the dark high-density zones with small gray value grew in summer. It was consistent with the research results of Su and Sun (2003) on the growth characteristics of coastal corals in the northern the South China Sea. In conclusion, there is a negative correlation between the climate characteristics of coral growth and cloud cover, and the gray scale records of the shore coral can be directly used as a reliable indicator of cloud cover change over the South China Sea and even tropical seas. As an index of coral density, coral gray value is related to the comprehensive quality of coral growing environment, including SST, precipitation and sunshine. The annual average SST in the northern part of the South China Sea has an obvious positive correlation with the gray scale of corals. The correlation coefficient between the two is 0.14 (n = 123), which exceeds the significance test level of 90% confidence. Therefore, SST is a very important environmental variable that affects coral density changes. In Fig. 6.10, coral grayscale basically reappears the long-term change trend of SST in the South China Sea. After 1880, SST of the South China Sea showed a warming trend, while coral grayscale showed a decreasing trend.

6.1.3 Upper Mixing Layer/Barrier Layer and Sea Surface Temperature Change The change of sea-air flux and the agitation of wind and waves make the water layer with certain thickness and uniform characteristics in the near surface layer of the ocean, which is called the ocean mixed layer. The vertical changes of temperature, salinity and density in the ocean mixture layer are small, and the average temperature is close to SST. The thermal dynamics of mixed layer in the South China Sea has obvious marginal sea characteristics (Wang et al. 2001), especially during the summer monsoon, the transformation of mixed layer responds more significantly to the southwest monsoon. Compared with other tropical sea areas, the mixed layer in the South China Sea is much thinner. The mixed layer of the South China Sea is influenced by the typical monsoon system and Kuroshio invasion (Qu 2001; Liu et al. 2004; Gan et al. 2006).

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Fig. 6.10 Changes of coral gray scale, global temperature and CO2 concentration (Wang et al. 2010b) a Grayscale time series of coral in Yongxing Island (solid gray line). The rough solid line is the annual average gray value, and the straight line is mean value from 1789 to 1992. b Long-term trend of coral gray level (coarse solid line), annual mean global temperature anomaly (1882–1992, dotted line) and long-term trend (fine solid line). The long-term trend of gray level and temperature is obtained by singular spectrum analysis. c Changes in atmospheric CO2 concentration from 1800 to 1992

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Characteristics of the Upper Mixed Layer in the South China Sea

Shi et al. (2001) and Du (2002) found that the ocean mixed layer is closely related to the large-scale circulation, the monsoon through time and space distribution of mixed layer flow field have important influence, on the one hand, through the ocean surface Ekman transport effect to influence the level of mixed layer distribution, on the other hand through the large scale circulation caused by the divergence or convergence to restrict or promote the development of mixed layer depth. In addition, research found that wind stress, net heat flux absorbed by sea surface and fresh water flux on sea surface are the main factors that determine the structure characteristics of heat content or temperature distribution in mixed layer, of which wind stress plays the most significant role. Based on South China Sea fused observation dataset SCSPOD14, Zeng et al. (2016), the climate state distribution of the mixed layer was given in the South China Sea. The annual mean depth of the mixed layer has two deep cores, one at the continental shelf area from the Luzon Strait to the northern part of the South China Sea, and the other at the depth center from the southwest side of the Philippine Islands to the northwest side of Kalimantan. There are two shallower zones of mixing depth, one off the east coast of Vietnam and the other off the west side of the northern Philippine Islands. The depth of the mixed layer in the South China Sea has significant seasonal variations (Fig. 6.11). In January, the mixed layer near the continental shelf slope of the northern South China Sea reaches the deepest, and the depth of the mixed layer becomes shallow from north to south. In the southern the South China Sea, the depth of the mixed layer is 30–40 m. With the weakening of the northeast monsoon, the wind stress agitation could not provide enough vertical turbulent kinetic energy, and the deep mixed layer could not be maintained throughout South China Sea. In March, only the depth of the mixed layer near the Luzon Strait was more than 50 m, and in the inner the South China Sea, the mixed layer showed a bowl-like structure with a deep center and a shallow edge, which was consistent with the anticyclonic distribution characteristics of the flow field in the same period. In April and May, the South China Sea entered the monsoon transition period, and the mixed layer continued to become shallower. In April, the mixed layer of the entire South China Sea was less than 35 m, and the mixed layer of the bowl of the South China Sea shifted southward in March. In May, the mixed layer of the South China Sea reached minimum and the heat obtained from the atmosphere was limited to the shallow surface layer which is consistent with the existence of a spring warm pool in the South China Sea. With the onset of the summer monsoon, the mixed layer of the South China Sea firstly deepen in the south. In June, the depth of the mixed layer was greater than 35 m, and the mixed layer here continued to deepen from July to September. The depth of the mixed layer in the South China Sea in summer is asymmetrically distributed: a straight line is formed from the southeast corner of Vietnam to the south of Taiwan Island, and the two sides of the line show completely different characteristics. In the northwest sea area above the line, the mixed layer is shallow. In the northwest sea area, the depth of mixed layer is less than 40 m,

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Fig. 6.11 Climate state distribution of the depth of mixed layer in the South China Sea based on SCSPOD14 observation dataset (Zeng et al. 2016)

which is the shallowest in the entire South China Sea. In September and October, the northeast monsoon began to prevail, and the mixed layer in the northern part of the South China Sea gradually deepened. In December, the northeast monsoon developed fully. In the sea area south of 10° N, the depth of the mixed layer was greater than 50 m. However, the mixed layer is not deep in the entire the South China Sea area, there is a shallow center of the mixed layer west of Luzon Island.

6.1.3.2

Influence of the South China Sea Barrier Layer on the SST of the Mixed Layer

In the mixed layer, the temperature, salinity, and density of the water are very uniform, and the isothermal layer was used to define the mixing depth in earlier studies. As observations have been made, oceanographers have found that in the upper layers of the ocean, the isothermal and isopensity layers are not always the same. When oceanic salinity changes, the barrier layer is created between the mixed layer of the ocean (consistent with the isosalt layer) and the upper boundary of the thermocline. The existence of barrier layer strengthens vertical stratification and inhibits downward transfer of heat, momentum and matter from sea surface. Pan et al. (2006a) used observation data in the northern part of the South China Sea to point out that the occurrence probability of obstacle layer is relatively high in the Luzon Strait and the northeastern central area of the South China Sea. Pan et al. (2006b) used observation data of the central the South China Sea, pointed out that precipitation mechanism and the southeast Ekman advection transport were the reasons for the multiple occurrence of barrier layers in the sea area west of Luzon Island in summer, and heavy precipitation was the key to the generation of barrier layers in the southeast sea area of Indo-China Peninsula in summer. Zhu and Qiu (2002) pointed out that the barrier layer in the southern the South China Sea is the

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shallowest in spring, the deepest in summer, and gradually becomes shallower in autumn and winter. The seasonal mean of barrier layer thickness in this sea area is not large, ranging from 12 to 25 m. Based on the South China Sea observation datasets SCSPOD14, Zeng et al. (2016) gave the climate state distribution of the South China Sea barrier layer (Fig. 6.12). The barrier layer of South China Sea is the most widespread and deepest in summer and autumn. In addition to seasonal changes, the barrier layers of various sea areas also show significant spatial changes. From November to February of the following year, the barrier layer of the South China Sea mainly appeared in the southern sea area and the western boundary current area in the northern part of the South China Sea, but they were all shallow and less than 10 m. During the monsoon transition from March to May, the barrier beds were distributed in blocks only in some sea areas and appeared the least. After the onset of summer monsoon, the barrier layer in the South China Sea increased rapidly and showed obvious asymmetrical distribution, which was consistent with the asymmetrical distribution of thermocline and mixed layer depth. Similar to the annual mean distribution characteristics, the barrier layer in summer and autumn is widely distributed in the southeast basin, and reaches the thickest in September, which is greater than 20 m. In addition, the Luzon Strait and the western seas of the Philippine Islands also produced barriers greater than 15 m during this period. In October, the barrier layer in the South China Sea, though covering the entire ocean basin, it was weaker than in September. After entering winter, the barrier layer begins to decay rapidly. Figure 6.13, during the summer monsoon, the surface water accumulated toward the southeastern part of the South China Sea driven by the southwest monsoon. On the east side of the South China Sea, the high mountain topography of the Philippine Islands controls the very abundant rainfall in the area, and accumulations of lowsalinity water on the ocean surface form a fresh water cap effect, which strengthens the salinity stratification of the upper ocean. On the west side of the South China Sea, the leeward side of the Annan Mountains on Indo-China Peninsula breeds the upwelling zone on the west side of the South China Sea, and the corresponding rainfall holes contribute little to the input of surface freshwater. The significant difference in rainfall distribution caused by this mountainous terrain results in the different east–west distribution characteristics of the barrier layer in the South China Sea: the barrier layer on the east side is deep and widely distributed, while the barrier layer on the northwest side does not exist. The freshwater discharge of the Mekong River in summer provides sufficient sources of fresh water for the sea area near the mouth of the Mekong River. When the western boundary flows northward, freshwater is carried to the inner South China Sea, while the western boundary flows off the shore induced by the southeast anticyclonic vortex of Vietnam. The combined effect will bring about sinking motion. The freshwater cap caused by the advection effect then floats on the deep thermocline, forming a deep and stable barrier layer, which has not received due attention in previous studies. In the central part of the Luzon Strait, the local rainfall and the surface fresh water transported to Ekman from the east overrun the high temperature and high salt water of Kuroshio bending into the channel. The

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Fig. 6.12 Deep climate state distribution of barrier layer in the South China Sea based on SCSPOD14 fusion observation dataset (Zeng et al. 2016)

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Fig. 6.13 Schematic diagram of barrier layer maintenance mechanism in the South China Sea during summer monsoon (Zeng et al. 2009)

two different water bodies meet to form a shallow halocline, thus generating the barrier layer here. For the South China Sea, the barrier layer may be closely related to the formation of warm water and local abnormal warming of the South China Sea due to its unique air-sea feedback characteristics. The lower the salinity in the mixed layer and the shallower the mixed layer, the deeper the barrier layer; the deeper the barrier layer, the more obvious the inhibitory effect on vertical heat transfer and the warmer the upper mixed layer. But it’s not that the deeper the barrier, the stronger the warming effect. In the South China Sea, the influence of the barrier layer on the temperature of the mixed layer can be divided into two stages: when the thickness of the barrier layer is less than 32 m, the temperature of the mixed layer in the South China Sea increases as the thickness of the barrier layer increases, however, when the thickness of the barrier layer is greater than 32 m, It no longer has a significant warming effect on the temperature of the mixed layer. The influence of the barrier layer on the upper ocean heat content is continuously increasing.

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6.2 The Sea-Atmosphere Interface and Boundary Layer in the South China Sea 6.2.1 Research on the Fluxes at the Sea-Air Interface The air-sea flux exchange is a key link in the air-sea interaction. The process of interaction between ocean and atmosphere is initially realized by the flux exchange at the air-sea interface. On the one hand, the ocean affects the ocean-atmospheric boundary layer through sensible and latent heat exchange processes, provides water vapor transport, and then affects the atmospheric circulation; on the other hand, most of the driving force of sea water movement also comes from the momentum flux exchange at the sea-air interface. The sensible heat flux, latent heat flux and radiation flux at the interface are important factors that affect the upper mixed layer of the ocean and even the seasonal thermocline, while the momentum flux is the drive of ocean currents and waves. The air-sea flux exchange first affects the movement of the upper ocean and the distribution structure of temperature and salinity, and then further affects the movement of the deep seawater through the thermal and dynamic adjustment process inside the ocean. Therefore, the air-sea flux exchange is one of the important mechanisms of climate change. For climate change and its prediction on the seasonal to interannual time scale, it is possible to be solved only on the basis of fully understand the interaction between atmosphere and ocean and its dynamics. With the development of oceanography and meteorology, the ocean and atmosphere have been studied as a coupled system. The momentum, energy, and mass fluxes at the air-sea interface are the only way to realize the interaction between ocean and atmosphere. Therefore, the observation of air-sea fluxes has received more and more attention. The climatic change characteristics of air-sea flux and its relationship with climate change are the difficulty and focus of the current research on the interaction between different circles in the current climate system. The heat flux at the air-sea interface includes solar short-wave radiation, ocean and atmosphere long-wave radiation (long-wave radiation upward from the ocean and long-wave radiation downward from the atmosphere), latent heat flux and sensible heat flux, as well as reflected radiation from the sea surface. Among them, shortwave radiation and latent heat flux are predominant. The transport of latent heat flux and sensible heat flux not only has an important impact on the large-scale air-sea interaction process, but is also the key to climate change. Clarifying the characteristics of heat exchange at the sea-atmosphere interface in the South China Sea plays an important role in understanding the mechanism of air-sea interaction in the South China Sea. At present, the observation of ocean heat flux is still lacking. The forcing of the South China Sea on the atmosphere is mainly reflected in the sensible and latent heat fluxes, especially the latent heat flux. When the ocean thermal field changes, the water vapor transport from the ocean to the atmosphere also changes. The variation of latent heat flux is small before monsoon onset, but increases after monsoon onset. During the precipitation process, the latent heat flux is significantly reduced due to

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the high humidity, and its larger value generally occurs during the southwest wind and monsoon interruption period (Yan 1999; Yan et al. 2007). In order to accurately quantify the sea-atmosphere flux in the South China Sea, flux observation towers were set up respectively in Nansha Islands and Xisha reef island within the 1994 project ‘Spratly Islands and its adjacent offshore area comprehensive survey’ and the 1998 project ‘South China Sea Monsoon Experiment’ (SCSMEX). In order to systematically understand the weather evolution process before and after the onset of the southwest monsoon in the South China Sea, accurately quantify the flux exchange between the ocean and the atmosphere (sensible heat, latent heat, net ocean heat budget) before and after the monsoon onset, and study the relationship between the spatiotemporal changes of air sea flux exchange and energy transfer and the development of the South China Sea monsoon, as well as the summer precipitation in China, we set up the subject of ‘Study on the characteristics of air sea flux during the onset of South China Sea Summer Monsoon and its impact on the occurrence and development of weather system’ in the SCSMEX. The National Natural Science Foundation of China (NSFC) has successively supported the general projects of ‘Observation and Research on the flux and turbulence structure in the near surface layer during the onset of the South China Sea monsoon’ (2001–2003), ‘Research on the variation of air sea flux and its impact on the monsoon during the southwest monsoon period of the South China Sea’ (2006–2008). With the support of the above-mentioned projects, the South China Sea Institute of Oceanology, Chinese Academy of Sciences has carried out three flux experiments in Xisha sea area (1998, 2000, 2002), and obtained the data of wind, temperature and humidity gradients, radiation, wind speed, temperature and humidity fluctuations in the near sea layer from May to June in three typical years (late year of southwest monsoon onset in 1998, early year in 2000 and normal year in 2002). On the basis of observational experiments, the surface layer atmospheric turbulence structure before and after the onset of southwest monsoon is analyzed. The values of air sea heat, momentum and water vapor exchange are calculated. The characteristics of air sea heat exchange and the variation of exchange coefficient under different weather conditions are discussed. The exchange coefficient changes. In order to explore the time evolution characteristics of air sea heat flux in Xisha and Nansha areas, Wu et al. (2005) calculated the air sea heat exchange value and the annual cycle of sea surface heat budget before and after the onset of the South China Sea Summer Monsoon in 1998 using the observation data of ocean stations.

6.2.1.1

Field Observation of Heat Flux in the Northern South China Sea

During the on-site observation, the turbulence observation data are affected by the ship motion. In addition, the installation position of the equipment is unreasonable, the hull interferes with the atmospheric turbulence structure, and there is no equipment to record the left and right, back and forth sway and up and down bumping motion of the hull, so the influence of these motions on the sensor can not be removed. The results of latent heat flux and sensible heat flux calculated by eddy correlation

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method are not credible, but the average values of water vapor content, air temperature, wind speed and other data measured are correct. These data can be used to calculate latent heat flux and sensible heat flux through block dynamics formula. The study of air-sea heat flux in the South China Sea began in the late 1970s. In 1979, the South China Sea Institute of Oceanography conducted an observation of air-sea flux in the Central South China Sea survey to study the spring heat balance in the Nansha sea area (Zhang, 1998). It is pointed out that 25% of the solar shortwave radiation is transmitted to the atmosphere in the form of reflection and sea surface effective return radiation, and 40% is transmitted to the atmosphere in the form of turbulent sensible and latent heat between the sea and the air, during which the seawater is warming. From November 14–17, 1979, Zhang et al. (1986) conducted a study on the gradients of sea surface temperature, humidity, and wind in the Pearl River Estuary in the northern part of the South China Sea. They obtained turbulence data for the first time using vortex correlation technology on the Nansha Reef in September 1994, and analyzed and calculated the drag coefficient, momentum flux, sensible heat flux and latent heat flux of the Nansha sea area. It is found that the airsea sensible heat flux and latent heat flux are significantly different under different weather conditions in the Nansha sea area. Both are significantly greater during the winter monsoon and summer monsoon than during the monsoon intermission, indicating that the sensible heat flux and latent heat flux are dominated by wind speed (i.e. atmosphere). The ‘Special Project for Comprehensive Survey and Evaluation of my country’s Offshore Oceans’ (referred to as ‘Project 908’) from 2006 to 2007 implemented a large number of ship-based flux observations. Four investigation cruises were conducted in the summer and winter of 2006 and spring and autumn of 2007 respectively. The cross-sectional observations covered the sea area from coast to land slope. Each season there were 220 CTD large-scale observation stations. The key survey areas of marine hydrology and meteorology were set up in the sea area more than 60 m near the Pearl River Estuary. Near the Pearl River Estuary in the northern part of the South China Sea, the ocean features are complex and changeable, and the upwelling has obvious influence on the sea area. In the ‘908 Special’ survey, in addition to the conventional temperature, salinity and meteorological observations, we also carried out the observation of air-sea flux, solar radiation, navigation current and navigation automatic weather station. Based on the measured hydrometeorological data for four seasons from 2006 to 2007, Zhang et al. (2012) calculated the air-sea heat flux (latent heat flux, sensible heat flux and sea surface net heat flux) in the northern South China Sea, and gave the seasonal variation and spatial distribution.

6.2.1.2

Intraseasonal and High Frequency Variations of Latent Heat Flux in the South China Sea

The latent heat flux in the South China Sea has significant seasonal variation (Fig. 6.14) and interannual variation (Zeng et al. 2009), as well as strong intraseasonal oscillation and high-frequency variation (Zeng and Wang 2009). Based on the

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weekly satellite latent heat data, harmonic analysis and power spectrum analysis show that the latent heat flux in the South China Sea has significant seasonal variation. The seasonal variation of the latent heat flux in the South China Sea has two significant periods, 28–35 days and 49–56 days, respectively (Fig. 6.15). The monsoon activity in the South China Sea is closely related to the intraseasonal variation of latent heat flux. The intraseasonal variation of latent heat flux in winter is stronger than in summer, but different from that in summer. The amplitude of seasonal variation of latent heat change in winter and summer is 80 W/m2 and 35 W/m2 , respectively. In summer, the latent heat flux in the South China Sea has weak eastward and northward signals, while in winter it is like a standing wave (6–30 W/m2 ). The intraseasonal signal of latent heat flux in summer is mainly affected by the southwest monsoon, while in winter, it is closely related to wind speed and sea surface specific humidity. In order to discuss the influence of various relevant parameters on the intraseasonal fluctuation of latent heat flux, we selected typical events in summer and winter respectively to conduct synthetic analysis. The latent heat fluxes were

Fig. 6.14 Seasonal distribution of latent heat flux in the South China Sea (Zeng et al. 2009)

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Fig. 6.15 Harmonic analysis results of latent heat flux in the South China Sea (shaded area passes significance test) and power spectrum analysis results (Zeng and Wang 2009). The square in figure a is the analysis area

recalculated with SST, wind speed, and atmospheric specific humidity of filtered signals, and their influence on the seasonal variation of latent heat flux was evaluated. The intraseasonal variation of winter SST could weaken the intraseasonal signal of latent heat by 20%. Shinoda et al. (1998) also pointed out that this phenomenon also occurs in the western Pacific. By analyzing the sea surface and upper-air observation data of Paracel Islands automatic weather station, it is found that there is a strong synoptic scale disturbance process in the northern part of the South China Sea (Zeng et al. 2012). Power spectrum analysis shows that there are two peaks in the energy spectrum density of meteorological elements at sea surface and upper air, namely 5–8 days disturbance and 3–4 days disturbance (Fig. 6.16). The standard deviation of the 36-year weather scale disturbance from 1976 to 2011 shows that the weather scale disturbance of Xisha Station was the most active in August. On the interannual scale, the synoptic scale disturbances in the northern part of the South China Sea were closely related

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to El Niño. After the El Niño warm event, there were two active periods of synoptic scale disturbances, the first in the El Niño peak period, and the second in the summer of the extinction year. Compared with the summer of the El Niño development year, the synoptic scale disturbance, especially the 5–8-day disturbance, was more active in the summer in the extinction year. Based on the observation data from Paracel Islands automatic weather station and daily satellite latent heat data SCSSLH, it is found that the latent heat flux in the South China Sea has significant high-frequency change signals. The highfrequency variation of latent heat flux in the South China Sea is mainly a synopticscale disturbance with a period of 5–8 days. The monsoon activity in the South China Sea is closely related to the high-frequency change of latent heat that the highfrequency variation of latent heat in winter is stronger than in summer, but different from that in summer. The amplitude of seasonal variation of latent heat in winter and summer is 40 W/m2 and 20 W/m2 respectively. The high-frequency change of latent

Fig. 6.16 Power spectrum distribution of observation elements of automatic weather stations in Xisha Islands (Shi et al. 2015a)

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heat in the South China Sea in summer is mainly affected by the southwest monsoon. When the high-frequency signal of wind speed is erased, the change of latent heat is advanced by about one day. In winter, when the high-frequency signal of atmospheric specific humidity is erased, the high-frequency fluctuation characteristics of latent heat are greatly weakened, with a decrease of more than 50% (Shi et al. 2015a).

6.2.1.3

Remote Sensing Calculation and Evaluation of Latent Heat Flux in the South China Sea

(1) Accuracy verification of atmospheric specific humidity parameterization For the evaluation of air-sea heat flux, the most critical item is the latent heat flux which is generated by evaporation. Seawater evaporation is not only an important means for the exchange of water and heat between the ocean and the atmosphere, but also a major factor determining the balance of water, heat, and salinity at the air-sea interface. Therefore, understanding and accurately calculating sea surface evaporation is helpful to clarify the relationship between the salt content of seawater and ocean currents, and reveal the inherent laws of marine air-mass degeneration and atmospheric circulation. At present, there is no good method for the direct measurement of evaporation. Many evaporation instruments have been designed, but most of them can only be measured in a small space. Commonly used evaporation instruments are mainly various types of water surface evaporators, soil evaporators and soil lysimeters. The water surface structure and surrounding conditions in the pan affected by the hull are very different from the actual sea conditions, and the evaporation is also lack of representativeness. Satellite sensors have great potential for flux exchange observations at the ocean–atmosphere interface. For a long time, meteorologists have devoted themselves to describing the physical elements of the entire layer of air column with the meteorological elements of the sea surface, because the observations are much easier at the sea surface layer. Based on the monthly atmospheric observation data of 46 oceanic island stations and 17-year voyages distributed in the world’s major oceans, Liu (1986) derived a five term regression equation about the atmospheric specific humidity and the water vapor content (also known as the precipitable amount W) of the atmospheric column per unit area. The root mean square error of the formula is 0.73 g/g, where W can use satellite observation data. By comparing the atmospheric specific humidity obtained from the fixed-point detection data of the air-sea interface with that calculated from the above empirical formula in satellite data, the feasibility of the monthly average global atmospheric specific humidity parameterized formula in the South China Sea is confirmed (Zeng et al. 2009). In order to further calculate the daily latent heat flux data, 1727 high-precision observation samples were used to verify the accuracy of the main parameters in the latent heat block formula-sea surface temperature, wind speed and atmospheric specific humidity (Wang et al. 2013). So as to evaluate the accuracy of calculating the daily latent heat flux in the South China Sea using the monthly mean

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Fig. 6.17 Comparison of atmospheric specific humidity observed by buoy in continental shelf area from March to May 2011 and automatic weather station in Xisha Islands from 2008 to 2010 as well as the latent heat data of SCSSLH and OAFlux satellites (Wang et al. 2013)

global specific humidity parameterization formula, 1016 vertical sounding profiles from 1998 to 2012 were used for verification. Figure 6.17 shows the observational values of atmospheric specific humidity at the Paracel Islands automatic weather station and the fixed buoy in the northern slope of the South China Sea, and the time series of atmospheric specific humidity with two latent heat data of SCSSLH and OAFlux. It can be seen that from 2008 to 2010, the specific humidity of SCSSLH is closer to the observation value, but in the continental slope area, but the accuracy of oaflux is higher in the slope area. In addition to the field observations, it is also compared with the existing 5 kinds of daily latent heat data, which confirmed the high accuracy of SCSSLH. (2) Comparison between flux observation tower and satellite remote sensing flux The flux exchange between the ocean and the atmosphere, including heat flux and momentum flux, can affect the ocean-atmospheric boundary layer and the upper ocean structure, thereby affecting the atmospheric circulation and ocean circulation. In addition, as a necessary driving condition for ocean and climate models, air-sea flux has a non-negligible impact on the results of the model. Due to the importance of air-sea flux, a variety of reanalysis flux products have been widely used. They can provide global, grid, and almost real-time updated air-sea flux data. However, different flux products have differences in assimilating observation data and selecting parameterization schemes, which lead to differences among these flux products. In recent years, there is an increasing trend of observational experiments on the ocean, allowing us to use these observations to evaluate the quality of flux products. By collecting and sorting out the data of reliable observation methods such as buoys and flux towers in the South China Sea in recent years, we have evaluated 5 commonly used flux products (ERA-interim, OAFlux, TropFlux, NCEP2, JRA55), with a view

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to determine the error level of flux products, and provide reference for selecting appropriate flux products, improving and optimizing the numerical model in practical applications. The observation data are not assimilated into any reanalysis products, which ensures the independence and effectiveness of the assessment. Figure 6.18 shows the monthly average time series of latent heat fluxes observed by three buoy stations in Maoming, Shantou, Xisha and Xisha Tower. It can be seen that on the monthly average time scale, the flux product and the observed change trend are relatively consistent. The seasonal differences of flux product errors are also very significant, especially NCEP2. In summer, the errors of flux products are relatively weak. In order to analyze the reasons for the flux product error, we respectively give the scatter plot and the fitting straight line between the latent heat flux error (ΔLH) and the four block variable errors (ΔU, ΔTs, ΔTa, ΔQa), such as As shown in Fig. 6.19. In order to measure the contribution of the four block variable errors to the latent heat flux error, all data have been standardized. It can be seen from Fig. 6.19 that the wind speed error and the sea temperature error are positively correlated with the latent heat flux error, and the specific humidity error and the latent heat flux error are negatively correlated. These are all determined by their signs in the block formula. When the temperature is high, the sea-air temperature difference is small, the air sea specific humidity difference is small, and the latent heat flux is small. Therefore, the air temperature error and the latent heat flux error are negatively correlated. By

Fig. 6.18 Comparison of latent heat fluxes of various fluxes products and observed latent heat fluxes a–d are the observation data of Shantou, Maoming, Xisha Tower and Xisha buoy successively; e–h is the time series of the difference between flux product data and observation data of corresponding stations. All data are monthly averages

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Fig. 6.19 Scatter diagram of the error of latent heat flux product relative to the observed value and the error of block variable relative to the observed value. The gray solid line is the line obtained by the least square method. All data have been standardized. ΔU represents wind speed error; ΔTs represents SST error; ΔTa represents temperature error; ΔQa stands for specific humidity error

comparing the slopes of the four fitting straight lines in Fig. 6.19, it can be seen that the slope between the specific humidity error and the latent heat flux error is the largest, followed by wind speed, then air temperature, and sea temperature the smallest. This shows that the error of the latent heat flux product is mainly caused by specific humidity error, and it is worth noting that the correlation between latent heat flux error and SST error is the weakest, indicating that although the latent heat flux error has a certain relationship with the SST error, it is not sensitive to SST error. In ocean model or air-sea coupled model, sea-air flux is a necessary boundary condition. The flux products evaluated in this study are also widely used in different numerical models. It can be seen that the error of the flux product itself will have a certain impact on the results of the numerical model. We know that the sea temperature change above the mixed layer is mainly controlled by the net heat flux at the air-sea interface. The two largest terms of net heat flux are are solar short-wave radiation and latent heat flux, of which the temporal and spatial variation of latent heat flux are the most significant. Combined with the SST tendency diagnostic equation, we evaluated the influence of the error of latent heat flux in flux products on the SST in the model calculation (Fig. 6.20). A notable feature is that the change in SST is relatively strong in both winter and summer, but SST fluctuates more in winter due to the greater uncertainty between flux products. Although the error of latent heat flux in summer is small, due to the thin thickness of the mixing layer, one of the two is in the numerator position and the other is in the denominator position in the calculation formula of the net heat flux term of the SSTA tendency equation. As a result, a smaller error of the latent heat flux on SST can not be ignored. In summary, both the flux products and the observed data show that latent heat flux itself has obvious seasonal variation, which is stronger in winter and weaker

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Fig. 6.20 SST tendency change caused by latent heat flux error estimation based on flux products

in summer. This seasonal variation leads to the seasonal difference of latent heat flux error, which are also manifested stronger in winter and weaker in summer. In addition, the differences between flux products also become more obvious in winter. With the help of SSTA trend equation, we estimated the SST tendency change that may be caused by latent heat flux error. The results show that the SST change is still obvious in winter, and there is great uncertainty on the influence of SST change due to the significant difference between flux products. We can also see the importance of choosing the right flux product that different flux products may result in a large difference in SST simulation.

6.2.2 Temporal and Spatial Variation of the Marine Atmospheric Boundary Layer in the South China Sea Above the ocean, the temporal and spatial variation of the thickness of the marine atmospheric boundary layer (the offshore gas layer about 1000 m above the sea surface) are relatively slow. Due to the strong mixing in the upper ocean, the daily changes in SST are extremely small. However, the sea water has a large heat capacity, and a slowly changing sea surface temperature with a small range means that a slowly changing and weak force acts on the bottom of the boundary layer. Atmospheric circulation affects changes in the marine environment through the ocean-atmospheric boundary layer. Studying the ocean-atmospheric boundary layer will help us better study the influence mechanism of the changes in the ocean surface structure and its relationship with the occurrence and development mechanism of synoptic scale phenomena. The marine atmospheric boundary layer connected by the air-sea interface is the environment for human activities and survival on the ocean. The prediction of the processes that occur in the ocean-atmospheric boundary layer is directly related

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to the development and utilization of the ocean, marine disasters and marine security. Therefore, the development of ocean-atmospheric boundary layer prediction technology is one of the focuses of coastal countries in the world. The medium of the air-sea interaction is the ocean–atmosphere boundary layer, which is the bond between the ocean and the atmosphere. Therefore, understanding the characteristics and laws of wind speed, temperature, and humidity in the marine atmospheric boundary layer is of great significance for the numerical prediction of the marine environment. In this section, we use the sounding data from the SCSME to analyze the impact of monsoon onset on the structure of the marine atmospheric boundary layer in the South China Sea. At the same time, we use multiple voyage sounding data to analyze the microstructure changes of the ocean atmosphere under several marine phenomena in the South China Sea.

6.2.2.1

Marine Atmospheric Boundary Layer Under the Influence of Summer Monsoon

(1) Variation characteristics of atmospheric boundary layer during the South China Sea summer monsoon outbreak The thermodynamic properties of the ocean make the diurnal changes of the atmospheric mixing layer on the ocean not as obvious as on land, but we can still see the diurnal changes of the atmospheric boundary layer. Taking the vertical structure of boundary layer at the same time and the average value, we use the composite analysis to analyze the boundary layer before and after the onset of the monsoon because the onset time of the southern and northern monsoon is different. The onset date of the monsoon in the northern South China Sea in 1998 was approximately May 17, while that in the southern South China Sea was May 22. There are 45 (106) sounding data before (after) the onset of the northern monsoon and 72 (80) sounding data before (after) the onset of the southern monsoon. The structure of the boundary layer in the southern South China Sea is relatively stable before and after the monsoon onset. The average diurnal variation of water vapor in the whole lower atmosphere is relatively large, and the difference between day and night of water vapor decreases after the onset of the monsoon. After the onset of monsoon, the water vapor content decreased by 1–2 g/kg compared with that before the onset of monsoon. In the northern part of the South China Sea, the difference between day and night of water vapor is relatively small in the boundary layer. From the boundary layer to the upper atmosphere, the diurnal difference of daily average water vapor is significant before the onset of the monsoon, and the property of water vapor is relatively uniform after the monsoon’s break. After the monsoon onset, the water vapor content increased significantly by 1–2 g/kg than before the onset of the monsoon. Compare the difference between the north and the south: before the monsoon onset, the diurnal change of water vapor content in the lower layer is greater in the south than that in the north; after the monsoon onset, the diurnal variation of the water vapor content in the entire layer is greater than that in the north; before the monsoon onset, the water vapor content in

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the south of the South China Sea is 1–2 g/kg higher than that in the north; before and after the outbreak, the boundary layer in the southern SCS was obviously deeper than that in the northern part. According to the statistics, the average daily variation of virtual potential temperature is 0.5–1.0 k, and the average daily variation of specific humidity is 0.2–0.8 g/kg. In the boundary layer height sequence, the average value of the same time is selected as the boundary layer height of the composite event. By calculating the variance of 13 (23) sounding data before (after) the onset of the northern monsoon and 18 (18) sounding data before (after) the onset of the southern monsoon, the diurnal variation of the average boundary layer height in the Southern and Northern South China Sea is obtained (Fig. 6.21). It can be seen that at noon (06GMT) when the solar radiation is relatively strong, the southern boundary layer of the South China Sea develops deeply. The boundary layer height has regular diurnal changes before the monsoon onset, and its variance is small; after the monsoon onset, the diurnal changes become more obvious, but irregular. At noon, the development is deepest, and its variance becomes larger. In the northern part of the South China Sea, there is a regular diurnal variation before the onset of the monsoon, and its variance is small; but after the monsoon eruption, this diurnal variation tends to disappear and its variance becomes larger. The increase in cloud cover after the monsoon onset weakens the diurnal variation of the boundary layer in the northern South China Sea.

Fig. 6.21 Synthetic diurnal variation of mean boundary layer height a South before monsoon onset; b South after monsoon onset; c North before monsoon onset; d North after monsoon. The vertical line represents the variance

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(2) Characteristics of long-term ocean-atmospheric boundary layer before and after monsoon onset The atmospheric boundary layer is a medium that characterizes the exchange between the atmosphere and the ocean. The mixed layer in the atmospheric boundary layer is most directly affected by the water vapor and heat on the underlying surface of the ocean. The increase in the mixing layer represents the strong transport of water vapor from the ocean to the atmosphere, which is closely related to the ocean temperature. An increase in sea water temperature corresponds to more water vapor being transported from the ocean to the atmosphere. The atmospheric boundary layer before and after the monsoon onset is reduced as a whole. The difference is that in the northern part of the South China Sea, there are obvious fluctuations in the height of the mixed layer in the atmosphere. After the onset of monsoon, the height of mixing layer decreases with the decrease of SST, and then increases slightly with the increase of SST in mid JuneIn the northern part of the South China Sea, before the monsoon break out, the height of the mixing layer is relatively high, with an average height of 760 m. Although the height of the mixing layer fluctuates during this period, it is mainly concentrated in the diurnal variation. In 1998, the onset time of the monsoon observed at a fixed point in the northern South China Sea was May 17, while the height of the mixed layer dropped obviously after May 14, mainly at 540 M. At this time, SST also had a drop, which was positively correlated with the change of mixing layer height. During the observation period in June, after the monsoon erupted completely, the height of the mixing layer gradually increased with the recovery of SST. In the southern part of the South China Sea, before the monsoon broke out, due to the high water temperature (SST > 29 °C), the mixing layer in the atmospheric boundary layer developed deeply and remained stable. The monsoon broke out around May 22. It can be seen from Fig. 6.22 that at the beginning of the summer monsoon, the thickness of the mixing layer in the southern South China Sea did not have a rapid decline in the thickness of the mixed layer as that in the northern South China Sea, but remained the same as that before the onset of the monsoon. It was not until mid-June that the thickness of the mixed layer began to decrease slightly. The average thickness is 820 m before the onset of monsoon and 790 m after the onset of monsoon. In the southern part of the South China Sea, the characteristics of the mixed layer change are obviously different from those in the north. Although the underlying surface temperature is very high, the height of the mixed layer is always maintained within a range. We used to think that the higher the SST, the more the mixing layer develops. Relatively speaking, the sea water temperature before and after the onset of the southern South China Sea monsoon corresponds to a change value of 2 °C. However, this increase in water temperature did not lead to a corresponding increase in the height of the mixing layer (MLH) after the onset of the monsoon. SST and MLH here are different from the northern part of the South China Sea, which makes us speculate that the development of atmospheric boundary layer may be controlled by other factors.

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Fig. 6.22 Temporal evolution of the ocean–atmosphere mixed layer thickness and SST during the 1998 summer monsoon a Northern South China Sea; b Southern South China Sea; c Boundary layer height on Dongsha Island; d The height of the oceanic atmospheric boundary layer at 06Z

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Fig. 6.22 (continued)

Comparing before and after the monsoon onset, we know that when the water temperature is higher than the air temperature, the stratification of the atmosphere near the sea surface is unstable, and the air above the water surface obtains heat from the sea, generates thermal turbulence and convection, and can quickly transport the obtained energy upward. This process continues until the water loses heat and the temperature is equal. On the contrary, the atmosphere stratification is very stable. The sensible heat flux in the northern part of the South China Sea is relatively small during the monsoon onset, indicating that the atmospheric stratification near the sea surface is stable and the heat is transferred from the atmosphere to the ocean. While in the south of the South China Sea, the sensible heat transport increases after the monsoon onset, which just provides energy to the mixed layer and makes the mixed layer develop deeper. The latent heat exchange in the southern part of the South China Sea is larger than that in the northern part. Latent heat flux is the main way of heat transfer from the ocean to the atmosphere. The evaporation in the south of the South China Sea is large, and the water vapor is continuously transported to the atmosphere, which deepens the atmospheric mixing layer. After the onset of the northern monsoon, the latent heat is lower than before the monsoon, while the latent heat is increased after the onset of the southern monsoon. In addition, considering the adjustment of the atmosphere itself: the configuration of the upper and lower layers also plays a very important role in determining the structure of the lower atmosphere. The elevation of condensation height is a characterization of the height of the cloud bottom in the atmosphere. Since the dry adiabatic decline rate of the air block in unsaturated space is greater than the vertical decline rate of the dew point, the temperature and dew point of the air block will gradually approach as the air block rises, and finally reach saturation and condensation occurs. The height of the wet air block just beginning to condense is called the rising condensation height. If the height of the mixed layer is higher than that of the cloud base, saturation will occur in the middle and upper part of the mixed layer, and the height of the mixed

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layer will continue to develop. And if the height of the mixing layer is lower than the height of the cloud base, there will be a mixing layer coupled with the clouds above it, and the development of the mixing layer will be inhibited by the cloud capping effect, that is, the height of the mixed layer will not develop significantly. The development of the mixed layer in the southern South China Sea is affected by continuous high temperature of the underlying surface. The heat exchange between the sea and the atmosphere is very large, making the overall mixed layer height about 100 m higher than that in the north. However, after the monsoon erupted, the height of the mixed layer did not decrease, and the adjustment of the atmosphere also played a key role. The boundary between the cloud layer and the mixed layer is very clear in the southern part of the South China Sea. The cloud layer is below the mixed layer, and the development of mixed layer can continue without the cloud capping effect. In the north, the mixed layer cannot break through the limitation of the cloud cover, so it has not developed deeply. In other words, the development of the mixed layer is inhibited due to the cloud capping effect. The height of the mixed layer decreases, which means that this part of the energy released is manifested in the form of rainfall. There is a negative correlation between the decrease of the mixed layer and the occurrence of rainfall in the atmosphere: in the northern South China Sea, when the monsoon broke out, the height of the mixed layer began to decrease significantly on May 15, and rainfall occurred at this time; in early June, when the height of the mixed layer increased significantly, rainfall stopped. In the southern South China Sea, the height of the mixed layer did not decrease significantly throughout May, which corresponds to the no-rainfall period in the southern South China Sea. In June, although the overall height of the mixed layer did not decrease significantly, the height of the mixed layer did not decrease significantly in some of the moments, which corresponds to the occurrence of rainfall, thus verifying our conjecture again. The mixed layer represents the microscopic coupling of the atmosphere and the ocean, water vapor and energy are transferred upwards from the air-sea interface to the atmosphere, which fully supports the influence of ocean forcing on the height of the mixed layer in the boundary layer. The decrease in the height of the mixed layer indicates the release of energy, which is prone to produce rainfall.

6.2.2.2

Synoptic-Scale Air-Sea Interactions of the Ocean Front in the South China Sea

The atmosphere and ocean are a coupling system in the earth’s sphere. Air sea interaction is not only closely related to global climate change and the occurrence of local extreme disastrous weather, but also affects the physical processes in the ocean and changes in the ecological environment. Therefore, the research on the air-sea interaction mechanism and its influence has become a hotspot and frontier of atmospheric and marine scientific research in recent years. The impact of SST changes caused by ocean fronts and mesoscale vortices on the atmosphere and the feedback effect of the atmosphere are important scientific

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issues in the study of air-sea interactions. The latest research has further found that the horizontal gradient structure of SST caused by the ocean front and mesoscale vortices has an impact on the dynamic structure of the marine atmospheric boundary layer, and SST changes have an impact on on the vorticity field, divergence field of the sea surface and the vertical structure of atmospheric elements such as wind and humidity in the marine atmospheric boundary layer (Chelton 2013). Previous studies have mostly focused on the ocean frontal areas in the open ocean, such as the equatorial area of the East Pacific (Lindzen and Nigam 1987; Wallace et al. 1989), the Gulf Stream and its extension basins, and the Kuroshio and its extension basins (Nakamura et al. 2012). Through the analysis of satellite observation data and numerical simulation, it is confirmed that there is a positive correlation between the surface water temperature near the ocean front and the sea surface wind speed, that is, the wind speed is faster in areas with higher sea surface temperature and slower in the areas with lower sea surface temperature (Chelton et al. 2004; Small et al. 2008; Chelton and Xie 2010). The changes in wind field generated by the horizontal gradient of surface sea temperature caused by the ocean front and mesoscale vortices will affect the variation of the convergence and divergence field and vertical airflow in the atmospheric boundary layer, and affect the horizontal and vertical transport of water vapor in the atmosphere. It may spread to distant areas through the upper atmospheric circulation, and then affect the global and regional climate (Czaja and Blunt 2011; Nakamura et al. 2012; O’Reilly and Czaja 2014). Although the sea surface water temperature disturbance caused by mesoscale vortices has a certain effect on the formation of wind, humidity, precipitation and clouds in the atmospheric boundary layer, it is a small quantity relative to the average state of these variables, and its impact on regional climate is also very limited (Frenger et al. 2013; Chelton 2013). In addition, the response of the atmospheric wind stress field to the ocean front has a feedback effect on the internal physical processes of the ocean, such as affecting the distribution of Ekman suction (Chelton et al. 2004; O’Neil et al. 2005), upwelling structure and ocean front and mesoscale vortex structure, which is also worthy of attention (Chelton 2013). The dynamic structure adjustment of ocean atmospheric boundary layer caused by sea surface temperature anomaly is mainly reflected in the change of sea surface wind field. There are two main theories regarding the response mechanism of sea surface wind field to surface sea temperature near the ocean front. The first one is proposed by Lindzen and Nigam (1987) when using a one-dimensional boundary layer model to study the response of sea surface wind in the equatorial region of the East Pacific to changes in surface water temperature. They believe that the change of surface sea temperature causes the baroclinic effect of the ocean atmosphere boundary layer, which changes the horizontal pressure gradient, and produces a pressure gradient force from cold water area to warm water area, thua caus the acceleration and deceleration of sea surface wind speed. In addition, Song et al. (2006) used a numerical model to study the influence of SST changes in the Atlantic Gulf Stream region on the structure of the ocean atmosphere boundary layer, and analyzed the dynamic and thermodynamic mechanisms. The results showed that the

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thermal forcing of SST causes the change of the perturbation pressure gradient force, which accelerates the air movement from the cold-water area to the warm-water area, and restrains and decelerates the air movement from the warm-water area to the coldwater area. Song et al. (2006) also found that the vertical movement of air caused by horizontal convergence and divergence also has an impact on the changes in the sea surface wind field, while the effects of Coriolis force and horizontal advection are relatively minor factors leading to the change of wind field. In view of the above-mentioned response mechanism of the sea surface wind field to the surface sea temperature near the ocean front, Wallace et al. (1989) and Hayes et al. (1989) proposed a second theory. They believe that if the pressure gradient is the decisive factor in determining the change of surface wind speed on the ocean front, then the region with the strongest wind speed acceleration (deceleration) on the front should coincide with the region with the largest surface water temperature gradient. However, their observational studies on the equatorial region of the East Pacific show that these two regions do not overlap, but have a certain phase difference. Therefore, they believe that the momentum transport caused by vertical mixing is the main factor that determines the impact of the front on the sea surface wind field. Because the sea surface water temperature changes the stability of the atmospheric boundary layer, the enhancement of warm water and the suppression of vertical mixing in the boundary layer by cold water affect the momentum exchange process above and below the boundary layer, resulting in the change of sea surface wind speed. Skyllingstad et al. (2007) used a two-dimensional large eddy numerical model to study the response process of the wind field to the surface water temperature front. The simulation results show that the vertical mixing of turbulence has a greater contribution to the change of wind field with the change of surface water temperature, while the change of pressure gradient has a relatively small effect. Ocean fronts exist not only in the oceans, but also in coastal waters. According to the definition of Yanagi and Koike (1987), ocean fronts can be divided into three categories: open ocean front, shelf front and coastal front. Coastal fronts can be divided into four types according to the specific reasons: ➀ estuarine front, which is formed by high salinity and low salinity in the estuary area; ➁ thermal effluent front, which is formed by hot water discharged from power plants along the coast; ➂ tidal front, a front formed between locally mixed uniform seawater caused by tides and topography and weakly mixed stratified seawater (Simpson and Hunter 1974). Mostly formed in summer; ➃ Hot salt fronts. Compared with ocean fronts, the temporal and spatial scales of fronts in coastal (offshore) areas are smaller. At the same time, there are obvious diurnal changes in the wind field above the fronts. Therefore, the dynamic and thermal mechanism of the coastal air sea interaction may be different from that of the ocean. The South China Sea is the largest marginal sea in China. As a warm pool in winter and a water vapor transport channel in summer, the South China Sea plays an important role in the weather and climate of South China and the Yangtze River Basin. The frontal features in the northern part of the South China Sea are significant, such as the thermal salt front, tidal front and upwelling front. It is of great scientific significance to study the front-atmosphere interaction mechanism in the northern

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South China Sea and its seasonal variation characteristics, and to further clarify the dynamic and thermodynamic mechanisms of the air-sea interaction in the northern South China Sea. Therefore, this part discusses the air-sea interaction mechanism in the coastal ocean front area of the northern South China Sea and its influence on the local weather and climate and offshore internal physical processes. (1) Effects of the oceanic front on the structure of the oceanic atmospheric boundary layer in the northern South China Sea in winter Using high-resolution [(1/20)°] monthly average OSTIA (operational sea surface temperature and sea ice analysis data) data for the six years from 2006 to 2011, the temporal and spatial variation characteristics of the front in the northern shelf of the South China Sea are analyzed (Fig. 6.23). Satellite data show that there are three areas in the northern part of the South China Sea that have obvious frontal activities, namely the Beibu Gulf, the northwestern sea area of Luzon Island, and the coast of Guangdong-Fujian. Among them, the fronts of the Beibu Gulf and the northwest sea area of Luzon Island only occur in winter, while the fronts along the coast of Guangdong and Fujian can be observed throughout the year. In this paper, we mainly focus on the long and narrow belt-shaped fronts located on the 20–50 m isobath along the coast of Guangdong-Fujian to discuss the characteristics of the front in the northern South China Sea and its influence on the local sea surface wind field. The front extends from the southern part of the Taiwan Strait to the southwest, and reaches as far as the east of Hainan Island, with significant seasonal variation. In winter, the front begins to form in November after the northeast monsoon prevails, and develops rapidly in December, covering the widest sea area. The intensity of the eastern front increases significantly from December to February, while the intensity of the western front does not change significantly in the same period. After entering spring (March), the northeast monsoon began to weaken, and the winter front began to fade. After entering May, the covered sea area drastically reduced to half of the winter. In summer (June to August), influenced by the Pearl River diluted water and the Guangdong Fujian coastal and Taiwan Shoal upwelling systems, the summer front begins to develop in the eastern coast of Guangdong and the southern Taiwan Strait, but its coverage area is much smaller than that in winter. After the summer monsoon subsided, the frontal coverage area of the entire Guangdong-Fujian coastal area was the smallest in September. Although the front coverage area in winter is much larger than that in summer, the average gradient of SST in the front area is similar. The mean SST gradient in the mature stage of frontal development is about 0.021 °C/km in winter and 0.017 °C/km in summer. The disturbance fields of the monthly average QuikSCAT wind speed and OSTIA SST in 2008 are obtained by spatial high pass filtering. The analysis shows that there is an obvious positive correlation between the local SST disturbance and the wind speed disturbance on the northern front of the South China Sea. That is, the surface wind speed is high in the warm water temperature region of the front, while the surface wind speed is low in the cold water temperature region, which proves that the South China Sea front has an impact on the local variation of the sea surface wind field (Fig. 6.24). At the same time, the local influence of the front on the sea surface wind

Fig. 6.23 Monthly mean SST and SST gradient distribution in the northern South China Sea (Shi et al. 2015b)

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field has significant spatial and seasonal changes. The positive correlation between SST and sea surface wind speed in winter is significant in the west of 117° E, and negative in the east of 117° E and the south of Taiwan Strait, while significant in the south of Taiwan Strait in summer. The reason for the insignificant influence of the wind speed on the sea surface east of 117° E in winter is that the blocking effect of Taiwan Island and the narrow tube effect of the Taiwan Strait caused by the spatial distribution of wind field characteristics are more important than the frontal influence. While in summer, the frontal area south of the Taiwan Strait is weaker in the west of 117° E, and stronger in the south of the Taiwan Strait, especially in the sea area near Taiwan Shoal, so that the local effect of the front is prominent. The local influence of the northern front of the South China Sea on the sea surface wind field also has obvious interannual variation. The winter front influence in 2006 and 2008 is more significant than that in other years. The SST wind speed coupling coefficient defined by the linear regression coefficient of SST and wind disturbance is about 0.5, which is higher than 0.2–0.3 in other years. The internal mechanism of the interannual change is still unclear and needs further study. By comparing the results of the control experiment and the sensitivity experiment of changing the front SST gradient and position, it is found that the pressure gradient force above the area with the largest SST gradient change on the front surface changes the most, and there is a positive correlation between them. Therefore, the change of sea surface wind field is mainly caused by the change of pressure gradient force caused by SST gradient, the advection term and Coriolis force term play a secondary role, and the vertical mixing term is the balance term of the sum of the first three. We also found that when the background wind speed is high, the frontal influence on the wind field is not obvious. One of the reasons may be that the high background wind speed causes the air mass to stay for a short time above the front, and the air mass has no time to respond to the changes of different water temperatures on both sides of the front. Although the change of air mass properties is limited in this case, the adjustment effect of the front on the atmospheric boundary layer can still be observed in the form of the change of the wind speed profile of the offshore surface layer with height. (2) Structural characteristics of the oceanic and atmospheric boundary layer over the upwelling front in summer in the northeastern South China Sea Fujian Guangdong coastal area is the confluence of Fujian Zhejiang coastal water, South China Sea water and Pearl River diluted water. The topography of the sea area is a wide continental shelf, mainly affected by the East Asian monsoon, with obvious seasonal changes, and the southwest wind prevails in summer. There is an upwelling in the coastal waters of Fujian Guangdong in summer, and the southwest monsoon and topography are important factors for the upwelling. Some studies have confirmed the existence of upwelling in this area in summer by using field observation data and satellite remote sensing data. Through the satellite remote sensing sea surface temperature (SST) and the wind field, it can be seen that the upwelling intensity is closely related to the change of the wind field. Tthe change of the component of sea surface wind field parallel to the coastline is an important reason for the change of

Fig. 6.24 Disturbance field of SST and SST obtained after spatial high-pass filtering of QuikSCAT wind speed and OSTIA SST in 2008 (Shi et al. 2015b)

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upwelling intensity in this region in summer. However, the microscopic activity state of the atmosphere near the upwelling region is not very clear. We use sounding data to reveal the forcing response of the ocean to the atmosphere. The structure of the atmospheric boundary layer represents an important factor for the ocean to affect the atmosphere. In September 2006, the South China Sea open voyage conducted cross-sectional observations in the upwelling area of eastern Guangdong, and a total of 7 balloons were released. In the open voyage in August 2007, 3 balloons were released on the same cross-section. From the three-day mean SST of the satellite TMI on September 9, 2006 (Fig. 6.25a), it can be seen that the surface temperature of coastal seawater gradually decreases from southwest to northeast. The surface water temperature of the coast east of 116° E is generally lower than 29 °C, and the coastal waters are low temperature areas where the surface water temperature is lower than 28 °C. On the QuikSCAT wind field, the southwest monsoon is relatively weak because it is in the transition period of summer circulation and winter circulation, and the east wind prevails in the coastal area. In the August 2007 voyage, uniform southwest wind prevailed in the observation area, and the upwelling was strong. The surface temperature of the coastal seawater gradually decreases from southwest to northeast. The surface temperature of the coastal water east of 116° E is generally lower than 28 °C, and a relatively obvious cold vortex appears. In the virtual potential temperature profile of the atmospheric sounding data in September 2006 (Fig. 6.26), it can be clearly seen that the corresponding ocean temperature has a structure of’deep on the left and shallow on the right’. A cold surge bulge appears at 103°–104° E, which makes SST here slightly lower. Correspondingly, there is a downward ‘groove’ in the upper atmosphere, which indicates that the atmospheric temperature is lower over the cold-water region, while is higher in the warm-water region. Further analysis revealed that there was an obvious mixed layer in the atmosphere on the cross-section in September 2006, with an average height of 200–500 m, and the thickness of the mixed layer increases gradually. In the

Fig. 6.25 3-day mean SST (color) and QuiKSCAT wind field during August and September 2006 voyages (vector arrows)

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upwelling region, the height of the mixed layer is below 500 m, while in the warm water region, the height of the mixed layer is higher than 500 m. During the voyage we also found that other atmospheric factors changed significantly with temperature over the course of the voyage.

6.2.2.3

Atmospheric Duct in Atmospheric Boundary Layer

Atmospheric duct is a special tropospheric atmosphere with the structure of atmospheric refractive index decreasing with height. This phenomenon of atmospheric hyperrefraction has an important impact on modern radar detection and electronic communication. For example, it can lead to over the horizon propagation and detection blind area, which will affect the detection performance of radar. With the continuous development of modern economy and military, radar system, early warning system and communication system are required to have the ability to work allweather, so it is necessary to study the law of atmospheric duct environment and its prediction and detection methods. The change of atmospheric refractive index (M) is often used in the research to study the atmospheric duct. The formula of the atmospheric refractive ( ) Zcalculation 4810e 6 × 10 P + + index is M = 77.6 T T R In the formula, e is the water vapor pressure (hPa); P is the air pressure (hPa); T is the absolute temperature (K); Z is the height from the sea surface (m); R is the average earth radius, taking 6.371 × 106 m. When the corrected atmospheric refractive index decreases with altitude, that is, when dM/dZ < 0, the atmospheric duct phenomenon will appear. In tropospheric atmosphere, atmospheric duct can be divided into three types: suspended duct (uplift duct), surface duct (including surface duct with trapped layer grounded and surface duct with trapped layer suspended) and evaporation duct according to the vertical gradient of atmospheric refractive index and its height. Among them, the bottom height, top height, thickness, intensity and trapping layer are the main parameters to describe the properties and characteristics of atmospheric duct. Domestic research on atmospheric ducts began in the 1990s. The South China Sea is a high-incidence area of atmospheric ducts. Cheng et al. (2013) conducted a study on the temporal and spatial distribution of atmospheric duct characteristics in the South China Sea based on sounding data during 1998 SCSME. Cheng et al. (2013) studied the spatial and temporal distribution of atmospheric duct characteristics in the South China Sea Based on the radiosonde data during the 1998 monsoon test. The results showed that the probability of atmospheric duct occurrence decreased after the onset of summer monsoon, the intensity of low-level atmospheric duct in the northern South China Sea increased slightly, the thickness of low-level atmospheric duct in the Southern and Northern South China Sea decreased, and the sharp decrease in humidity was the direct cause of these changes. Based on the high-resolution sounding data collected from 2010 to 2012, Zhao et al. (2013) quantitatively analyzed the occurrence probability and the distribution characteristics of

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Fig. 6.26 Profile of observed virtual potential temperature during September 2006 voyage (a) and CTD station water temperature map (b)

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height, intensity and thickness of atmospheric duct in the South China Sea and the tropical East Indian Ocean in spring. (1) Statistical characteristics of atmospheric duct during monsoon tests in the South China Sea Evaporation duct is a common type of duct. It is a kind of duct formed by atmospheric junction, which causes a sharp decrease of atmospheric humidity with height and changes the atmospheric refractive index structure. The marine evaporation duct is the most important part of the tropospheric duct research. In order to make full use of or avoid the propagation effects caused by the evaporation duct environment, many experts have carried out research on the environmental characteristics of the marine evaporation duct. Lin et al. (2005) and Yang et al. (2009) made a statistical analysis of the evaporation duct in China’s sea area based on the evaporation duct model, and pointed out that the evaporation duct height has the characteristics of seasonal variation, monthly variation and spatial variation. It is not a simple spatial–temporal distribution characteristic that higher in the south nor in the summer. It can be seen that the evaporation duct environment has the characteristics of geography and scale, and in the coastal area it may also be affected by the land. However, the South China Sea is greatly affected by the monsoon and circulation, the meteorological and hydrological conditions are complex, and the environmental characteristics of evaporation duct are different. Due to the low height of the evaporation duct, which is generally less than 40 m, the observation data of the sea surface and lower atmosphere is extremely scarce due to the constraints of observation methods and means. Most of the evaporation duct studies in the existing literature use the inversion of the evaporation duct model, or use the data of coastal and offshore stations with low resolution. In view of this, we use the high-resolution low-level atmospheric profile data of the South China Sea Monsoon Experiment (SCSMEX) during the past two months, which were observed four times a day by the research vessels of ‘Experiment 3’ (20°29′ N, 116°57′ E) and ‘science 1’ (6°15′ N, 110°0′ E), to study and analyze the characteristics and causes of evaporation duct before and after the onset of the South China Sea monsoon. This experimental data distribution can better represent the atmospheric state and the North–South difference in the South China Sea before and after the monsoon onset, which is conducive to the analysis of the regional characteristics of evaporation duct environment in the South China Sea. During this monsoon experiment, a total of 294 times of valid sounding data were collected, of which 147 times were in the north and 147 times in the south. In 1998, the southern South China Sea monsoon broke out on May 22, and the northern South China Sea monsoon broke out on May 17. The sounding profiles before and after the onset of the northern South China Sea monsoon were 42 and 105 h, respectively, and those in the southern South China Sea monsoon were 66 and 81 h, respectively. It can be seen from Table 6.1 that the occurrence probability of the evaporation duct at each time before the monsoon onset in the northern South China Sea is 81.82, 70, 18.18, and 30%, while the probability of occurrence after the monsoon onset is 60, 80.77, 48.15, and 33.33%. Obviously, except for 00gmt, the occurrence probability of

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evaporation duct at other time after the onset of monsoon is increased correspondingly compared with that before the onset of monsoon. The same phenomenon occurs only at 12GMT and 18GMT in the southern South China Sea. This shows that the onset of the southwest monsoon in the South China Sea is conducive to the occurrence of the evaporation duct, which increases the probability of the occurrence of the maritime duct. This may be due to the increase of the evaporation of water vapor at the air-sea interface after the onset of the southwest monsoon, which is more likely to cause sharp humidity and form the duct structure. In addition, the occurrence probability of evaporation duct in the northern part of the South China Sea is 18.18–81.82%, and that in the southern part is 68.75–100%. It can be seen that the occurrence probability of evaporation duct in the southern part of the South China Sea is higher than that in the northern part, indicating that the occurrence probability of evaporation duct has an increasing trend with the decrease of sea latitude, which is consistent with the previous research results. The results also show that the occurrence probability of evaporation duct shows obvious diurnal variation. The occurrence probability of evaporation ducts at 00GMT and 06GMT in the northern and southern South China Sea is greater than that at 12GMT and 18GMT, that is, the occurrence probability of evaporation ducts during the day is greater than that at night and. It also shows that the difference in the north is more obvious than that in the south because the evaporation ducts in the south have a greater probability of occurrence. There are 4 observations/occurrence probability of 100% before and after the monsoon onset. In order to analyze the diurnal changes in the intensity and height of the evaporation duct before and after the monsoon onset in the South China Sea, statistical analysis was carried out on the northern and southern parts of the South China Sea. The intensity and height of the evaporation duct in the northern part of the South China Sea basically show a ‘low–high–low’ diurnal variation. Both the intensity and height reach the maximum at 06GMT at noon, and the diurnal change of intensity is more obvious than the height. Before the onset of monsoon, the variance of the height and intensity of evaporation duct is smaller, but the diurnal variation is weaker; after the onset of monsoon, the variance of the intensity and height of evaporation duct becomes larger, and the diurnal variation is more intense. The intensity of the evaporation duct in the southern part of the South China Sea clearly shows a ‘low–high–low’ diurnal variation, reaching a maximum at 06GMT at noon, while the diurnal variation of the evaporation duct height is small, and the height at noon is not the highest. As in the northern South China Sea, the variance of height and intensity of evaporation duct before monsoon onset is smaller than that after monsoon onset, indicating that the diurnal variation of height and intensity of evaporation duct before monsoon onset is weaker. The average intensity and height of the evaporation duct in the northern part of the South China Sea are about 5 M-unit and 30 m respectively, while those in the southern part of the South China Sea are about 10 M-unit and 20 m respectively. Therefore, it can be concluded that the intensity of the evaporation duct in the southern part of the South China Sea is greater than that in the north, while the height is lower than that in the north. It shows that as the latitude decreases, the height of evaporation duct tends to decrease, but the intensity tends to increase.

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Table 6.1 Occurrence probability of evaporation dust in the northern and southern parts of the South China Sea GMT item

Northern south China sea

Southern south China sea

Pre-monsoon Post-monsoon Total Pre-monsoon Post-monsoon Total 00

06

12

18

Duct frequency

9

15

24

17

21

38

Observation 11 times

25

36

17

23

40

Percentage (%)

81.82

60

66.67 100

91.30

95

Duct frequency

7

21

28

17

18

35

Observation 10 times

26

36

17

18

35

Percentage (%)

70

80.77

77.78 100

100

100

Duct frequency

2

13

15

13

18

31

Observation 11 times

27

38

16

22

38

Percentage (%)

18.18

48.15

39.47 81.25

81.82

81.58

Duct frequency

3

9

12

11

18

29

Observation 10 times

27

37

16

18

34

Percentage (%)

33.33

32.43 68.75

100

85.29

30

(2) Statistical characteristics of oceanic atmospheric dust over the South China Sea and eastern Indian Ocean Based on the data of voyages, the South China Sea Institute of Oceanography, Chinese Academy of Sciences has carried out the research on the oceanic atmospheric duct in the South China Sea and the East Indian Ocean. During the spring of 2010–2012 (April 12-may 27, 2010, March 31-may 15, 2011, February 25-april 20, 2012), the research vessel ‘Experiment 1’ of South China Sea Institute of Oceanography, Chinese Academy of Sciences completed three open voyages in the Indian Ocean. During the expedition voyage, 4 high-precision GPS radiosonde (nearly 2000 sounding data in total) were released at regular intervals (00UTC, 06UTC, 12UTC and 18UTC) every day. Through preprocessing and quality control of the received data, 380 valid GPS radiosonde data were finally obtained (voyage route and 12 ut time on March 11, 2012 are shown in Fig. 6.27). Based on these high-precision GPS sounding post-processing data, the occurrence probabilities of three types of

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atmospheric ducts over the South China Sea and the tropical East Indian Ocean are analyzed, and the statistical results of the ducts are given. It is found that evaporation duct is the most frequent atmospheric duct in the study area, with an occurrence probability of 75.3% and an average height of 15.3 m; surface duct has an occurrence probability of 5%, an average height of 84.1 m, an average thickness of 14.9 m and an average strength of 10 m unit; suspended duct has an occurrence probability of 43.7%, an average height of 1003.6 m, an average thickness of 62.2 m and an average strength of 7.9 m-unit. There is little interannual variation in the probability of duct occurrence and and the average value of duct characteristic. Due to the low probability of occurrence of surface duct, the statistical results of the duct characteristic quantities rely on few measured examples. However, from the statistical results of evaporation duct and suspended duct, it can be seen that the duct characteristic quantities basically obey the normal distribution in value.

6.3 Characteristics and Analysis of Tropical Cyclone Activity in the South China Sea Tropical cyclone (TC) activities in the South China Sea include TC generated locally in the South China Sea and TC that enters the South China Sea westward after being generated in the Western Pacific. About 13.2% of the TC generated locally in the South China Sea (Chen and Ding 1979). From 1949 to 2013, there were a total of 660 tropical cyclones in the South China Sea, of which 247 were generated locally in the South China Sea. Since the 1980s, the local generation of TC in the South China Sea has doubled and 98% of them were generated in July to September. The onset of summer monsoon in the South China Sea usually begins in the middle of May and lasts until September. The results show that TC is mainly formed in the North (South) of the South China Sea during the summer (winter) monsoon. The activity of TC in the South China Sea has a good correlation with sea surface temperature (SST) and outgoing long-wave radiation (OLR) (Lee et al. 2006). The initial position of the locally generated TC in the South China Sea usually has a positive relative vorticity of the sea surface wind, while almost no TC is generated in the region of negative relative vorticity (Lee et al. 2006). Lee et al. (2006) analyzed 20 tropical cyclones that formed in the South China Sea from May to June in 1972–2002, and found that 11 of them were generated in the weak baroclinic environment within the Meiyu front, while the other cyclones were more barotropic and more likely to develop and strengthen into strong tropical cyclones. Through the analysis of remote sensing echo images, it is found that there are significant differences in columnar water vapor, liquid water content and total latent heat release between developable and premature extinction tropical disturbances. The direction of the monsoon trough and mountains can change in the relative vorticity of the atmosphere, and then affect the distribution characteristics of tropical cyclone locations.

Fig. 6.27 sample of atmospheric temperature, relative humidity and modified refractive index at 12UTC on 11 March 2012 for the three Indian Ocean voyages

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6.3.1 Influencing Factors of Tropical Cyclone Formation in the South China Sea The mean flow field in summer provides favorable environmental conditions for TC generation, while mesoscale disturbance is the main factor for the generation of individual tropical cyclones. The mesoscale precursor factors of TC generation in the tropical western Pacific include Rossby wave trains induced by energy dispersion of a pre-existing TCTCED, synopitc wave trains (SWT) and easterly wave (EW). Although the large-scale circulation of the South China Sea and the Western Pacific belong to the same Western Pacific monsoon system, there are many obvious differences in atmospheric and oceanic conditions between the two sea areas. For example, the South China Sea is a semi-enclosed marginal sea, while the western Pacific is an open sea. The low-level wind field in the South China Sea in summer is mainly the southwest monsoon, while the western Pacific is mainly affected by the northwestsoutheast monsoon trough. For TC generation in the South China Sea, there are four types of initial disturbances, namely, tropical convergence zone disturbance, trade wind disturbance, monsoon disturbance and baroclinic disturbance. Lee et al. (2006) found that part of the TC in the South China Sea is related to the weak baroclinic disturbance associated with the Meiyu front. TC generation in the South China Sea is also related to the monsoon and the direction of coastal mountains. When the winter monsoon prevails in the northern hemisphere, vortices often form along the coasts of Kalimantan island and Borneo island, known as Borneo vortex (BV), which are usually precursor disturbances of TC in the South China Sea. The low frequency oscillation from intraseasonal to interannual is an important controlling factor of TC generation. Compared with the synoptic scale disturbance, the atmospheric low frequency oscillation has a longer time scale and a wider space range, which can be used as the background field of synoptic scale disturbance. Low-frequency oscillations generally refer to atmospheric oscillations with a time scale of more than 10 days and within 100 days. The Intraseasonal Oscillation (ISO) of the tropical atmosphere modulates TC mainly through the changes of the intensity and structure of the tropical depression (TD) or SWT type disturbances in the lower atmosphere. The TD type disturbance will be enhanced when the ISO phase is positive, which is mainly related to the barotropic capacity conversion related to the rotational and divergent components of the ISO wind field. Studies have shown that quasi-biweekly oscillation (QBWO) plays an important role in modulating TC activities. The OLR field is usually used to calculate convective activities related to ISO. OLR can well indicate the intensity of tropical deep convection (salby and Hendon 1994; Riley et al. 2011). The OLR field of 20–100 days band-pass filtering can generally be used as the local phase determining ISO activity (Riley et al. 2011), which is different from the global ISO phase. The global ISO phase is defined as a real-time multivariate MJO index, which divides tropical regions into different MJO phases every day without considering seasonal variations (Wheeler and Hendon 2004). However, this index cannot accurately describe the characteristics of ISO spreading northward to the Northwest Pacific in summer. The local ISO phase signal

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is calculated based on the value of the OLR filter field at each longitude at each time point (Riley et al. 2011). The large negative OLR value represents the local strong phase of ISO. Although significant ISO signals mainly propagate eastward in winter, in summer, ISO not only propagates eastward in the Northwest Pacific, but also propagates northward to subtropical regions (Chen and Murakami 1988). The propagation characteristics of ISO have significant seasonal variations in the Northwest Pacific TC season (Huang et al. 2011). In this section, we mainly discuss how ISO modulates mesoscale disturbances related to TC generation in the South China Sea.

6.3.1.1

Research on Precursor Signals of Synoptic-Scale Disturbances

According to the previous definition, there were 35 TC generated in the South China Sea from 2000 to 2011. Using the daily low-level wind field (3–10 days band-pass filter) in the 7 days prior to TC generation TC generation, six types of precursory mesoscale disturbances are identified. Among them, there are 10, 5, 3, 4, 8 and 5 precursor disturbances generated by SWT, TCED, EW, BV, TCSV and the sixth type of TC that are not among the first five. SWT type accounted for 29% of the total, followed by TCSV type (23%) and TCED type (14%), BV type and the other type accounted for 11% and 14%, respectively, while EW type accounted for only 9%. If TC is formed in SWT that has nothing to do with the previous generation of TC, it is named SWT type, which is the first type. Northwest-southeast SWT occurs mostly in the Northwest Pacific (WNP) summer. The formation of SWT may be related to the instability of summer mean airflow in the presence of positive feedback of convective friction convergence. Similar to WNP, the precursor mesoscale disturbances generated by most TC in the South China Sea are also northwest southeast SWT. SWT-type TC generation mainly occurs from August to September. The composite field of the upper layer (250 hPa) circulation during the first 72 h of TC generation is divergent, which corresponds to the convergence region at the bottom. The second type is tced type. This type of TC is generated by the cyclonic circulation embedded in the northwest southeast wave train caused by TC energy dispersion. Most of TCED-type TC generation occurs in August to September. The third type of TC is formed by the westward Easterly Wave. 72 h before TC generation, there is a wave train under the mean easterly wind. EW disturbance moves slowly westward and develops into a closed cyclonic circulation 24 h before TC generation, and enters the South China Sea to strengthen TC movement to the middle of the South China. The formation of EW type TC mainly occurs from August to October. The rapid increase of EW disturbance may be related to the accumulation of wave energy at a certain critical longitude or the convergence of wave energy caused by the sudden shortening of the zonal wavelength. The fourth type of TC is developed by local BV. Bv often occurs in the coastal waters near Borneo on Kalimantan Island. It is a synoptic scale system of winter monsoon system in the southern South China Sea. BV is formed and embedded in the monsoon trough, which is mostly related to the low-level winter monsoon airflow

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from high latitude. It generally brings strong precipitation, affects the weather in Malaysia, and affects the planetary scale atmospheric circulation through a large amount of latent heat release. After the formation of BV, it often moves to the West and North, and some BVS may develop into TC after moving to the South China Sea. Because BV mainly occurs in Malaysia, this kind of precursory disturbance is different from other types of disturbance. The fifth type of TC is developed from the southwest wind shear related to the preexisting TC, which belongs to the TC shear induced vortex (TCSV). Different from the TCED type in the southeast side of the new TC generation and the pre-existing TC, the TCSV type TC is formed in the southwest side of the pre-existing TC. By analyzing the composition of wind field and relative vorticity five days before TC generation, it is found that the existing TC appeared in Northeast Taiwan, and the cyclonic shear associated with it is very weak. With the TC moving northeastward in the early stage, the northeasterly wind on the west side of the TC will strengthen the local air shear, and then gradually strengthen into a closed cyclonic circulation. TC generation related to TCSV mainly occurred from July to September. The remaining ones that do not belong to the first five types are classified as the sixth type of disturbance, including Meiyu front (Lee et al. 2006), upper tropospheric forcing, or low-frequency oscillations. In addition, according to the source of precursor disturbance, these 35 TCs can be divided into two categories: one is that the disturbance sources are inside the South China Sea (13); the other is that the disturbance sources are outside the South China Sea (22). In other words, 63% of the early TC disturbances come from outside the South China Sea. The main reason for this difference is that the previous results only used JTWC (Joint Typhoon Warning Center) data to determine the source of TC. However, in terms of synoptic scale disturbance, the early disturbance of TC generation can be traced back. Generally speaking, the disturbances related to the EW type come from outside the South China Sea, while the BV type disturbances exist inside the South China Sea. The other four types of disturbances may exist in the interior or exterior of the South China Sea.

6.3.1.2

Potential Vorticity Diagnosis of Tropical Cyclones Induced by Mid-Level Eddies in the South China Sea

The mesoscale vortex is a synoptic scale system that appears in the middle troposphere (700–500 hPa). The initial disturbance of the mesoscale vortex usually has a cold center structure, and there is no obvious cyclonic circulation on the underlying surface. This is obviously different from the warm heart structure of TC. Some midlevel vortices can form TCs in the South China Sea, which is generally considered as a top-down process. Potential vorticity (PV) is a significant variable, which can include both thermal and dynamic characteristics. The concept of PV was first introduced by Rossby (1940). PV is a conservative and reversible variable in non-adiabatic state without considering friction. In the early days, PV was often used to track gas blocks, but later it was mainly used as a dynamic variable to study three-dimensional

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flow. The piecewise PV inversion method can separate different physical processes and their corresponding contributions. Previous studies suggest that latent heat plays an important role in the formation and development of TC. High PV and PV anomaly always exist in the process of hurricane, because the wind eye wall and spiral rain belt can release latent heat rapidly. The PV slice inversion method can also be used to analyze TC generation. In this part, the nonlinear equilibrium PV piecewise inversion method is used to diagnose the dynamic and thermal processes of TC Usagi (2001) caused by the middle layer vortex in the South China Sea, including the relative contributions of upper layer disturbance, middle layer to lower layer latent heat and surface thermal anomaly. Usagi originated from a middle-level vortex in the South China Sea in August 2001. The maximum potential vortex (PV) of initial disturbance is near 500 hPa, and the anticyclone circulation and cold center structure are found in the near sea surface. The lower layer and upper layer have weak upward motion, while the upward movement in the middle layer is stronger. The cloud top height corresponding to the middle vortex is relatively high. Larger relative humidity is concentrated in the middle layer, causing precipitation and the development of middle-level cyclones. The middle vortex shows the baroclinic structure and the warm center cyclonic circulation is obvious. Warm hearts gradually develop downward to the surface, corresponding to weak upward motion in the lower layers and weak downwelling motion in the middle and upper layers. During this period, dry air and environmental easterly wind cut in from the upper layer, and wet air and precipitation mainly occurred in the lower layer. With the downward development of convection, the vorticity and warm center structure of cyclones have gradually developed. As the environmental field changes, the baroclinic structure of the vortex gradually transforms into a quasipositive pressure, and strong convective instability appears in the lower layers. At the same time, the humidity layer gradually deepens. When the Western Pacific Subtropical High (WPSH) located in the northeast of the cyclone shifts to the southwest, the cyclonic circulation is gradually controlled by the entire layer of east wind, and the horizontal wind and vertical shear are significantly reduced. Along with the favorable environmental field, the ascending movement of the lower and middle layers is enhanced. The cyclone circulation and warm core structure in the middle layer have also been strengthened. The warm core structure develops downward and upward at the same time. The upper layer has a strong anticyclonic circulation. At this time, the lower layer vortex has been strengthened to TC. This process can be represented by Fig. 6.28.

6.3.2 Formation, Intensity and Track of Tropical Cyclones in the South China Sea The generation of TC is closely related to dynamic and thermal factors such as sea surface temperature (SST), middle tropospheric humidity, and vertical wind shear

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Fig. 6.28 Diagram of TC Usagi generation process caused by middle-level vortex in the South China Sea (Yuan and Wang 2014) a early; b Downward development stage; c TC generation phase. ‘ + ’ represents warm center; ‘−’ stands for cold center

(Gray 1979; Camargo et al. 2007; Chia and Ropelewski 2002). The inter-annual variation of the frequency of TC generation in the South China Sea is largely related to ENSO (Lee et al. 2006). Recent studies have shown that the frequency of TC generation in the South China Sea will increase in the next year of El Niño, mainly because El Niño will warm the Indian Ocean the following year, triggering Kelvin fluctuations and spreading eastward to the western Pacific (Xie et al. 2009), thus affecting the large-scale circulation in the Western Pacific and South China Sea. Conversely, the vertical wind shear is reduced in the South China Sea, which is conducive to the generation of TC in the South China Sea (Du et al. 2011; Zhan et al. 2011). In addition, many studies have shown that the generation of TC in the South China Sea is also closely related to the East Asian monsoon on different scales (Wang et al. 2012; Li and Zhou 2013). The interaction between TC and its environmental field affects the airflow field around it, and the vortex is guided by the advection effect of this airflow field. In addition, sudden changes in TC movement are often caused by the adjustment of large-scale circulations, such as the advance and retreat of the subtropical high, the break of the tropical convergence zone (ITCZ), the formation and retreat of the equatorial buffer zone, the propagation of planetary waves, and the alternation of trade wind and monsoon. The transition of the large-scale circulation from one state to another will cause a sudden change of the guiding air flow around TC, which will lead to a sudden change of the path. The movement of TC is mainly the result of the interaction of the following five basic factors: Large scale circulation guiding airflow, the interaction of different scale circulation systems, the β effect, the asymmetric structure of typhoon vortex and the influence of underlying surface. The guiding flow of large-scale circulation is the main controlling factor of TC movement, and its dominant factor accounts for 70–90% (englebretson, 1992). Both numerical simulation and observational studies show that the β effect term has a

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strong systematic shift to the TC path only when the TC intensity is very weak (Carr and elsberry 1990; Franklin et al. 1996). The guiding airflow is usually defined as the vertical integral of the atmosphere, which usually represents an average current of large-scale circulation guiding TC movement (Holland 1983). There are different choices for different researches on the height of the integral of the atmosphere. For example, Chu et al. (2012) chose 850–300 hPa as the integration layer, while Chan and Gray (1982) believed that the 900–200 hPa wind field integration had the best correlation with the TC movement path. Most of the TC will move under the action of large-scale background guiding airflow, but some TC paths will be different from the large-scale background guiding airflow, or even on the contrary, these TC are guided by the abnormal guiding airflow caused by other abnormal ocean or climate factors. The formation and path of TC in the South China Sea are also closely related to the position of the monsoon trough (Xie et al. 2003). The monsoon trough is a trough formed by the convergence of the cross-equatorial airflow and the trade wind airflow. The monsoon trough plays a significant role in the South China Sea, which not only provides favorable dynamic conditions for TC activity, but also has an important impact on the path of tropical cyclones. The monsoon trough in the South China Sea began to strengthen in May and lingered in the northern part of the South China Sea until it moved to the southern part of the South China Sea after September. The average location of TC generation in the South China Sea is generally several latitudes away from the location of the monsoon trough (Chia and Ropelewski 2002). For example, in October, the average position of TC in the South China Sea is in the middle of the South China Sea (13° N), while the monsoon trough has moved to the south of the South China Sea (south of 10° N).

6.3.2.1

Numerical Simulation and Analysis of Individual Cases

This part takes the process of typhoons ‘Pearl’ (2006) and ‘Dujuan’ (2010) as examples, and uses numerical simulation to study the intensity of TC and its path changes. (1) Typhoon Pearl (2006) Typhoon Pearl (2006) was the first tropical cyclone to enter the South China Sea in 2006, and its maximum sustained wind speed reached 46 m/s during its rapid strengthening. It is the strongest typhoon that entered the South China Sea in May in the history of the Hong Kong Observatory. Pearl was formed in the Western Pacific on May 8, 2006, with an intensity level of tropical depression. After that, it quickly intensified to typhoon level and entered the South China Sea on May 13 after making landfall twice in the Philippine Islands. Pearl strengthened rapidly after entering the South China Sea and became a typhoon of category 4 (Saffir Simpson classification) after May 14. After entering the South China Sea, pearl first moved along the northwest direction, then quickly turned to the northeast direction, and finally landed near Shantou in the east of Guangdong Province.

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In this part, MM5 is used to simulate typhoon and compare with satellite and reanalysis data. Data includes latent heat retrieved by OAflux (Objectively Analyzed air-sea Fluxes) and AMSRE (the Advanced Microwave Scanning Radiometer-Earth Observing System), three-hour precipitation from TRMM (the Tropical Rainfall Measuring Mission satellite), the wind field retrieved by QuikSCAT (quikscatter), precipitation data of 86 stations in Guangdong Province and JTWC typhoon data. A total of 5 experiments were designed (1 control experiment and 4 sensitivity experiments). All simulations were run from 00:00 on May 12, 2006, when Pearl (2006) was about to enter the South China Sea. The model has two nested simulation areas, the accuracy of the large area and the small area are 15 km and 5 km, respectively. There are 27 vertical layers. The NCEP FNL (Final) Operational Global Analysis data are used as the initial and boundary conditions of the model. The lower boundary condition of the model is driven by the global sea surface temperature data (RTG). Blackdar boundary layer, resiner 2 humidity and Betts Miller cumulus parameterization were used in the control experiment (CTL). The 4 sensitivity tests were carried out using MRF boundary layer scheme (PBL_MRF), Grell Cumulus Parameterization Scheme (CUM_G), SST remained unchanged during the whole typhoon development (SST_C). The 4 sensitivity tests adopted MRF’s boundary layer scheme (PBL_MRF), Grell cumulus parameterization scheme (CUM_G), keeping sea temperature constant during the entire typhoon development process (SST_C), and the boundary condition of the warm pool with uniform meridional distribution (SST_U) on the day before the typhoon intensified. During the movement and development of typhoon Pearl (2006) in the South China Sea, according to the characteristics of its path, it can be divided into two parts: westward and northeastward. All the results of the model can simulate the northeast part of the path better, but the simulation of the west part is quite different. The moving speed of the typhoon in the northeast part simulated by PBL_MRF is the closest to the observed moving speed, while other experimental models all overestimate the moving speed of the typhoon, which results in the difference between the landing site and the actual landing site of about 200 km (that is, in the north of the actual landing site).. In the simulation process of the northeast part of the typhoon, except for PBL_MRF, the paths simulated by the other 4 modes are all easterly, and the path deviation simulated by CTL is the smallest. The simulation results show that the Grell cumulus parameterization scheme or the different distribution of sea temperature have no obvious influence on the typhoon path, but the difference of the MRF boundary layer scheme (PBL_MRF) obviously affects the typhoon path. The use of the MRF boundary layer scheme will result in lower humidity in the boundary layer, which may mean that the warm and humid air coming from the Bay of Bengal or the southern hemisphere is weaker, which may cause strong northern dry and cold air to invade southward, thereby making the position of the subtropical high eastward. The location of the subtropical high is usually considered as the dominant airflow controlling the typhoon path. Therefore, different boundary layer structures, especially the parameterization schemes related to humidity, may affect the path of typhoon.

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The results show that the CTL model can simulate the central pressure well in the stage of typhoon rapid strengthening, but it overestimates the intensity growth rate in the early stage of typhoon entering the South China Sea. The simulation of the maximum wind speed of the typhoon by all models is lower than the observation. The MRF parameterization scheme tends to produce excessively strong vertical mixing, which can reach 2–3 km around the eye wall of the typhoon, which leads to the dry boundary layer of its simulation. Therefore, PBL_MRF tends to simulate a weaker typhoon with the highest central pressure and the lowest maximum wind speed. The result of CUM_G is similar to that of PBL_MRF, except that the simulated typhoon intensity is slightly stronger than that of PBL_MRF. If the sea temperature is kept constant during the development of the typhoon, since more latent heat flux will be transported from the ocean to the atmosphere, the simulated typhoon will be stronger. This phenomenon becomes more obvious after the typhoon strengthens rapidly, which is consistent with the previous research results. Using a uniform sea temperature distribution before the typhoon rapidly intensifies is equivalent to weakening the sea temperature around the typhoon, that is, the ocean provides less energy to the typhoon than the control experiment, so the simulated typhoon intensity will also be weakened. The air-sea latent heat flux below the center of the typhoon plays a vital role in the formation and rapid intensification of the typhoon. Latent heat flux is usually calculated by the block formula, which mainly requires some surface meteorological variables, such as surface wind speed, atmospheric temperature, ocean surface temperature, atmospheric specific humidity and sea surface saturation humidity. These variables can be obtained in a variety of ways, such as ship ocean surface weather reports, satellite remote sensing observations, and numerical weather prediction models. In the process of tropical cyclone development, especially in the case of strong typhoon, direct observation is almost impossible. Therefore, satellite remote sensing is the best way to obtain all kinds of data in the case of typhoon. At present, both the latent heat retrieved by TMI and that from OAflux are widely used latent heat flux products. However, these remote sensing data have certain limitations in the presence of typhoons. In this study, the latent heat flux simulated by the model is mainly compared with the latent heat flux calculated by AMSRE inversion and the latent heat flux and sensible heat flux of OAflux. The latent heat flux, sensible heat flux and 6-h accumulated precipitation in the region of 800 km around the typhoon center along the track of the typhoon were calculated and compared with the satellite data. The results show that the simulated latent heat fluxes of PBL_MRF, CUM_G and SST_C will have a significant increase during the rapid strengthening of the typhoon, which is consistent with the AMSRE observation, but the result of OAflux observation is not obvious. The increase in latent heat flux simulated by CTL and SST_U during the development of the typhoon is relatively reasonable (Fig. 6.29).Satellite observations have greater technical limitations under severe weather conditions. For example, QuikSCAT has a large error when the wind speed is greater than 40 m/s. Although OAflux and AMSRE are considered better flux products, the evaluation of these data is usually only carried out under normal weather conditions. Under typhoon conditions, the usefulness of

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Fig. 6.29 Time variation series of latent heat flux observed by model simulation and AMSRE and OAflux (a) and time variation series of sensible heat flux observed by model simulation and OAflux (b)

these data will be questioned. Typhoon Pearl exceeded 40 m/s on May 14, which is the error limit of the QuikSCAT wind field. In the development of Pearl, the latent heat flux of AMSRE is more reasonable than that of OAflux. The latent heat flux correlation between CTL and AMSRE is the best, although the former is much higher in magnitude than the latter. This higher part of the latent heat flux may be related to the initial vortex placed at the beginning of the simulation or the sea temperature data using RTG. The model’s simulation of sensible thermal data has similar results. In addition to CTL and SST_U, PBL_MRF also has good results for the simulation of sensible heat flux. The high sensible heat flux simulated by SST_C is mainly caused by ignoring the sea temperature cooling caused by the typhoon. The main difference between the 6-h accumulated precipitation simulated by the model and the TRMM result is reflected in the period of time before the typhoon rapidly intensified. This is because the TRMM data is affected by islands and other topography. There is biggest simulation error for the rapid strengthening of the typhoon in the result of SST_C. CTL and SST_U had a low estimate of precipitation before the typhoon strengthened rapidly, with an amplitude of about 10 mm. Comparing the results of simulation and satellite observation in the early stage of typhoon Intensification (May 14), during the intensification (May 15) and after the intensification (May 17), it is found that compared with the satellite data, the five models have higher estimates of precipitation and lower estimates of maximum wind speed. Larger precipitation areas are mainly concentrated on the west and northwest sides of the precipitation center. Using the MRF boundary layer scheme will greatly underestimate the intensity of the typhoon, which is also reflected in the simulation of the maximum wind speed. The constant sea surface temperature during the development of typhoon will provide more energy for the development of the typhoon, resulting in a significant increase in the intensity of the typhoon and an overestimation of precipitation and maximum wind speed. Different atmospheric boundary layer conditions and cumulus parameterization schemes can lead to changes in latent heat and precipitation, but will not affect typhoon intensity, maximum wind speed and central pressure. However, the change of SST not only affects the latent heat and precipitation, but also affects the intensity of typhoon.

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(2) Typhoon Dujuan (2003) On August 28, 2003, Typhoon Rhododendron forms in the Northwest Pacific east of the Philippines, and then moved mainly along the west-northwest path. It entered the South China Sea through Bashi Strait at about 18:00 on September 1, and then continued to move along the west-northwest direction. It landed in Shenzhen at about 12:00 on the 2nd. On the 3rd, it entered Guangxi Province and weakened to a low pressure and gradually disappeared. The changes of SST play an important role in the development of TC. Compared with the weekly-mean SST, the daily-mean SST has higher temporal resolution, which can reflect a more detailed SST spatial distribution, and can be used as an example of different distribution of SST. This study mainly discusses the different effects of using daily-mean and weekly-mean SST (TMI-AMSRE) as the underlying surface input of the model simulation on the path and intensity of typhoon Dujuan. Compared with the observation, the path simulated by the model is closer to the observation except that the position of 12 h is obviously northward, and the path errors of 24 and 48 h are within 200 km. In the first 24 h, the daily-mean SST and the weekly-mean SST simulated typhoon tracks were similar. However, in general, the simulation results of daily-mean SST in the first 36 h are closer to the observation than those of weekly-mean SST. While after 36 h, the simulation results of weeklymean SST are closer to the observation than those of daily-mean SST. It indicates that different SST has a certain impact on the simulation of Typhoon Dujuan. The typhoon intensity simulated by daily-mean SST is slightly weaker than that simulated by weekly-mean SST. From the simulation results, the difference of the sea surface wind field will be quickly triggered at the maximum value of the SST difference, and will affect other areas along with the model integration; as the typhoon moves and makes landfall, there are obvious differences in the surface wind field near the typhoon. Within the typhoon circulation range, different SST will affect the water vapor transport from the ocean to the atmosphere, which in turn affects the precipitation caused by the typhoon. The daily-mean SST simulated typhoon 24 h precipitation is mainly distributed in the south of the typhoon center, and there are many large precipitation centers. The daily-mean and weekly-mean SST simulated 24 h precipitation have obvious differences, and the maximum precipitation difference is more than 40 mm (located at 21.5° N, 116.5° E) (Fig. 6.30). At the same time, the large precipitation difference area is more consistent with the large SST difference area in the northern part of the South China Sea. As the thermal forcing source of underlying surface, the tropical ocean also affects the upper atmosphere in the form of heat transfer. The latent and sensible heat fluxes simulated by daily-mean SST are significantly higher than those simulated by weekly-mean SST. On the one hand, it is conducive to the transport of water vapor from the ocean to the atmosphere, on the other hand, it is also conducive to reducing the cooling effect of typhoon. The latent heat flux is an order of magnitude larger than the sensible heat flux, indicating that the latent heat flux is relatively more important, which is also consistent with actual observations.

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Fig. 6.30 Daily average a 24 h typhoon precipitation simulated by TMI-AMSRE SST and daily and weekly average b 24 h typhoon precipitation difference simulated by TMI-AMSRE SST (unit: mm) (Chen et al. 2009)

6.3.2.2

Path Characteristic Analysis

(1) Seasonal and inter-annual variations This study first used the ‘mixed polynomial regression curve classification model’ to conduct 20 random experiments on the local generated TC paths in the South China Sea from 1980 to 2009, and then classified them into three categories: ➀ northwestern; ➁ westward; ➂ northward. From 1980 to 2009, there were 63 cases of TC generation, of which the northwest route was the most (34 cases), the westward route was the second (24 cases), and the northward route was the least (only 5 cases). From the spatial distribution of the initial generation locations of the three types of TC, it can be seen that for more than half of the northwest TCs, the generation locations are mainly distributed in the central and northern parts of the South China Sea. In addition to the west of the Philippine Islands in longitude, the westward TCs are distributed in the north and south of the South China Sea. The overall spatial distribution is relatively uniform in the latitude direction, and the path of such TCs is relatively lon. The generation locations of the 5 northward TCs are scattered near the Paracel Islands and Zhongsha Islands in the northern part of the South China Sea. The westward and northwestern TCs generated locally in the South China Sea have significant ‘single peaks’ in frequency. The the peak values are located in September during the summer winter monsoon transition period, partly due to the smaller vertical shear of the horizontal wind field during the monsoon transition period, which is conducive to the development of the sea surface tropical disturbance. The westward TCs decreased month by month after September, mainly due to the gradual prevalence of the strong northeast monsoon. The second peak of westward TCs is in October, while that of northwest TCs is in August. The seasonal distribution of westward TCs and northwestern TCs is relay. The northwestern path mostly occurs during the summer monsoon season, that is, from May when the summer monsoon erupts on a large scale to October when the summer monsoon begins to recede; while

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the westward path mainly occurs from September to November when the winter monsoon begins. In addition, 3 of the 5 northward TCs occurred during the monsoon transition period (April to May and September), and the other 2 cases occurred in midsummer (August). The time correlation was not significant. In terms of interannual variation, the TC of the northwestern route in El Niño was more than that of the westward route. The westward and northward routes increased significantly in the strong El Niño event. In the strong La Niña events from 1998 to 1999, the westward path increased significantly. During 1980–2009, 2/5 of the northward tropical cyclones occurred in 1999. (2) Steering flow There are different degrees of easterly components of the three types of TC guiding flow in the central and northern South China Sea, and the easterly airflow is mainly constrained by the anticyclonic circulation system in the north and the cyclonic circulation system in the south (Fig. 6.31). Among them, the easterly steering airflow of the northwestern tropical cyclone has a relatively significant southerly component; the easterly guiding airflow of the westward TC is the most straight and broad. In the vicinity of the Paracel Islands and Zhongsha Islands where the generation locations of northward TCs are concentrated, the easterly airflow is weak and uneven. From the 500 hPa geopotential height composite field, it can be seen that when the northwestern and northward tropical cyclones occur, the westward extension of the West Pacific Subtropical High is not obvious, and the west ridge point is located east of 135° E. The 5870 gpm line outside the main body of the subtropical high does not extend to the air over the mainland, and the overall shape is meridional. When the westward tropical cyclone occur, the westward extension of the WPSH is the most significant, and the west ridge point can reach 125° E. The 5870 gpm line outside the main body of the WPSH can cover most areas of Guangdong and Fujian, and the overall form of the zonal type is significant. When the northwestern and westward TC occur, the central axis of the WPSH is maintained near 25° N, while when the northward TC occurs, the WPSH is relatively southward. (3) Relationship with ISO The TC paths generated locally in the South China Sea are further classified into westward (including northwest, southwest, and due west) and eastward (including northeast, southeast, and due east). The eastward TC mainly landed in Taiwan, the Philippines and Japan, among them, TC mainly landed in Taiwan in China and occasionally turned back to land in southern China, while the westward TC landed mainly in southern China and the coast of Vietnam. Although the research on the western Pacific TC roughly includes the TC generated locally in the South China Sea, the intensity, frequency and path of TC generated locally in the South China Sea are different from those in the Western Pacific. Its uniqueness indicates that it is necessary to study it separately. From 1970 to 2010, a total of 154 TCs were formed in the South China Sea from April to September, 105 of which moved westward and 49 eastward. The TC moving westward showed a significant seasonal change, reaching a peak in September, while

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Fig. 6.31 Steering flow field of three types of locally generated tropical cyclones in the South China Sea (synthesis of all days during the life of each tropical cyclone) Shaded area the area that passes the significance test with a confidence of 95%

the TC moving eastward had no obvious seasonal change, and the peak was in May. Although the total number of TC did not change significantly from May to July, the proportion of eastbound to westbound TC changed significantly. From July to December, this ratio was significantly less than 1, that is, after July, the westward TCs were significantly more than the eastward TCs, and from May to July, the eastward TCs were basically more than the westward TCs. This research mainly discusses the period of frequent TC activities in the South China Sea, namely June to October (JJASO). During the JJASO period, most of the TCs (84) were westward, and only 29 TCs were eastward. Most of the TC generated in the northern part of the South China Sea, which was mainly controlled by the southeast airflow and would lead most of the TC westward. However, 1/3 of the TC runs counter to the large-scale background circulation. The 20–100-day filtered OLR field and TC steering flow field were synthesized and analyzed according to the first three days of the eastward and westward path occurrence time (Fig. 6.32). During JJASO, for both eastward and westward paths, positive convection dominated the whole South China Sea and the northern part of the Northwest Pacific. During the eastward TC period, the positive convective activity anomaly area is in the southwest-northeast direction. The two maximum areas were located in the northern South China Sea and the seas east of the Philippines, and the convective activity is stronger in the east of the Philippines. The ISO convective activity caused strong eastward guiding airflow anomalies in the main generating area of TC and east of the Philippines. The eastward TCs are mainly distributed on the main axis of the eastward guiding anomalous airflow, which reflects the importance

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Fig. 6.32 Steering airflow and OLR filtered for 20–100 days during JJASO (Yang et al. 2015). Black dots represent TC generation positions

of anomalous guiding airflow to the TC path. The eastward guided airflow anomaly caused by ISO is of the same magnitude as the original easterly guiding airflow in the area. That is to say, the eastward guided airflow anomaly caused by ISO plays a decisive role in the eastward movement of TC. The composition analysis of westward TC shows that the Northwest Pacific including the South China Sea is also dominated by positive convection. However, whether it is the intensity of convective activity or the guide airflow abnormality caused by convective activity, the westward period is significantly weaker than the eastward period. During the westward, the positive convective activity anomalous area is west-eastward. In the main generation area of TC, the anomalous guiding flow caused by the convective activity is very weak compared with the original westward guiding flow, so it has little effect on the path of TC. Strong guiding airflow anomalies occurred in the southern South China Sea, while TC was rarely generated in this area during JJASO (Xie et al. 2003). In order to further study the seasonal changes of the relationship between TC path and ISO, the TC season during JJASO is divided into two phases: June to August (JJA) and September to October (SO). It is found that 70% of the eastward TC during the JJASO period occurred in the JJA phase, while the westbound TC occurred in the JJA and SO phases in equal numbers. The distribution of convective activities related to ISO is similar in the two phases. During the eastbound path, both JJA and SO have strong convective activity centers in the South China Sea and the Western Pacific. In contrast, it is stronger in the South China Sea during JJA and in the Western Pacific during SO. Moreover, the anomalous distribution of convective activity during JJA is more compact than that during SO. During JJA, the ISO related convective activities extended from the South China Sea to the northern part of the Northwest Pacific. The maximum value of the convection was in the western part of the Luzon Strait, which caused a strong eastward guiding current anomaly. During the SO period, the convective activity area was decomposed into two parts, one located in the South China Sea, with a west–east direction, and the other located to the east of the Philippine Islands, with a southwest-northeast direction. The overall effect of the change of the convective activity modal from JJA to SO is that part of the guided airflow caused by the two convective activity centers will cancel each other, resulting in weakening of the eastward guiding flow.

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Using a simple two-layer model (Lee et al. 2009) and using the OLR anomalies during the eastbound and westbound paths as the forcing fields, the relationship between ISO convective activities and the induced flow anomalies is further confirmed. The model results of the eastward path show that there are cyclonic and anticyclonic circulation in East Asia and Northwest Pacific respectively. The anticyclonic circulation is northwest-southeast, corresponding to strong westerly winds (750–250 hPa) in the South China Sea and the Northwest Pacific. However, the barotropic flow caused by the OLR anomaly during the westward path is significantly weakened and relaxed in the South China Sea (Fig. 6.33). From the difference between the two, we can see that there is a strong westerly barotropic anomaly in the South China Sea, especially in the northern part of the South China Sea, corresponding to the eastward path of TC.

Fig. 6.33 Barotropic streamfunction (contour, 106 m2 s-1 ) and wind (vector, m s-1 ) from the simple model runs. a and b are the model responses to the composited OLR anomalies in Fig. 6.33 c, d, respectively. c is the differences between a and b (a - b). The zero lines are thickened. The contour interval is 0.5*106 m2 s-1 . Positive pressure flow function and (c) difference between JJASO eastbound and westbound paths using OLR anomaly field as forced field (Yang et al. 2015)

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6.3.3 Interannual and Interdecadal Variability of Tropical Cyclone Formation Frequency Over the South China Sea The TC path is closely related to the anomalies of large-scale wind fields caused by different ENSO phases. The traditional El Niño refers to the sea temperature anomaly in the eastern Pacific. However, in recent 20 years, scientists have discovered a new El Nino associated with the sea surface temperature anomaly in the central Pacific— Central Pacific El Nino or pseudo El Nino (Ashok et al. 2007). Currently, EMI and Niño 3.4 indexes are generally used as the criterion for the Central El Niño (CP) and Eastern El Niño (EP) events (Chen and Tam 2010).

6.3.3.1

Annual Variation

In this study, the TC data provided by IBTrACs were used to explore the influence mechanism of CP and EP El Niño on TC formation in the South China Sea from 1965 to 2010. According to the two types of El Niño indexes, 6 events were selected from 1965 to 2010, respectively, which were CP (1968/1969, 1990/1991, 1994/1995, 2002/2003, 2004/2005 and 2009/2010), and EP (1965/1966, 1972/1973, 1982/1983, 1991/1992, 1997/1998 and 2006/2007). Seven La Nina events (1970/1971, 1973/1974, 1975/1976, 1988/1989, 1998/1999, 1999/2000 and 2007/2008) were also selected. TC in the South China Sea mainly occurs from May to November. In this study, the TC generation season is divided into summer (JJA) and autumn (SON). In addition to the obvious difference in the generation location, the law of time variation is also obviously different. During the JJA period, the interannual change of TC is not obvious, while the interdecadal change was relatively prominent. The frequency of TC increased significantly after the 1970s than before (Kim et al. 2011); for the SON period, the interannual change of TC was significant, which may Related to ENSO. This study mainly discusses the relationship between the interannual variation of TC generation and two kinds of El Niños in ENSO development years. In son period, the correlation between TC and EP index is poor, but the correlation between TC and CP index is 1–3 months ahead. This relationship is gradually strengthened from JJA of the previous year, which indicates that CP index in late summer and early autumn can be used as a good precursor of TC generation in son period. During the JJA period, the TC generation has a weaker relationship with the CP index, but it has a close relationship with the East Asian summer monsoon. In recent 10 years, the frequency of EP-type El Niño has decreased, while that of CP-type has increased (Ashok et al. 2007). At the same time, the SST of the South China Sea also showed interdecadal variation around 1970 (Wang et al. 2010a, b). Using spectral analysis method, Wang et al. (2010a, b) found that the interannual variation of TC in 1978–2010 was significantly stronger than that in 1965–1977; using wavelet analysis method, they analyzed the

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relationship between CP El Niño index and TC generation during son, and found that they had a significant negative correlation. (1) Thermodynamic factor Thermal factors such as SST and humidity in the middle troposphere affect the generation of TC. Deep convection can only develop when the SST is above 28 °C, and only in the southern part of the South China Sea can reach this temperature in autumn. SST was significantly different in two different El Nino events. SST warm anomaly corresponding to EP El Nino is mainly in the east of the South China Sea, which is related to the El Nino driven atmospheric and marine circulation (Xie et al. 2003; Liu et al. 2006). (Xie et al. 2003; Liu et al. 2006). Generally, SST warm anomaly can provide enough water vapor to the sea and air boundary to supply the development of deep convection. However, EP El Nino index is negatively correlated with TC generation index, which indicates that the thermal or dynamic factors other than SST have a stronger influence on TC generation. In contrast, CP El Nino has a weak influence on the positive SST anomaly in the South China Sea, and the significant negative SST anomaly occurs in the east of the Philippines. The second thermal factor related to TC generation is the humidity in the middle troposphere. During the two El Niño events, the middle layer of the South China Sea was dry, and the humidity during the CP El Niño was lower, which was not conducive to the formation of TC. (2) Dynamic factor During the EP and CP El Niño periods, an anticyclone will form in the Northwest Pacific. The anticyclone associated with CP El Niño is significantly stronger than EP El Niño. At 500 hPa, although the teleconnection of the two types of El Niño events in the South China Sea is significant, the northerly or northeasterly wind associated with the CP-type El Niño is significantly stronger. At the lower level, CP El Niño will cause a significant anticyclonic circulation anomaly in the South China Sea, and a cyclonic circulation anomaly in the Western Pacific, which will lead to an abnormal increase in the northeasterly wind in the South China Sea. While the EP type El Niño is in the lower layer. The impact on the South China Sea is weak (Ashok et al. 2007; Chen and Tam 2010). The maintenance of humidity in the middle of the South China Sea mainly depends on local evaporation and external water vapor transport. Although EP-type El Niño can cause warm SST anomalies, the low and middle atmosphere wind speeds are abnormally weak, which is not conducive to evaporation, so the water vapor in the middle atmosphere can be maintained, while the strong and dry northeast wind caused by CP-type El Niño in the South China Sea is conducive to evaporation., Resulting in a dry middle atmosphere. The vertical wind shear abnormalities caused by the two types of El Niño in the South China Sea are obviously different. The EP-type El Niño index has a weaker relationship with the vertical shear of the wind in the central South China Sea, while the CP-type El Niño shows a strong positive vertical wind shear. This indicates that the warm anomaly in the central Western Pacific can cause the vertical wind shear to increase in the South China Sea. Conducive to TC generation.

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373

Decadal Variation

(1) Association with variation of East Asian summer monsoon About half of the TC generation frequency (49.2%) of the South China Sea TC generation frequency from 1965 to 2004 was generated in summer (June to August, JJA). The frequency of TC generation in autumn (September to November, SON) is second only to summer. In winter and spring, TC is rarely generated, accounting for about 3% and 11%, respectively. The location of TC generation in the South China Sea also has obvious seasonal changes. About 82% of TCs are formed north of 15oN in summer, and about 66.7% are formed south of 15oN in winter (Lee et al. 2006). The change of TC generation position with latitude is considered to be related to the meridional displacement of the East Asian Summer Monsoon (EASM). The following discussion is divided into two seasons: summer (JJA) and autumn (SON). The results of spectrum analysis show that there is a significant 10-year cycle in the formation of TC in the South China Sea, while the autumn TC shows a 4-year cycle of inter-annual variation. Therefore, it can be considered that the decadal TC generation frequency changes mainly occur in summer. The 11-year moving average of summer TC frequency shows that the number of TCs was relatively small from the mid-1970s to the mid-1990s, and the number of TCs was relatively high before the mid-1970s and after the mid-1990s. Since summer TC is mainly generated in the northern part of the South China Sea, we used the Lepage method to further confirm the interdecadal variation of summer TC in the northern part of the South China Sea (Fig. 6.34). There were two major mutations in EASM from 1965 to 2004, namely in the late 1970s (Li et al. 2010) and 1993–1994 (Wu et al. 2010). In response to the interdecadal changes of EASM, the summer TC generated in the South China Sea was divided into two periods, 1965–1974 and 1995–2004, when TC generation was relatively Fig. 6.34 Time series (solid line) and 11-year average (dashed line) of TC frequency anomalies in the northern South China Sea in summer a and Lepage test of TC generation frequency in the northern South China Sea b (Wang et al. 2012). The solid and dotted lines in figure b represent the Lepage test with more than 90% and 95% confidence, respectively

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high, and 1979–1993, when TC generation was relatively low. The frequency of TC generation is 1.9, 0.8 and 2 in the above three periods respectively. The annual average frequency changes of more and less than 95% confidence level. By comparing the vertical wind shear during the periods of high and low, it is found that the periods of high TC correspond to significant weak windshear. The East Asian Jet (EAJS) is an important component of EASM and is closely related to climate change in East Asia. The empirical orthogonal decomposition (EOF) of the 200 hPa summer zonal wind is carried out to analyze the changing law of EAJS. The principal component (PC1) of the first mode (34%) shows that there is a meridional dipole structure, and the zero line is located near 40° N, which means that EAJS has a meridional displacement, which is consistent with the results of previous studies. The principal component (PC2) of the second mode (19%) shows a sandwich structure in the meridional direction, which is positive in the regions of 30°–45° N and 80°–130° E, while in the south and north All are negative values. PC1 has a significant interdecadal change, with a displacement to the equator in the late 1970s, and PC2 also has a significant interdecadal change, that is, it was stronger from 1979 to 1993 and weaker in the other two stages. Here, PC1 and PC2 can be considered to represent the meridional position and strength of EAJS, respectively. The WNPSH index (average field of 500 hPa geopotential height anomalies: 10°– 30° N, 120°–140° E) also showed obvious interdecadal changes, that is, there was a clear trend of westward extension in the late 1970s. From 1995 to 2004, TC generation was significantly correlated with the meridional position of EAJS, from 1965 to 1974 and from 1995 to 2004, it was significantly correlated with the intensity of EAJS, and from 1979 to 1993, it was significantly correlated with WNPSH. Although the extent of westward extension of WNPSH in 1995–2004 was higher than that in 1979–1993, the intensity of EAJS was higher in 1979–1993 than in 1995–2005, so it has a greater impact on vertical wind shear. (2) Association with atmospheric and marine factor changes Some recent studies have found that there were interdecadal variability in the East Asian and Western Pacific summer monsoons in the mid-1990s (Kwon et al. 2005, 2007; Yim et al. 2008). The intensity of the zonal wind in the East Asian subtropical jet area gradually decreased after the mid-1990s, accompanied by a significant increase in precipitation in South China (Kwon et al. 2007). The attenuation of the zonal wind is a positive pressure response to the increase in precipitation and the release of heat in the area (Kwon et al. 2007). The relationship between the East Asian and Western Pacific monsoons also showed interdecadal changes from 1993 to 1994. From 1994 to 2004, the correlation between the two monsoon systems was very strong, and the correlation was significantly weakened from 1979 to 1993 (Kwon et al. 2005). The average summer rainfall in East Asia and the Western Pacific has changed from a mode related to ENSO from 1979 to 1993 to a mode related to the western Pacific monsoon (Kwon et al. 2005). These results have been verified in the hybrid coupling model (Yim et al. 2008). From 1970 to 1992, the precipitation in South China was always low, but from 1993 to 2004 it was above average. This significant change in precipitation is believed to be related to the weakening of the East Asian

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summer monsoon (Kwon et al. 2007), and the corresponding increase in low-level convergence and upper-level divergence (Wu et al. 2010). The weakening of summer monsoon is thought to be related to the increase in snow cover on the Qinghai-Tibet Plateau in early spring and the decrease in sea-land temperature differences caused by the increase in sea temperature in the Central and Eastern Pacific (Wu et al. 2010). Wu et al. (2010) found that the South China Sea-Northwest Pacific and North ChinaMongolia were two abnormal high-pressure centers during 1993–2002, compared to 1980–1992. The appearance of these two high-pressure centers is directly related to the increase in precipitation in South China. The increase in typhoon activity in the western Pacific may also be part of the reason for the increase in precipitation in southern China after the mid-1990s (Kwon et al. 2007). This study mainly discusses the interdecadal changes and mechanisms of TC activities in the South China Sea by discussing changes in atmospheric and ocean factors. Figure 6.35 shows the July–September (JAS) TC in the South China Sea from 1979 to 2010, including the frequency of strong TC (Cat4) generation and the corresponding inter-annual variation of the monthly mean sea surface temperature (SST) in the South China Sea. It can be seen that the tropical cyclone activity and SST in the South China Sea have obvious characteristics of interdecadal variability, and there was an obvious jump after 1993, that is to say, the frequency of TC increased significantly after that. During the JAS period from 1979 to 1993, only 17 TCs were generated in the South China Sea, while 43 TCs were generated from 1994 to 2008. However, TC generated locally in the South China Sea rarely reaches the level of a super typhoon. Among the TCs in Zhongnanhai in the past 30 years, only one TC reached the super typhoon level (level 4) in 1995. Warm SST can provide enough energy for the generation and development of TC (Gray 1968). In the corresponding time period, the TC frequency in the western Pacific has a clear downward trend, reflecting the opposite relationship between the East Asian and western Pacific summer monsoons (Kwon et al. 2005). It can be seen from the seasonal variation chart of TC (Fig. 6.36) that there were no TCs generated in July from 1979 to 1993, and 13 TCs were generated at the same time from 1994 to 2008. The small vertical wind shear and high SST correspond to the frequent seasons of TC, showing the important influence of environmental factors on the generation of TC. The disparity of TC generation frequency between 1985–1993 and 1994–2002 is more obvious. There were 33 TCs from July to September from 1994 to 2002, while there were only 8 TCs from 1985 to 1993 in the corresponding months. The difference between SST and the upper ocean heat content shows that in the latter stage, the SST in the northern part of the South China Sea is generally warmer than the previous stage, but the upper heat content is not higher overall, but some areas are lower, indicating that the upper heat content cannot be fully reflected. The generation mechanism of weaker TC. In the atmosphere, small vertical wind shear, high middle-level humidity, low-level relative vorticity, and strong convective activity can all provide favorable conditions for the generation and development of TC. The subtropical high belt was obviously westward in the previous stage, which means that the previous stage was controlled by a stronger subtropical high compared

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Fig. 6.35 Interannual variation of JAS TC (gray) and strong TC (Cat4, black) frequency and regional monthly mean SST in the South China Sea from 1979 to 2010 (Yang et al. 2012)

to the latter stage, which inhibited the development of convective activities and was not conducive to the formation of TC. From the perspective of large-scale circulation differences, the entire Indian Ocean, South China Sea, and Western Pacific have a significant warming trend from 1994 to 2002. This warming is more obvious in the Kuroshio extension area and may be related to the northward shift of the subtropical high (Fig. 6.37). The outflow (northeast wind) from the high-pressure anomaly center located in the northern part of my country and the Kuroshio extension area meets the southwest warm humid air from the South China Sea to form a cyclonic circulation, which is conducive to the generation and development of TC in the northern part of the South China Sea.

6.4 Intra-seasonal Signals of Upper Ocean and Atmospheric Anomalies in the South China Sea The South China Sea monsoon is an important component of the East Asian monsoon. The South China Sea summer monsoon erupts first in the Asian summer monsoon, about mid-May each year (Yan 1997). The onset of the South China Sea summer monsoon will affect the strength of the summer monsoon. It will also have a significant impact on my country’s rainfall during the flood season. It also has an important effect on the atmospheric circulation and climate in East Asia and the Northern Hemisphere. The South China Sea atmospheric circulation is an atmospheric circulation system regulated by multiple scales. In terms of energy, seasonal changes take the first place, followed by intraseasonal changes (Ding et al. 2004). Thirdly, changes in weather scales of 2–8 days and changes in interannual scales also have an important impact on the atmosphere of the South China Sea.

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Fig. 6.36 Monthly variations of TC frequency and regional SST from 1979 to 1993 and 1994 to 2008 (Yang et al. 2012)

The South China Sea is a sensitive sea area for the Asian monsoon. Changes in the thermal structure of the upper ocean (including heat content and sea temperature, etc.) have an extremely important impact on the atmospheric circulation, especially the East Asian monsoon and the weather and climate in southern my country (Wang and Qin 1997; Zhou et al. 1999). The intra-seasonal signals and weather-scale (including the influence of extreme weather) signals in the abnormal signals of the ocean and atmosphere in the South China Sea have a non-negligible impact on my country’s climate, and even affect the weather changes in the entire northern hemisphere.

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Fig. 6.37 Differences of OLR field (isoline, W/m2), SST (shadow, °C) and 850 hPa wind field (vector, M/s) between 1985–1993 and 1994–2002 (Yang et al. 2012)

6.4.1 Northward Propagation Characteristics of the South China Sea Intra-seasonal Oscillation 6.4.1.1

Northward Transmission of OLR in the South China Sea

The ISO transmitted from the equator to the east mainly affects the southern part of the South China Sea, and has little effect on the northern and southern regions of the South China Sea, while the northward transmission of the Indian Ocean and the westward transmission of the Pacific Ocean have significant impacts on the South China Sea (Wang and Rui 1990). Therefore, the OLR is filtered through the Fourier transform method to obtain the intra-season signal (10–90 days), and the daily data is averaged, and the radial(105°–122.5° E) average can be used to see the OLR season The propagation characteristics of internal oscillations in the north–south direction of the South China Sea (Fig. 6.38). From 2002 to 2011, there was not only a process of northward propagation from the equator, but also a process of southward propagation from mid-high latitudes. The significant northward propagation mainly occurred in summer, and the amplitude was higher than that of the southward propagation process. The northward propagation process had an impact on the South China Sea in summer. The influence of convection and rainfall is much stronger than that of southward transmission. The southward transmission is mainly manifested in the influence of the Asian continental winter high pressure and the difference in heat between the land and the sea in the South China Sea. There are also obvious interannual differences in the strength of ISO in the South China Sea. For example, the northward transmission was not significant in the summer of 2004 and 2006, and the northward transmission was significant in the summer of the rest of the year. However, the northward transmission phenomenon rarely occurred in winter, but the beginning of 2008 was an exception. At the end of 2007 by the beginning of 2008,

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Fig. 6.38 Zonal-time plot after radial (105°–122.5° E) averaging within seasons in the South China Sea during 2002–2011

it was a long-lasting ISO process, which was also the ‘freezing rain’ event in the spring of 2008. The period of northward transmission is 22–26 days on average, the amplitude is generally −40–40 W/m2 , and the average speed is 43.2 km/h.

6.4.1.2

Northward SST Response of OLR in the South China Sea

The intra-seasonal oscillation (ISO) of the atmosphere mainly has two cycles of quasi-two weeks and 30–60 days, which affect the process of air-sea changes in tropical regions. Solar radiation and the latent heat of the ‘Indo-Taiwan Warm Pool’ play an important role in driving the intraseasonal oscillation of SST. The abnormal westerly wind in the warm pool area leads to an increase in evaporation and an increase in latent heat flux. After this process develops for about a week, convection increases, solar radiation decreases, and SST decreases; a decrease in SST will lead to a decrease in evaporation and a decrease in latent heat flux. After that, the convection started to increase again. SST in the South China Sea also responds to the spread of the atmosphere in the north–south direction. SST at the same time uses the same processing method as OLR to study the impact of OLR’s northward propagation process on the South China Sea. SSTA also has the same northward response, with an intensity of 0.6– 0.8 °C. The north pass of this kind of SST depends on the north pass of OLR, so

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in the years when the OLR north pass in the South China Sea is strong, the SST changes relatively increase. Of course, SST in the South China Sea is affected by many factors. In addition to the atmosphere, solar short-wave radiation, internal advection diffusion in the ocean, and other nonlinear heating processes will all cause SST to change, so the SST signal is only the trend consistent with OLR. The lead-lag correlation between SST and OLR shows that the warm anomaly of SST in the low latitudes of the South China Sea leads the strong convection of OLR by 2–3 pentads. When SSTA lags OLR by 2–3 pentads, the amplitude of SSTA turns from positive to negative. This may be the result of the separation between the northward transmission and the eastward transmission of MJO during the season, and it also reflects the response of the local air-sea interaction in the South China Sea to the intraseasonal changes. Before the northward transmission, the vertical structure of the atmosphere in the South China Sea gradually collapsed. Under the influence of the positive anomaly of SST due to the static action of the bottom water vapor and the dry subsidence of the middle layer, the large-scale circulation and local rainfall energy changed and lost balance. When the northward transmission entered the South China Sea Later, the positive anomaly of latent heat is promoted, convection activity is strengthened, evaporation is strengthened, cloud clusters appear, water vapor convergence, which causes the instability of the atmospheric structure, water vapor and latent heat begin to be released, and the occurrence of rainfall will also reduce the ocean surface temperature, completing the South China Sea A cycle of intra-seasonal changes. Therefore, the turbulent flow, heat and water vapor exchange at the air-sea interface are important parameters that characterize the forcing of the underlying surface and the interaction with the upper atmosphere. It can strongly affect the structure of the atmospheric boundary layer and thus the atmospheric circulation. The atmosphere directly affects the circulation structure of the ocean and the temporal and spatial distribution of SST through heat, mass exchange and wind field momentum input.

6.4.1.3

Characteristics of Air-Sea Interaction at Seasonal Scale in the Xisha Sea Area

Xisha is the area where the monsoon erupted earlier in the northern part of the South China Sea. This study uses the long-term meteorological observation data of Xisha from 2008 to 2010 to analyze the multivariate seasonal transition process. Before the establishment of the summer monsoon, the wind direction of Xisha changed greatly, with the northeast wind dominating. In May 2008, the monsoon broke out in the 3rd–4th pentads (that is, the 28th pentad), and the wind direction changed to the southwest monsoon. Two pentads later than the wind angle, it is manifested that the atmospheric circulation this year has more influence on the local air-sea interaction. At the same time, the humidity of the Xisha has been high, and the pressure maintained at about 1004 hPa after the subtropical high eastward, which is higher during the summer. SST and temperature remained stable. The wind speed was 3–5 m/s. There were two monsoon interruptions in July and September. In 2009,

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the summer monsoon onset was relatively late, approximately close to June (32 pentads), and OLR represented the year’s. The monsoon onset is 3 pentads earlier than the wind direction, which shows that the influence of the local air-sea interaction in this year is more obvious. At the beginning of the monsoon onset, the humidity is very high and the convective effect is also strengthened. After July, Convective rainfall was significantly weakened, and the average wind speed was lower than that in 2008. The monsoon interruption occurred twice in July and once in August. The summer monsoon retreated earlier than in 2008; the 2010 summer monsoon Xisha broke out at 5 On the 16th, close to 2008, the OLR and the wind direction represented the monsoon onset time basically the same, indicating that the monsoon onset of this year was basically affected by the overall atmospheric circulation and local air-sea atmosphere, and there was a longer interruption in June., And then the outbreak continued until August, and then it was interrupted again (Fig. 6.39). The onset time of the summer monsoon climate in different regions of the South China Sea is different due to different variable definitions and different data analysis, and the onset of the South China Sea summer monsoon has always been considered to be the result of a multivariate compound mutation, which itself is

Fig. 6.39 Seasonal variation process of several atmospheric variables at Xisha Station from April 2008 to December 2009. a 5-day average wind direction Angle; b 5-day average external longwave radiation, the black line represents the signal line of monsoon outbreak 235 W/m2 ; c Relative humidity of xisha; d atmospheric pressure; e Atmospheric temperature; f Wind vector. The red dots show the onset of the monsoon in each of the two years

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also the response of the South China Sea air-sea interaction to the global environment. The process of change. Regarding the mechanism of the onset of the South China Sea summer monsoon, the seasonal changes from winter to summer and the corresponding seasonal evolution of the tropical large-scale circulation system and thermal conditions determine the overall process of the outbreak, which in turn affects the progress of the monsoon. Under the restriction of the summer monsoon, low-frequency oscillations are phase-locked, leading to the onset of the summer monsoon. During the active monsoon period, the ocean will receive more rainfall from the atmosphere and complete the conversion between convective effective potential energy and kinetic energy; during the monsoon interruption, the northern South China Sea will warm up, with evaporation greater than precipitation, and the ocean will import water vapor into the atmosphere. This water vapor cycle process is a common result of large-scale dynamics and SST driving. The propagation of the 10–20-day mode and the 30–60-day mode in the South China Sea in the meridional and zonal directions have different effects on the establishment and development of the South China Sea monsoon effect. The 10–20-day mode mainly weakened the influence of the subtropical high in the process of propagation to the northwest, while the 30–60day mode formed in the tropical Indian Ocean formed a strong convective center. It is the interaction between the two that weakened the influence of the subtropical high. Cyclone circulation in the South China Sea, and westerly winds enter and occupy the entire South China Sea. There is a certain relationship between the strength of the South China Sea monsoon and the types of summer rain belts in my country. In the years when the summer monsoon is stronger, the Yangtze River Basin-southern Japan has less summer rainfall, and North China has more rainfall (Ding et al. 2002). Zhou and Yu (2005) revealed the relationship between atmospheric water vapor transport and China’s typical abnormal summer precipitation modalities. The first modal summer rain belt along the middle and lower reaches of the Yangtze River Basin, the water vapor comes from the Bay of Bengal and the South China Sea, and the source is Philippine Sea. The second modal summer rain belt along the Huai River Basin, the water vapor comes from the South China Sea, the source is the East China Sea.

6.4.2 Sources of Intra-seasonal Oscillation in the South China Sea Chen and Xie (1988) believe that the establishment and retreat of summer monsoon in Australia, Bay of Bengal and South China Sea are triggered by low-frequency oscillation when the seasonal change conditions are met, that is, it is a process of direct nonlinear interaction between low-frequency wave groups and the seasonal cycle. The South China Sea Monsoon Experiment (SCSMEX) clearly shows that the South

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China Sea summer monsoon is characterized by quasi-two-week and 30–60-day low-frequency oscillation. Chen et al. (1995) studied the onset and life cycle of the South China Sea Summer Monsoon in 1979 from two time scales of 30–60 days and 12–24 days. The results showed that the 30–60-day oscillation played an important role in the formation of monsoon troughs and ridges, while the 12–24 day oscillation played a role in triggering the onset of the summer monsoon. During the summer monsoon, there are two active and interrupted monsoon processes. In these two processes, the relative vorticity of the 30–60-day oscillation was positive when it spread into the South China Sea, the lower atmosphere was converged, the upper atmosphere diverged, and convection strengthened. While in the process of the 10–20-day oscillation spreading from mid-latitude to the South China Sea, the convection activity was promoted for the first time, and the convection was inhibited for the second time (Johnson and Ciesielski 2002). Gao and Zhou (2002) found that the intra-seasonal oscillation of SST during the summer monsoon was zonally distributed and northward transmitted. There is a good correlation between SST and intraseasonal oscillation signals of zonal wind and OLR, which proves that intraseasonal signals of the South China Sea play an important role in air sea interaction. Yuan and Liang (2006) used the rainfall data of Xisha station in the northwest of South China Sea from 1958 to 2000 and the 850 hPa wind field data from 1980 to 2001. It shows that both the rainfall and the wind field had intraseasonal oscillations of 10–20 days and 30– 50 days, but the intensity of the rainfall and 850 hPa wind field was not consistent with the monsoon intensity. Using TRMM data from 1998 to 2007, Wu et al. (2010) found that there were intraseasonal signals during the onset of SCS monsoon. The Intraseasonal Oscillation of the SCS summer monsoon begins in the equatorial region of the Western Pacific, spreads northward to the Philippine Sea, and then spreads westward into the SCS. The air sea interaction mechanism involved in the propagation process mainly includes wind evaporation feedback mechanism and cloud radiation mechanism, which makes the bottom atmosphere unstable and connects the South China Sea with the Philippine Sea. Therefore, the research on the air sea interaction of the South China Sea intraseasonal oscillation mainly focuses on the local air sea interaction of the South China Sea, and does not integrate the source of the South China Sea intraseasonal oscillation. Similarly, Roxy and Tanimoto (2012) mainly studied the air-sea interaction process under the dominant role of signals within 30– 60 days of summer in the South China Sea. There is a significant correlation between SST and precipitation (r = 0.44). The SST warm anomaly in the South China Sea makes the atmospheric convection activities continue to strengthen, and the negative sea level pressure anomaly will result in a northward increase in the seasonal signal, as well as rainfall. In terms of dynamic mechanism, intra-seasonal signals belong to the coupling of planetary-scale circulation and large-scale convection. Therefore, as a marginal sea of the Pacific Ocean, the previous research work mainly focused on the ocean scale intraseasonal oscillation, while the impact on the South China Sea and its own

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role were less studied. It is difficult to understand the role and significance of intraseasonal signals in the South China Sea by using the traditional MJO eight-phase decomposition method. According to the characteristics of quasi-biweekly oscillation and 30–60 day oscillation in the seasonal signals of the South China Sea, the two main signals are separated and the different propagation characteristics of the two signals in the northward transmission are studied respectively. Set phase 0° before entering the South China Sea and phase 360 when leaving the South China Sea. The whole process is a cycle. Clusters of different periods and sources is combined into different northward propagation processes to study its impact on the South China Sea. The ISO standards for the separation of the South China Sea are: ➀ There is a negative OLR anomaly signal northward entering the South China Sea from the Pacific or Indian Ocean northward; ➁ It can affect more than 1/2 of the South China Sea; ➂ The low value area is less than 20 W/m2 . Satisfying the above can be regarded as a northward propagation of Intraseasonal Oscillation in the South China Sea. This new method can not only distinguish the development process of ISO in the South China Sea in time, but also separate the signals from different sources in space. The cluster composition after separation mainly includes: 46 cases of the northward quasi biweekly oscillation are mainly from the Northwest Pacific, while 28 cases of he 30–60 day oscillation are northward, of which 12 cases are from the Northwest Pacific, and the other 16 cases are from the Indian Ocean to the South China Sea. The cluster composition fields of the northward propagation process are as follows: ➀ Fig. 6.40 shows the northward propagation process of the quasi biweekly oscillation, which is divided into three phases of 0°, 120° and 240°. The quasibiweekly oscillation mainly comes from the equator near 150° E, from the northwest of the Philippine Sea to the South China Sea. It enters the South China Sea and affects the South China Sea for 10–15 days. Therefore, it is generally believed that the quasi-biweekly oscillation of the South China Sea mainly occurs during the summer monsoon and modulates the establishment of the monsoon through the weather system. ➁ Fig. 6.41 shows the northward propagation process of the 30– 60 day oscillation, which comes from the Pacific Ocean and is divided into five phases of 0, 72, 144, 216, and 288. This oscillation also comes from the vicinity of 150° E at the equator, from the northwest of the Philippine Sea into the South China Sea, which is mainly affected by the Western Pacific warm pool. The convective anomaly changes greatly. ➂ The 30–60-day oscillation propagates northward from the Indian Ocean, which can be divided into six phases of 0°, 60°, 120°, 180°, 240° and 300°. This oscillation comes from the equator near 60° E and enters the South China Sea from the northeast of the Bay of Bengal. The quasi-biweekly oscillation mainly comes from the Northwest Pacific, while the quas-biweekly oscillation from the Indian Ocean has little effect on the South China Sea. In terms of the influence time, the quasi-biweekly oscillation is the shortest. The 30–60 day oscillation from the Pacific Ocean is shorter than the 30–60 day oscillation from the Indian Ocean. From the perspective of influence intensity, the 30–60 day oscillation from the Indian Ocean is stronger than the 30–60 day oscillation from the Pacific Ocean, and the quasi-biweekly oscillation is the weakest.

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Fig. 6.40 Synthetic (0°, 120°, 240°) OLR phase diagrams of the Pacific quasi-two-week oscillation moving northward into the South China Sea

Similarly, the SST response to the OLR intraseasonal signal in the South China Sea reflects the response of the South China Sea to the northward propagation of Intraseasonal signals. According to the lead-lag relationship between SST and OLR, not only one-cycle SST response process in the South China Sea is calculated, but also the composite results of two phases of lead and lag OLR are calculated. For the quasi-biweekly oscillation from the Pacific Ocean, the South China Sea SST two phases ahead is in a warm anomaly, and the sea temperature rises by about 0.2 °C. The warm core is mainly located on the east side of Xisha in the northern part of the South China Sea. As the warm signal disappears northward, the cold anomaly starts to spread northwest from the Pacific equatorial 150° E region, and finally forms a Southwest-northeast cold belt. Different from the quasi-biweekly oscillation, the SST of the 30–60-day oscillation from the Pacific Ocean increases by 0.05 °C in the leading phase. However, with the obvious strengthening of cold anomaly in the two lagging phases, not only the degree increases, but also the range expands correspondingly. the SST of the 30–60-day oscillation from the Indian Ocean is similar to the 30–60-day oscillation from the Pacific Ocean.

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Fig. 6.41 OLR phase diagrams of the 30–60 day Pacific oscillation moving northward into the South China Sea (0°, 72°, 144°, 216°, 288°)

6.4.3 The Basic Characteristics of ISO Affecting the South China Sea The 30–60-day intra-seasonal oscillations from the Indian Ocean, which affects the South China Sea, mainly occurs in the equatorial region. From the perspective of synthetic field, in the process of signal propagation to the northeast in the season, due to the blocking of Indochina Peninsula, the local water vapor and heat supply is insufficient before reaching the South China Sea. So that the northward propagation process of the Indian Ocean will have sea-air interaction characteristics different from that of the Pacific Ocean. Using OAFLUX data, this study selects two examples, from 14 June to 13 July 2007 and 26 August to 30 September 2008, to study the process of the 30–60-day intra-seasonal oscillation of the Indian Ocean affecting the South China Sea locally.

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It can be seen from Fig. 6.42 that the eastward ISO is divided into two branches, the centers are in the South China Sea and the middle of the East Indian Ocean. Firstly, on June 24, 2007, the latent heat flux of the East Indian Ocean and the water vapor flux in the atmosphere increased, and the wind direction was basically westerly, the latent heat and water vapor reached the maximum on June 26. The strengthening of the southerly wind affected the further development of the atmosphere. The local air-sea interaction in the Indian Ocean promoted the increase of convection. At this time, the ISO was divided into two branches. The first signal to enter the South China Sea began on June 26. The increase of latent heat flux and the increase of water vapor flux in the atmosphere caused the local atmospheric oscillation to develop and become active. From June 29 to 30, the latent heat and water vapor reached the maximum and the zonal wind changed from westerly to easterly. During this process, the northward OLR in the South China Sea also had a process of strengthening and weakening, that is, the convection began to increase on June 24, the OLR decreased by 15 W/m2 on June 30 and increased on July 4. Figure 6.43 shows the changes of latent heat flux and water vapor flux in the Indian Ocean and South China Sea caused by ISO from August 26 to September 30, 2008. It can also be clearly seen that the signal is divided into two branches under the blocking effect of Indo-china Peninsula. The difference between these two cases is that the first case has the most significant impact on the South China Sea branch, while the other case mainly stays in the Bay of Bengal and has a weaker impact on the South China Sea. The northward propagation of the Indian Ocean in 30–60 days has interannual characteristics. The statistical results show that there were more occurrences in 2003 and 2008, 3 and 4 times respectively, while there were fewer occurrences in 2002, 2004 and 2009–2011, none in 2002 and 2011, and only once in the other 3 years. The

Fig. 6.42 Variation distribution of latent heat flux (shadow, W/m2 ), water vapor flux (contour line) and wind field (arrow, m/s) from June 14 to July 13, 2007

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Fig. 6.43 Variation distribution of latent heat flux (shadow, W/m2 ), water vapor flux (contour line) and wind field (arrow, m/s) from August 26 to September 30, 2008

main reason may be that the northward propagation into the South China Sea is weak, and more of it stays in the Indian Ocean to develop locally and die. The frequency of northward propagation is closely related to the origin of the Indian Ocean and the internal SST in the South China Sea. In this study, the correlation analysis between the annual frequency of northward propagation of Intraseasonal signal in the South China Sea and the Indian Ocean (0–10° N, 60°–70° E) SST and the Central South China Sea (10°–20° N, 110°–120° E) SST was conducted. The fitting coefficients were 1.69 and −1.65, respectively. It can be seen that the cold anomaly in the South China Sea and the warm anomaly in the Indian Ocean increased the frequency of northward propagation of the Indian Ocean.

6.5 Summary and Outlook This chapter reviews the thermal dynamics of the upper mixing layer, flux exchange at the air-sea interface, atmospheric boundary layer structure, tropical cyclone activity and sources of intra-seasonal oscillation in the South China Sea. The thermodynamics of the upper mixed layer in the South China Sea has obvious marginal sea characteristics, and the temperature changes of the surface and upper mixed layer almost have all the time scale characteristics of tropical ocean, such as diurnal, intra-seasonal, inter-annual and inter-decadal variations. The fixed-point

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buoys in the South China Sea summer monsoon experiment provide high time resolution SST data for the study of the diurnal SST variation, which makes it possible to study the diurnal SST variation. The basic characteristics of intra-seasonal SST variation and the physical process of its formation in the South China Sea have significant monsoon characteristics. ENSO signals affect the bridge through atmospheric and ocean circulation, and to a great extent affect the inter-annual SST variation in the South China Sea. Corals in the South China Sea are natural climate recorders, showing a significant rise in sea surface temperatures since 1880. Air-sea flux exchange is the key link of air-sea interaction. The observation of air-sea heat flux in the South China Sea began in the late 1970s. The shipborne flux observations, fixed-point buoy observations and flux observation tower data accumulated in recent years provide key observational evidence for analyzing the characteristics and changes of air-sea flux, verifying the accuracy of remote sensing heat flux data inversion, and parameterizing the model flux in the South China Sea. Over the ocean, the temporal and spatial variation of the structure of the oceanic atmospheric boundary layer (the offshore gas layer about 1000 m above the sea level) is relatively slow, but the diurnal variation of the atmospheric boundary layer over the South China Sea still exists. The horizontal gradient structure of surface SST caused by the front and mesoscale vortex in the South China Sea has an important influence on the dynamic structure of the oceanic and atmospheric boundary layer. The radiosonde observation data provide valuable observation data for analyzing the microstructure changes of the oceanic atmospheric boundary layer under different oceanic phenomena in the South China Sea, and also provide key observation support for analyzing the occurrence probability and distribution characteristics of the height, strength and thickness of various atmospheric duct in the South China Sea. The activity of tropical cyclones in the South China Sea includes those generated locally over the South China Sea and those generated over the western Pacific and moving westwards into the South China Sea. The intensity, frequency and track variations of locally generated tropical cyclones in the South China Sea are different from those in the western Pacific, and the track differences are closely related to the anomalies of large-scale wind field caused by different ENSO phases. For the tropical cyclones in the South China Sea in summer and autumn, the interannual variation of tropical cyclones in autumn was significant, and the tropical cyclones in autumn were significantly stronger than those in 1965–1977 after 1978. On the interdecadal scale, there is a significant 10-year cycle for tropical cyclone generation in summer, but not in autumn. The seasonal signals in the anomalous signals of the upper ocean and atmosphere in the South China Sea have a significant influence on the climate of China. The sources of the intra-seasonal oscillation in the South China Sea mainly include the east oscillation signal from the equator, the north oscillation signal from the Indian Ocean and the west oscillation signal from the Pacific Ocean. There are obvious inter-annual differences in the intensity of intra-seasonal oscillation over the South China Sea, and the phenomenon of northward oscillation rarely occurs in winter, but the early 2008 was an exception, a long period of intra-seasonal oscillation process, which caused the ‘freezing rain’ event in the spring of 2008.

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At present, there is a lack of systematic research on the process and mechanism of air–sea coupling between ocean and atmosphere in the South China Sea. Although existing studies have explored the thermodynamic processes of the South China Sea, they have not yet explained how the South China Sea plays an active role in local air-sea interaction and climate change. Future studies should focus more on how the South China Sea plays a role in the climate system.

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Wang B, Rui H (1990) Synoptic climatology of transient tropical intraseasonal convection anomalies: 1975–1985. Meteorol Atmos Phys 44(1–4):43–61 Wang DX, Xie Q, Zhou FX (2001) Preliminary experiments for regional atmospheric circulation’s response to sst anomalies in South China Sea and its adjacent areas. J Trop Oceanogr 20(1):82–90 (in Chinese) Wang C, Wang W, Wang D et al (2006) Interannual variability of the South China Sea associated with El Niño. J Geophys Res Oceans 111(C3):C03023 Wang C, Wang X (2013) Classifying El Niño Modoki I and II by different impacts on rainfall in Southern China and Typhoon Tracks. J Clim 26(4):1322–1338 Wang D, Zeng L, Li X et al (2013) Validation of satellite-derived daily latent heat flux over the South China Sea, compared with observations and five products. J Atmos Oceanic Tech 30(8):1820– 1832 Wang G, Li J, Wang C et al (2012) Interactions among the winter monsoon, ocean eddy and ocean thermal front in the South China Sea. J Geophys Res Oceans 117(C8):C08002 Wang L, Lau KH, Fung CH et al (2010a) The relative vorticity of ocean surface winds from the QuikSCAT satellite and its effects on the geneses of tropical cyclones in the South China Sea. Tellus Dyn Meteorol Oceanogr 59(4):562–569 Wang X, Wang DX, Gao RZ et al (2010b) Anthropogenic climate change revealed by coral gray values in the South China Sea. Chin Sci Bull 55(13):1304–1310 Wheeler MC, Hendon HH (2004) An all-season real-time multivariate MJO index: development of an index for monitoring and prediction. Mon Weather Rev 132(8):1917–1932 Wu DS, Xu JP, Wang YL et al (2005) Variation characteristics of air-sea heat flux at Ocean observation stations in South China Sea. J Trop Meteorol 21(5):517–524 (in Chinese) Wu RG, Wen ZP, Yang S et al (2010) An interdecadal change in Southern China summer rainfall around 1992/93. J Clim 23(9):2389–2403 Xie SP, Hu K, Hafner J et al (2009) Indian Ocean capacitor effect on Indo–western Pacific climate during the summer following El Niño. J Clim 22(3):730–747 Xie SP, Xie Q, Wang D et al (2003) Summer upwelling in the South China Sea and its role in regional climate variations. J Geophys Res 108(C8):3261 Yan JY (1997) Climatological characteristics on the onset of the South China Sea southwest monsoon. Acta Meteor Sin 55(2):174–186 (in Chinese) Yan JY (1999) Estimation and analysis for air-sea fluxes of heat and moisture over the neighbouring Seas of China. Q J Appl Meteorol 10(1):9–19 (in Chinese) Yan J Y , Liu J M , Jiang G R , et al (2007) Advances in the Study of Air-Sea Flux Exchange over the South China Sea. Advances in Earth Science 22(7) (in Chinese) Yanagi T, Koike T (1987) Seasonal variation in thermohaline and tidal fronts, Seto Inland Sea. Japan Cont Shelf Res 7(2):149–160 Yang KD, Ma YL, Shi Y (2009) Spatio-temporal distributions of evaporation duct for the West Pacific Ocean. Acta Physica Sin 58(10):7339–7350 (in Chinese) Yang L, Du Y, Wang D et al (2015) Impact of intraseasonal oscillation on the tropical cyclone track in the South China Sea. Clim Dyn 44(5–6):1505–1519 Yang L, Du Y, Xie SP et al (2012) An interdecadal change of tropical cyclone activity in the South China Sea in the early 1990s. Chin J Oceanol Limnol 30(6):953–959 Yim SY, Jhun JG, Yeh SW (2008) Decadal change in the relationship between east Asian-western North Pacific summer monsoon and ENSO in the mid-1990s. Geophys Res Lett 35(20):229–237 Yuan JN, Liang JY (2006) A diagnostic study of monsoon intraseasonal oscillation by using observational data of Xisha station in the South China Sea. Acta Oceanol Sin 28(1):18–25 (in Chinese) Yuan J, Wang D (2014) Potential vorticity diagnosis of tropical cyclone Usagi (2001) genesis induced by a mid-level vortex over the South China Sea. Meteorol Atmos Phys 125(1–2):75–87 Zang N (2005) Diurnal cycle of SST in South China Sea and the effect of summer monsoon onset. Master thesis of Ocean University of China. (in Chinese)

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Zeng L, Li X, Du Y et al (2012) Synoptic-scale disturbances over the northern South China Sea and their responses to El Niño. Acta Oceanol Sin 31(5):69–78 Zeng L, Ping S, Liu et al (2009) Evaluation of a satellite-derived latent heat flux product in the South China Sea: a comparison with moored buoy data and various products. Atmos Res 94(1):91–105 Zeng L, Wang D (2009) Intraseasonal variability of latent-heat flux in the South China Sea. Theoret Appl Climatol 97(1–2):53–64 Zeng L, Wang D, Chen J et al (2016) SCSPOD14, a South China Sea physical oceanographic dataset derived from in situ measurements during 1919–2014. Sci Data 3:160029 Zhang QR (1998) The studies on the interaction of the Air-sea in Nansha Islands Waters. National Conference on Atmospheric Environment. (in Chinese), Beijing Zhang QR, Cai QB, Lin XG (1986) Preliminary analysis of near-surface atmospheric gradient observation experiment over the Northern South China Sea. J Trop Oceanogr 5(2):75–81 (in Chinese) Zhan R, Wang Y, Lei X (2011) Contributions of ENSO and East Indian Ocean SSTA to the interannual variability of Northwest Pacific tropical cyclone frequency. J Clim 24(2):509–521 Zhang Y, Wang D, Xia H et al (2012) The seasonal variability of an air-sea heat flux in the northern South China Sea. Acta Oceanol Sin 31(5):79–86 Zhao X, Wang D, Huang S et al (2013) Statistical estimations of atmospheric duct over the South China Sea and the Tropical Eastern Indian Ocean. Chin Sci Bull 58(23):2794–2797 Zhou F, Ding JY (1995) The intraseasonal oscillation of sea surface temperature in the South China Sea. J Ocean Univ Qingdao 25(1):1–6 Zhou F, Zhang Y, Huang F et al (1999) Spatial pattern of the air-sea interaction near the South China Sea during winter. Chin J Oceanol Limnol 17(2):132–141 Zhou TJ, Yu RC (2005) Atmospheric water vapor transport associated with typical anomalous summer rainfall patterns in China. J Geophys Res Atmos 110(D8):D08104 Zhu LS, Qiu Z (2002) Seasonal distribution and variation of barrier layer and its influence upon the vertical heat diffusion in the southern South China Sea. Acta Oceanol Sin (s1):171–178. (in Chinese)

Chapter 7

South China Sea Observation and Data Assimilation

7.1 Ocean Observation in the South China Sea Before the 1980s, oceanic observation data in the SCS were very scarce and mostly concentrated in the continental shelf area. When Xu et al. (1982) studied the upper and middle circulation of the SCS, they only obtained temperature and salinity data at more than 6000 stations from the Japan Oceanographic Data Center (as of 1970, SCS data from the Cooperatice Study of the Kuroshio and Adjacent current (CSK), which include Taiwan and Hong Kong to attend), and the distribution is very uneven. For example, the data in the deep water area of the central SCS and the waters of the Nansha Islands are very few. During the first national ocean census of China in the 1960s, the stations were all located on the continental shelf due to limited conditions. After its establishment in 1959, the South China Sea Institute of Oceanology (SCSIO), Chinese Academy of Sciences (CAS), has conducted many surveys in the northern shelf area of the SCS, the Qiongzhou Strait, and the Beibu Gulf. Among them, the Beibu Gulf background survey in 1964 and the continuous observations of the fixed-point diural-day currents in the Beibu Gulf from April to July 1969 and large-area hydrological observations in the northern shelf area of the SCS in 1971 for half a year (the latter two surveys both put anchored buoy stations for multi-day flow measurement) are the most distinctive. Since 1973, China has conducted several comprehensive surveys on Xisha Islands and Zhongsha Islands in the SCS and adjacent waters, which has opened the prelude to deep-sea observation, among which the diural-day tidal level survey on Huangyan Island has filled the gap in China’s. On this basis, the central area of the SCS (12°00, –19°00, N, 109°30, –118°00, E) was surveyed from 1977 to 1978, and the northeastern area of the SCS (17°00, –23°00, N, 112°30, –120°00, E) was surveyed from 1979 to 1982. The results of the survey were compiled into “The Comprehensive Investigation and Research Report of the South China Sea (1)” and “The Comprehensive Investigation and Research Report of the South China Sea (2)”, which were published in 1982 and 1985 respectively. Beginning in 1984, it carried out an organized survey with the Institute of Oceanography at National Taiwan University in the northeastern SCS. From August to September © Science Press and Springer Nature Singapore Pte Ltd. 2022 D. Wang, Ocean Circulation and Air-Sea Interaction in the South China Sea, Springer Oceanography, https://doi.org/10.1007/978-981-19-6262-2_7

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1994, it participated in the second, broader survey extended to the northeastern of the Luzon Strait. Relevant research results have been published in the “Chinese Oceanography Collection 6” in 1996 and on the “Tropical Ocean 16 (2)” in 1997. In addition to the large-scale comprehensive surveys mentioned above, the SCSIO, CAS conducted several physical oceanographic surveys in the northern SCS in accordance with the mission requirements at that time. For example, in the “SCS Warm Current Dynamics Experiment” from February to March 1982, the deep-water buoy station located off Shantou successfully obtained the ocean current observation data for seven consecutive days under the wind force of 7–8, which provided valuable current measurement evidence for the SCS Warm Current moving against the wind in winter. In the summer of 1983, the current measurement data of Buoy Station under the first tropical storm in China were obtained at the northern edge of the continental shelf of the SCS. The cross-sectional survey conducted by the SCS Bureau of the Ministry of Natural Resources in the northern continental shelf area of the SCS is still going on, and the observation cross-sections have been adjusted several times. The results of the previous survey have been compiled into the “Report of the Ten Year Hydrological Sectional Survey of the Northern Shelf Adjacent Waters of the SCS”, which was published in 1990. From April 1983 to January 1985, the State Oceanic Administration also organized a comprehensive survey of the central area of the SCS (12°00, – 20°00, N, 111°00, –118°00, E), and published the “Comprehensive Survey Report on Environmental Resources in the Central SCS” and the corresponding atlas in 1988. During the South China Sea Monsoon Experiment (SCSMEX) in 1998, the State Oceanic Administration organized two large-scale surveys covering almost the entire SCS. During this period, Taiwan Province also conducted surveys in the SCS and launched three deep-water buoy stations. SCS Fisheries Research Institute of the Chinese Academy of Fishery Sciences had conducted two large-scale fishery surveys (including hydrometeorology) in the central and northern SCS before the 1980s. The first was in the early 1960s, and the second was in the late 1970s. Both surveys had reports on physical oceanography. They also included many small-scale fishery surveys, temperature and salinity observations during the fishing season. As for the shallow coastal waters, coastal surveys were conducted from the late 1970s to the early 1980s and island surveys were conducted in the 1990s, and corresponding survey reports were published. In terms of the Gulf, the Daya Bay background survey conducted by the SCSIO, CAS from 1984 to 1986 was the most comprehensive (temperature and salinity surveys were conducted from 1982 to 1983), and the monograph “Environment and Resources of Daya Bay” was published. Due to the construction of the Daya Bay Nuclear Power Plant, Sun Yat-sen University has also conducted hydrometeorological surveys in Daya Bay. The above is only a brief introduction to the influential oceanographic surveys in the three major oceanographic research institutes in the SCS before the 1980s. Despite the harsh conditions, oceanographic workers (including those in the petrochemical and mineral resources sectors) overcame the difficulties with high spirits and did as much work as possible, leaving valuable first-hand observations for future

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generations. The survey data before the 1980s have been compiled and published by the National Marine Data Information Center. Major voyages to the SCS since the 1980s are described below. In the mid-1980s, the state launched a special survey mission for Nansha. The survey mission was organized and implemented by the SCSIO, CAS. The participating units covered dozens of research and business institutions from various departments in China. The core of the survey was on islands and reefs and their surrounding waters. In a multi-disciplinary comprehensive survey, the survey area is relatively limited, in terms of hydrodynamic environment, the main focus is on the hydrodynamic characteristics of a small area around islands and reefs, and there is a lack of repeated sampling and observation of key sections. The SCSMEX in the late 1990s was the first international joint observation project over the entire SCS basin, involving domestic participants from various Marine and meteorological research institutions. The SCSMEX mainly solves the changes in the upper ocean dynamics and thermal environment, the characteristics of the sea-air interface exchange, and the changes in the lower atmosphere, etc., before and after the onset of the SCS monsoon; Before and after the 1998 summer monsoon onset, using multi-ship simultaneous observations, mainly based on fixed-point time series observations, implemented the two voyages of large-scale observation missions, it’s time coincides within the La Niña event in 1998. Subsequently, under the support of ‘Project 973’ of the SCS Circulation, two largescale surveys covering the whole SCS were designed and executed in the summer of 2000 and the winter of early 2001, aiming at the basic dynamic characteristics of the SCS Circulation; And obtained the time series observation results of the SCS branch of the Kuroshio Current in the northeast SCS and the central and western boundary current. After entering 2000, in addition to the traditional reef-landing operations, the Comprehensive Scientific Exploration Program of Nansha Islands in the southern SCS has gradually attached importance to repeated observations of key sections in key sea areas, especially its follow-up observation and research plan—Nansha Basic Sectional Survey Program. Seasonal and interannual variations of the hydrodynamic environment in the central and southern SCS are described through repeated observations of a series of key sections. As China’s second national marine basic information survey project, the China Offshore Oceanographic Survey Program has completed the collection of highdensity typical seasonal basic marine environmental information covering the coastal areas of the country. For the first time the unified standard and technology system background, the comprehensive scientific survey data of oceanography in typical seasons in the coastal waters of China have been compiled, and supplementary encrypted surveys have been carried out for some controversial oceanographic phenomena. Since 2004, the SCSIO, CAS has organized an annual open voyage to the northern SCS. The station of the voyage was designed based on the study of the dynamic characteristics of the SCS circulation and air-sea interaction. The implementation of

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open voyages in the northern SCS has provided a very critical basic support platform for many ocean-related research institutions and teams, attracted more research teams to devote themselves to oceanographic research, and gained a deeper understanding of the Marine dynamic process, biological resource pattern and formation mechanism, as well as Marine geological structure in the northern SCS. Since 2010, the National Natural Science Foundation of China (NSFC) has launched the NSFC Sharing Voyages Program under the guidance and promotion of open voyages in the northern SCS. Through the implementation of the sharing voyage plan, the NSFC has accumulated a large number of first-hand survey data, which has effectively promoted the outcomes of the participating projects. At the same time, to meet the national strategic needs and improve the independent innovation capabilities of the Chinese Academy of Sciences in marine scientific research. The SCSIO, CAS using the upper ocean and large underwater floating bodies as observation platforms established a comprehensive ocean observation and research station focusing on the physical ocean, on the representative sea areas of the northwest SCS—The yongxing island of the xisha islands. Comprehensive deployment of an all-weather, long-term continuous monitoring system integrating the atmosphere, upper ocean, water body, and deep-sea processes. According to the observation requirements of different elements and the timeliness of data requirements, four major categories of observation and application platforms have been built: for sea surface elements Established a hydrometeorological observation network in the northern SCS; mainly built a submarine target observation array system for water body elements; designed a voyage large-scale observation system for water body-water surface-lower atmosphere elements; Based on data output requirements, a platform for numerical prediction and reanalysis of the marine environment of the SCS has been established. With voyage survey as the framework and stations as the fulcrum, a regional oceanic observation and research network with both comprehensive observation and special investigation functions has been formed.

7.1.1 Large-Scale Observation of Voyage 7.1.1.1

Voyage Observation in the Southern SCS

The southern SCS voyage observation was first initiated by the Nansha Special Program of the National during the “8th Five-Year Plan”. Since 1984, it has been organized and implemented by the SCSIO, CAS. Its main observation targets focus on the conventional projects of the hydrological environment, biological resources of islands, and reefs and their adjacent waters. From 1985 to around 2005, a total of 24 voyages were carried out in the past 20 years, and more than 3,300 stations of CTD profile data and conventional sea surface meteorological observation records were obtained, which covered the main islands and reefs and open sea areas of the Nansha Islands. The relevant survey data fills the blind spot of international observation data in this sea area, which has important scientific significance.

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In the late 1990s, in addition to routine reef boarding survey operations, it gradually increased that the proportion of conventional hydrometeorological surveys on the dynamic characteristics of the basin-scale circulation in the southern SCS voyages. The survey area is no longer concentrated around the islands and reefs, while covering the deep-water basin. Restricted by the need for good sea conditions for reef landing operations, the relevant surveys are carried out from April to May each year, mainly to obtain the dynamic and thermal characteristics of the southern SCS during the transition period of the spring monsoon. The comprehensive analysis of the observation data of the Nansha Comprehensive Scientific Survey for more than 20 years shows that on the multi-year average seasonal cycle scale, there has warm eddies moving westward in the middle of the ocean basin from February to April, which will eventually lead to the transition from the winter current field to the summer current field; during the summer monsoon, the Vietnam Coast Current began to form in July, reached its peak in August and died out in October, and there was obvious cyclone eddy activity (Wanan eddy) in the northeast of Natuna Island. From September to October, there were cold eddies traveling from the waters south of the Xisha to the south of the SCS, and eventually causes the summer flow field to change to the winter flow field. During the winter monsoon, there are strong cyclonic cold eddies in the waters northeast of Natuna Island and southeastern Vietnam. Observations have found that the change of water mass properties of middle and deep water in the SCS is not a monotonous and linear process, but a “leaping” change occurs in some periods. In some periods, the change is not very significant, and the evolution of water mass properties is relatively slow. The temperature near the core depth of the mid-level water in the South China Sea has shown an upward trend in the past 20 years, but the lower mid-level water of below 700 m and the upper the deep water, the temperature of the water body shows a downward trend, with a range of 0.0035–0.007 °C/a, and the fastest change is near 1100 m. The changing trend of salinity in each layer below 300 m is basically the same. They all experienced a process of increasing to decreasing in the middle and late 1980s. In general, the increased range of salinity is 0.006–0.007 psu /a (Fig. 7.1). After 2009, in order to connect with the 18°N cross-sectional observations of the Climate and Ocean Variability, Predictability and Change (CLIVAR), to meet the needs for cross-sectional data analysis of seasonal and inter-annual variability of the SCS circulation, and to use corals to reconstruct the past interannual and interdecadal climate sequence in the low-latitude sea area of the SCS, the Ministry of Science and Technology has set up a basic scientific survey plan of the SCS ocean section. The plan was implemented four times in total, and its fixed cross-sections were in a ‘three horizontal and one longitudinal’ layout (Fig. 7.2): 75 stations were laid out at 18° N, 10° N, 6° N and 113° E meridian cross-sections. There are 20 stations on the 18° N section, 20 stations on the 10° N section, 13 stations on the 6°N section, and 25 stations on the meridian Section 113° E (including 3 repeating stations). In the spring of 2009, the fall of 2010, the winter of 2011 and the summer of 2012, the survey tasks for the full seasonal coverage of the relevant sections were completed.

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Fig. 7.1 The T–S diagram of the middle and lower waters during the Nansha voyage from 1985 to 1999

Fig. 7.2 Distribution map of voyage stations of basic cross-sectional survey in the SCS

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In the actual implementation process, the 2009 voyage combined with the needs of the Nansha comprehensive survey mission, conducted 102 stations of CTD observations in the SCS; the CTD of MVP towed was deployed 3 times and 120n mile was observed; 3 sets of observational mooring were recovered and deployed, which has obtained ocean current observation data for two consecutive years in the Nansha sea area; 40 observation stations of TurboMap ocean turbulence microstructure; full navigation ADCP ocean current observation; full navigation surface sea temperature and salt observation; full navigation automatic weather station observation. The observation results (Fig. 7.3) show that the water properties of the SCS are relatively stable in different seasons, especially the water properties of the middle and lower layers are relatively single. During the observation period, no water mass distribution with the characteristics of Northwest Pacific water was found. During the investigation of the spring voyage, there were obvious hightemperature areas above 200 m west of the 6° N section with warm water activity. Near 113° E, there was a low-salt core at 40–80 m, which was also found during the comprehensive survey of Nansha in June 2007. Cyclone cold eddy activity occurred above 200 m west of the 10°N section, and thermocline ventilation occurred. The depth of the mixed layer at the 18° N section is relatively shallow, and the isotherm

Fig. 7.3 Temperature-Salinity diagram of basic section survey in the SCS. Red. Spring 2009; purple. Fall 2010; green. Winter 2011; yellow. Summer 2012

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tends to be higher in the west and lower in the east. The isothermal line of the 113° E section rises from south to north; local warm water is generated at 8°–10° N and 16°–18° N. During the summer voyage survey, there was a high-temperature water tongue on the surface of the east side of the 6° N section, and the thermocline appeared at 60–90 m. The 10° N section presents a relatively high-temperature zone around 113° E with a depth of 60 m, and a high-temperature zone also exists on the west side of the section with a depth of 50 m, and the thermocline appears at 70–110 m; the mixed layer is thinner and a relatively low salt zone appears in the water depth of 110–180 m on the west side of the section (110°–112.5° E). The surface temperature of the 18° N section is low in the east and high in the west, and the thickness of the high-temperature water layer in the west is relatively shallow. There is high salt water at 130–150 m on the east side, with the highest salinity of 34.78 psu. The surface temperature of section 113° E is low in the south and high in the north. The thermocline in the south is 70–140 m, and the thermocline in the north is 30–80 m. There are strong temperature and salinity gradients at 11° N. During the autumn voyage survey period, the weather was relatively bad, and offshore operations were greatly affected by the weather. According to the actual situation, the stations located outside the nine-dash line were forced to give up. Of the 20 stations on the 18° N cross-section, only 11 stations have been observed due to poor sea conditions. The water at the 18° N, 10° N, and 6° N sections all show that the temperature is high in the east and low in the west, and the salinity is low in the east and high in the west. The temperature in the southern 113° E section is about 1.5 °C higher than that in the northern, and the salinity is about 1 psu higher. This is mainly due to the northeast monsoon invading the SCS earlier than usual in 2010. From the end of October to the beginning of November, the northern of the SCS is full of windy areas. The thermocline is distributed below 60 m and the thickness is about 40 m. During the 46-day survey period, the survey operation time was only 13 days, and only 43% of the serial stations were completed in the entire voyage. The depth of the mixed layer at the 6° N section is deep in the east and shallow in the west, reaching 60 m in the east and only 20 m in the west. At 110°–111° E, there is seawater with a lower temperature than the surrounding temperature at a water depth of 50–60 m; the surface low-salinity area appears on the west side of the section, and the thickness of the low-salinity water is deeper on the east side than the west side; the halocline is at 30–50 m. The temperature above 200 m at 113° E cross-section was higher in the south and lower in the north, and the maximum difference was 2.0 °C. The intrusion depth of surface high-temperature water is more than 60 m at the south end and more than 30 m at the north end. The temperature of the water near 10° N is relatively low, indicating that there may be cold eddy activity in this area. The surface low-salinity center appears at the southern end of the section. In the section, the distribution depth of the halocline is 30–50 m, the high-salinity depth is below 80 m, and the salinity tends to be stable below 180 m.

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7.1.1.2

403

Open Voyage Observation in the Northern South China Sea

In order to play to the comprehensive advantages of multiple scientific research forces, strengthen the long-term accumulation of marine field data, promote longterm observational research on the dynamic change process of the marine environment and its ecological effects in the northern SCS and the output of major achievements, promote marine science research of multidisciplinary cross and integration, and with the exchange and cooperation of scientists inside and outside the institute, the SCSIO, CAS has taken the lead in implementing the voyage plan for the northern SCS since 2004. The plan takes the ocean multi-scale marine dynamics and environmental processes as observation objects of the Pearl River Estuary and the northern SCS, and aims to improve the cognition and predict the impact of natural and human activities on the offshore ecosystem of the SCS. During the summer and autumn seasons, the 8 repeated observation sections of the northern SCS as the skeleton, the continuous multidisciplinary comprehensive observations are carried out to provide a scientific basis for the sustainable development and decision-making of marine management in the SCS. The SCSIO, CAS provides the plan with about 30 days of marine operations each year. All domestic research teams with marine survey operations requirements are welcome to participate in the voyage survey for free of charge, and relevant basic survey data will also be shared with the research teams participating in the voyage for free in real-time. This pioneering open and shared marine survey platform has attracted many teams who are interested in investing in ocean research but lacking relevant resources to enter the field of ocean research and promote the development of related disciplines. The Northern South China Sea Open Voyage Program designed eight sections for important scientific objects such as Pearl River flushing freshwater, nearshore upwelling, Taiwan shallows, circulation around Hainan Island, and Luzon Strait transport (Fig. 7.4). The 18 °N section is the boundary between the tropics and the subtropics and is set as a regular section of CLIVAR to study oceanic meridional transport, atmospheric meridional circulation and monsoon activity. The contents of the survey include oceanic hydrological observation, oceanic current and meteorological observation, optical parameter measurement of the upper ocean, Marine biological, ecological and chemical data observation, aerosol measurement, Marine sediment sampling, etc. Its core investigation and research area are located in the northern SCS and its adjacent areas within the traditional borders of China. In terms of marine hydrology, the main instruments onboard include the conductivity temperature depth (CTD), the underway-CT, the moving vessel profiler (MVP), and the acoustical Doppler current profiler (ADCP), the lowered acoustical Doppler current profiler (LADCP), the turbulence ocean micro-structure acquisition profiler (TurboMAP), the mooring, the automated flowing pCO2 measuring system, the global positioning system sounding, the automatic weather station (AWS), the air-sea flux observation system, etc. Since 2006, radiometers and sounding observations have been loaded on open voyages, opening a new era of marine meteorological observation in the SCS. Sounding balloon observation is an effective method to obtain the vertical structure of atmospheric temperature and humidity over the ocean. The

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Fig. 7.4 The Distribution of CTD stations during the open voyage in the northern SCS from 2004 to 2013 (Zeng et al., 2009)

SCSIO open voyage releases the sounding balloons on time during the voyage to obtain vertical profiles of wind, temperature, humidity and pressure. In our observation network, we mainly choose the GPS-TK soundings developed by the key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric Physics, Chinese Academy of Sciences, and the CF-06A sounding balloon developed by Beijing Changfeng Microelectronics Co., Ltd in China. The comparative test results with Vaisala sounding balloon in tropical sea area show that the CF-06-A sounding also has very good results (Xie et al. 2014). The AWS is equipped with complete meteorological observation instruments, including net radiation meters, atmospheric temperature and pressure sensors, wind speed and direction observation equipment, and humidity observation instruments. By 2013, the open voyages have accumulated a large number of basic observation data for comprehensive research on the northern SCS, with a view to forming a high-quality grid multidisciplinary and multi-element observation data set for the northern SCS in the future. At present, a series of research achievements have been made in the fields of oceanography and meteorology: (1) the characteristics and changes of ocean water masses have been revealed, including the characteristics of upper ocean temperature, salinity and stratification, water mass intrusion and water exchange of strait, and interannual changes of water masses in the mid-deep layers; (2) It reveals the evolution characteristics of circulation and eddy structure, provides the observational facts of the SCS Warm Current, discovers the Dongsha bifurcating current, and explains its dynamic mechanism and the three-dimensional structure of mesoscale eddies. (3) Research on air-sea flux and atmospheric boundary layer, including the high-frequency variation of air-sea interface parameters, the evaluation and verification of heat flux parameterization, the structure of the atmospheric boundary layer and the feedback to the ocean, etc.

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Inspired by the open voyage plan for the northern SCS, SCSIO, CAS launched a similar open voyage plan in the Yellow and East China Seas in 2006. In 2010, the National Natural Science Foundation of China (NSFC) launched the larger and sustainable foundation shared voyage plan, which covers Chinese waters and extends to the western Pacific and the eastern Indian Ocean.

7.1.1.3

The NSFC Shares Voyage Observation

Under the guidance and drive of the open voyage of SCSIO, CAS, the NSFC launched the “NSFC Comprehensive Oceanography Voyage of SCS” in 2010. This plan is a shared voyage plan established by the NSFC to implement the strategic deployment of the “11th Five-Year Development Plan” of the NSFC. It aims to provide ship operation time for the NSFC projects that must conduct sea investigations, to ensure the implementation of the sea mission of the NSFC projects. According to the regulation of “ Pilot Implementation Measures of Ocean Survey Ship Hourly Expenses of the NSFC”, the NSFC adopts a financial subsidy method to provide the necessary basic funding guarantees for each shared voyage, and provide stable and reliable Sailing-time guarantee for fund-funded projects. And we will use this as an opportunity to explore the sharing mechanism of marine observation platforms, strengthen the long-term accumulation of marine field data, promote the interdisciplinary and integration of marine scientific research, and the exchange and cooperation between scientists, and promote the output of major achievements. Provide on-site testing and observation sites for Chinese scientists to study the marine environment and resources and solve major scientific problems that require long-term observations. The scientific goal of the oceanography integrated voyage of the SCS is to study the Marine environmental scientific issues in the SCS through the observation of multi-disciplinary integrated voyage, to understand and explore the regional response of marine dynamics, environment and ecological processes in the SCS under the background of global change, and the ability of natural and human activities to influence the SCS ecosystem. Through comprehensive investigations and studies in multiple disciplines such as a physical ocean, marine biology, marine chemistry, and marine geology, we can obtain regional marine samples and environmental parameter records to better understand the changing laws of the marine environment in the SCS, and serve the development of marine resources and ecological environmental protection in my country. At the same time, it provides data and technical support for the research and development of the SCS high-precision comprehensive marine forecast system. When the shared voyage of the NSFC was first launched in 2010, only one voyage was arranged in the SCS. After two years of operation, good results have been obtained and a large number of fund projects have been attracted to the Marine observation and research in the SCS. Due to the substantial increase in observation requirements, relying on only one shared voyage is far from meeting the observation needs of related projects. In 2012, voyages in the northern SCS and SCS were set up in the SCS. With the explosion of observation demand, the northern, central and

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western sections of the SCS were set up respectively in 2013 according to the core observation area. In 2016, an independent section of the Pearl River Estuary survey was set specifically in view of the concentration of nearshore observation items in the western SCS.

7.1.1.4

The Observation of Warm Eddy in the Central and Western South China Sea

In the central and western waters of the SCS, the circulation in spring and summer has very obvious mesoscale motion characteristics, especially at the end of spring, the area often has a long-lasting mesoscale warm eddy—the Xisha warm eddy (Fig. 7.5). The typical life cycle of the eddy is 3–4 months, usually begins to form in early March, reaches the strongest in May, and disappears in June, with the maximum intensity of the center exceeding 25 cm (SSHA). It is of great significance to carry out continuous comprehensive observation and research on the Marine environment in order to ensure the security of military and civilian life in the Xisha area and the government decision-making, and to reveal the characteristics of Marine environmental dynamic change process and its ecological effect. For this reason, the SCSIO, CAS organized special warm eddy surveys and carried voyage surveys to continuously observe the mesoscale warm eddies in the Xisha waters for many years. In 2010, the hydrological observation team of Xisha Warm Eddy Voyage completed the survey task of the voyage implementation plan. This voyage totaled about 500n mile and lasted 5 days. It realized the CTD observation of the whole journey and completed the observation of 27 CTD stations (Fig. 7.6). The depth of CTD delivery was 1500 m in deep water and 10 m from the bottom in shallow water. In addition, a total of 43 XBTs were deployed, and 39 XBT station observations were completed. In 2011, the SCSIO, CAS carried the “Shiyan 2” comprehensive scientific research ship along the survey line from Hainan Island to Xisha, using navigational surveys and sampler sampling to conduct surveys. Twenty CTD stations were actually completed, CTD observations were carried out during the whole journey, GPS sounding balloons were put in every 2 h, XBT was put in fixed points, and the whole process was observed by automatic weather stations. Due to the limitation of the winch cable, the maximum depth of CTD lowering is 400 m; due to the failure of the navigation CTD, data is only obtained on part of the survey line. On May 15, 2012, the “Shiyan 1” scientific research ship set off from Sanya City, during which it conducted XBT and GPS sounding operations; conducted cold spring sampling at 11 stations; and 1 station for receiving and releasing buoys. The entire voyage ended smoothly in about 4 days. In April 2013, a warm eddy fusion gradually formed near the Xisha Islands, and marine meteorological observations were carried out against this ocean background (Fig. 7.7). A total of 26 CTDs, 60 XBTs and 48 GPS sounding stations were completed. Among them, 45 sounding stations successfully obtained the atmospheric temperature and humidity profile with an altitude of more than 10 000 m.

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Fig. 7.5 Warm Eddy Position (SLA > 8 cm in the warm eddy area, which was relatively weak in 1994 and 1996 and SLA > 5 cm) obtained from the average of the remote sensing sea surface height anomaly from March to May during 1993–2006 (He et al.2013)

Intensified observations of the Xisha warm eddy were carried out on the Indian Ocean Voyage of the NSFC in 2014. The purpose is to reveal the rapid adjustment of the Xisha warm eddy to monsoon and tropical weather system changes. The observation plan includes sailing observations: AWS, 38 kHz ADCP, sailing pCO2 and sailing 21CT. Observation of the large-surface station: XBT and CTD are released at intervals (interval of 30n mile), GPS sounding (4 times a day). Observation implementation status: GPS sounding and XBT were launched at 4 pm on March 30, 2014, and 8 stations on the temperature and salinity profile, 10 GPS sounding stations, as well as data from the AWS automatic weather station, 38 kHz ADCP, and pCO2 and 21CT of the navigation observation were obtained for the Xisha warm eddy (15°–17° N, 100°–112° E). In August 2017, based on the special joint observation voyage of the WPOS warm eddy in the northern SCS, in view of the current status of strong warm eddy activity in the Xisha sea area, the SCSIO, CAS organized a supplementary observation of the Xisha warm eddy. This voyage completed 20 CTD observation stations (34 times stations), and the launch depth was 1150db. Navigating ADCP observation; navigating surface temperature and salinity (CTD) observation; automatic weather station observation, including wind speed, instantaneous wind speed, wind direction, air temperature, air pressure, and relative humidity; cast 17 XCTDs, release 9 GPS soundings, and release temperature 1 set of chain buoys. In addition, the voyage also

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Fig. 7.6 The SLA contour map and route diagram on August 12, 2010

investigated the nutrient salinity and chlorophyll profile structure of the Xisha warm eddy area, and implemented other targeted observational research, such as research on the distribution characteristics of particulate nitrogen isotope and POC, research on new and regenerated productivity of phytoplankton, changes in phytoplankton grain structure and microbial diversity under the influence of warm eddy, research on the response of microbial diversity to the warm eddy. Traces of the Xisha warm eddy has been found in the temperature and salinity field observed for many years, but there are certain differences in the location and intensity of the eddy each year. The warm eddy in the spring of 2004 is also shown in the voyage data in May 2004, which is a typical representative of a spring warm eddy. Two warm eddy centers appeared in the western SCS in the spring of 1998. Observations on the two voyages in April and June 1998 found that the warm eddy structure was in an inverted funnel shape, with a surface diameter of about 2 longitudes and a depth of about 400 m. Comparing with the corresponding wind field and rainfall field in the

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Fig. 7.7 Observation (exploration) of stations and routes in April 2013

same period, it is found that the wind speed has a tendency of turning and shearing in the warm eddy area, and rainfall is obviously higher in the warm eddy area, and the warm eddy also has a certain influence on the local convection on the sea surface. In addition to conducting targeted observations on the Xisha warm eddy and its air-sea interaction of weather-scale, the pressure-recording inverted echo sounders (PIES) of the Xisha area (Zhu et al. 2015) have been finished by the Second Institute of Oceanography, State Oceanic Administration under the funding of the “The AirSea Interaction and Evolution of Ocean Circulation and Eddy in the SCS” project. This mission deployed an array of five PIESs across the continental slope in the northern SCS, along a satellite track (Pass114) of the TOPEX/POSEIDON and Jason1/2 altimeters, by carrying the “Shiyan 3” scientific research ship in October 2012. Combined with the results of the 22 year long-term flow series in the northern SCS obtained by inversion and reconstruction of satellite sea surface altimeter data, the influence of mesoscale eddies on the quantity of flow is discussed, which provides a new understanding of the seasonal changes of the SCS circulation and reveals the mesoscale eddies. It is pointed out that the anticyclonic eddy in the northern SCS affects the vertical velocity shear and stratification and makes the near-inertial wave reflect and propagate inside the eddy. At the same time, it is pointed out that the largest warm eddy in history obtained a large amount of energy from the western boundary current during the migration process, and exhibited an abnormal longdistance northward migration.

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7 South China Sea Observation and Data Assimilation

Other Voyage Observations

In addition to the above-mentioned observation plans with good sustainability in terms of time, a series of other observation plans have been implemented for different physical processes in the SCS. The following observation plans have a relatively large impact. The most influential is the SCS Monsoon Experiment (SCSMEX, 1996–2001), an international cooperative research program jointly organized and implemented by several countries and regions. Aiming at the relevant changes in the sea-air flux and corresponding characteristics of the ocean before and after the onset of the SCS monsoon, the plan organizes an international joint survey combining large-scale navigation and fixed-point observation to reveal the onset mechanism of the SCS summer monsoon and its dynamic and thermodynamic characteristics. In view of the process of the onset, maintenance and change of the SCS summer monsoon, a comprehensive marine meteorological observation and research scheme is designed, which combines multi-ship synchronization, large surface sailing and fixed-point observation. Before and after the onset of the SCS summer monsoon in 1998, two phases (IOP1/IOP2) of joint marine and land observations were implemented. The observation periods were from April 22 to May 26 and June 4 to July 21, 1998. Observation missions are mainly composed of “Shiyan 3” (SY3), “Haijian 74” (HJ74) (the second phase mission is replaced by “Xiangyanghong 14” survey ship) and “Kexue 1” (KX1) scientific research ship. Among them, SY3 mainly implements 3 section observations and 1 fixed-point continuous station observation in the northern SCS, HJ74 implements large-area navigation observations, and KX1 also conducts partial section observations in addition to fixed-point continuous station observations in the southern SCS. A total of 497 stations of CTD observation and meteorological observation tasks were completed in the first phase, and a total of 796 CTD observation stations were completed in the second phase. At the same time, radar and air sounding on islands such as Dongsha and Xisha, as well as Taiwan’s anchored buoys and CTD observations were implemented. It can be seen from the T–S diagram before the monsoon onset (Fig. 12a), during the spring voyage of 1998, there were signs of subsurface high salinity water and midlevel low salinity water entering the SCS. At deeper depth, there were obvious signs of deep water intrusion in the western Pacific Ocean (the T–S diagram separated in the deep layer). It should be noted that there may be a problem with one of the thermohaline profiles (the profile with a question mark). After the onset of the summer monsoon (Fig. 12b), the subsurface water (or subsurface mixed water) and intermediate water activities of the western Pacific weakened, but the signs of deep water intrusion were still obvious; at the surface, there have still water activitie which property are similarity to the surface water of the western Pacific. Another noteworthy phenomenon is that after the onset of the summer monsoon, the salinity of the surface water in the SCS is significantly lower than before the onset of the monsoon. This may be directly related to the abundant rainfall after the onset of the summer monsoon. In addition, it can be seen from the T-S diagram that the subsurface water has obvious bifurcations, among which the bifurcation before the

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monsoon onset is more obvious, indicating that the subsurface water of the SCS is more differentiated before the monsoon onset (Fig. 7.8, 7.9, 7.10 and 7.11). SCSMEX observation results show that the intraseasonal modes of 30–60 days and 10–20 days have an important influence on the SCS monsoon and the distribution of related precipitation (Xu and Zhu 2002), revealing that between the large-scale circulation and the mesoscale convective systems is a positive feedback effect and the warm SST in the SCS has an important impact on the onset and intensity of the SCS monsoon (Ding et al. 2004). SCSMEX observations have also been applied to

Fig. 7.8 T-S diagram of spring and summer voyages during the phase IOP1 of SCSMEX in 1998

Fig. 7.9 Station distribution during SCOPE-PILOT voyage from June 20 to July 10, 2007 (section E1–E7) and station distribution during SCOPE II voyage from July 23 to 31, 2016 (S1–S2, E1–E7). The three pentagrams in the figure are mooring observation stations of two voyages

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Fig. 7.10 The large scale observation stations for the dilute water of the Pearl River in April (black), May (blue) and June (green) of 2016

regional numerical models to improve simulation and improve short-term forecasting capabilities (Liu and Ding 2003; Ren and Qian 2001). Under the support of the project of “The Air-Sea Interaction and Evolution of Ocean Circulation and Eddy in the SCS” and WPOS special funding, the First Institute of Oceanography of the State Oceanic Administration cooperated with the Bureau of Marine Fisheries Research of Indonesia to continuously observe the sea current and bottom temperature and salinity in the Kalimata Strait (Fang et al. 2010). Observation results show that the seasonal changes in the Karimata Strait’s flow are significant. In winter (Northern Hemisphere), the monthly average flow of the Karimata Strait is up to −3.6 Sv, with an average of −2.7 Sv, flowing from the SCS into the Java Sea; in summer, the maximum monthly average flow is 2.6 Sv and the average is 1.2 Sv, flowing from the Java Sea into the SCS. The average annual flow of the strait is −0.6 Sv, which flows out of the SCS. The observation results also show that there is a southward flow at the bottom of the strait all year round, indicating that in addition to the control of the monsoon field, ocean currents are also affected by the height difference between the SCS and the Java Sea, which once again proves the existence of the SCS branch. In addition to the above observation of large-scale circulation dynamics in the entire deep-sea basin of the SCS, there are a series of observation specifical voyages for the offshore oceanographic processes in the northern shelf and slope areas of the SCS and the dynamics of the Pearl River Estuary. In July 2007, in view of the nearshore oceanographic characteristics of northern SCS, especially the relevant dynamics characteristics of the upwelling of Guangdong, the SCSIO, CAS, the Institute of atmospheric physics, Chinese Academy of Sciences, the Xiamen University, the Third Institute of Oceanography, State Oceanic Administration and the Hong Kong University of science and technology jointly organize the implementation of the SCOPE-PILOT observations voyage (Fig. 7.9). The voyage was carried out by the “Shiyan 3” research ship, which carried out a multi-disciplinary and large-scale comprehensive survey on the east coast of Guangdong, and set up

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Fig. 7.11 Salty tide observation navigation and continuous observation stations from December 2007 to January 2008

three sets of mooring to observe the transport characteristics of bottom cold water across and along the continental shelf. In July 2016, on the basis of fully excavating and digesting the survey data of the SCOPE-PILOT observation voyage, the SCOPE II voyage was organized and implemented again. This voyage studied the upwelling dynamic adjustment and corresponding ecological and environmental characteristics during the prevailing summer monsoon and monsoon interval, and selected a low-pressure activity before and after to carry out multidisciplinary comprehensive observation.

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Fig. 7.12 Node distribution of hydrometeorological real-time observation network in Xisha and the northern SCS

From the late 1990s to the present, dozens of voyages have been conducted in the Pearl River Estuary, for example, in 2016 (Fig. 7.10). The significant seasonal and interannual variability in Pearl River freshwater runoff and the East Asian monsoon over the years has led to significant seasonal and interannual variability in the expansion and intensity of the Pearl River alluvial freshwater plume. Ou et al. (2009) categorized the expansion of the Pearl River freshwater plume on the northern shelf of the South China Sea into four patterns: seaward expansion, west Guangdong expansion, east Guangdong expansion, and symmetric expansion. Zu and Gan (2009, 2015), Luo et al. (2012), and Zu et al. (2014) have also investigated the rapid response of the Pearl River flume and its fronts to physically driven changes in wind, tide, and runoff using a numerical model of the Pearl River estuary circulation based on observational data. In winter, the runoff decreases sharply, the seawater goes upstream (backflow), and the mixing of salt and fresh water causes the water in the upstream river to become salty. The formation of salty tides is an important environmental problem

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in the Pearl River Delta. Through several voyage surveys of the Pearl River Estuary in the winter of 2007 (Fig. 7.11), the winter of 2009, and the winter of 2010, the relationship between the intensity of salt tide intrusion and the weather, runoff and tidal current was studied (Luo et al. 2010). The salt water from the sea is traced back along the Humen Waterway and Modaomen Waterway, and the scope of influence can reach various water works in Guangzhou and Zhuhai; the Hengmen Waterway is basically not affected. In the process of salt tide intrusion, factors such as topography, runoff, tide and wind have some influence on it. In different entrance waterways and at different times, runoff and tidal current have different strengths. The increase of runoff will suppress the upward tracing of salt water. The shoal area outside the entrance will block the upward tracing of salt tides. The wind directed downstream along the river channel is conducive to the enhancement of density circulation, and the weakening of tidal mixing enhances the pressure gradient. The latter two promote the movement of the outer sea water towards the entrance. In order to study the intrusion of salt tides in the Pearl River Estuary in winter, Zhou et al. (2014) established a hydrodynamic model of the Pearl River Estuary based on observational data and the EFDC model, and studied the effects of runoff, tides, wind and sea level rise on salt tide intrusion through numerical experiments.

7.1.2 Offshore and Station Observation Network 7.1.2.1

South China Sea Hydrometeorological Real-Time Observation Network

The SCS Hydrometeorological Real-time Observation Network collects and transmits real-time observation data to the research and application platform, aiming at the sea surface elements and the nearshore observation elements. The system has 23 online observation nodes, which are mainly composed of the following parts: (1) The island/island margin observation system based on the automatic weather station, wave meter and boundary layer tower on Yongxing Island of Xisha Islands; (2) the upper marine environment observation system composed of marine meteorological buoys; (3) Ocean optical buoy observation system; (4) The high-frequency ground wave radar observation system was deployed along the west coast of Guangdong (Fig. 7.12). The observation area of the SCS Hydrological Meteorological Real-time Observation Network covers the waters of the Xisha Islands, Sanya Bay, Pearl River Estuary, and the coast of northern Guangdong. Observation parameters include temperature, humidity, pressure, wind speed, wind direction, visibility, rainfall, surface flow, profile flow, waves, tide level, water temperature, salinity, ocean optical attenuation profile and ocean water optical absorption coefficient, etc. The observation network is a marine observation network for both military and civilian use, and is the ocean, atmosphere, and ecological multidisciplinary. It can realize three-dimensional continuous simultaneous observation of marine hydrometeorological environment in the

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central and northern SCS, Actively explore and establish a feasible hierarchical datasharing mechanism to provide domestic marine research institutions with accurate monitoring data, and at the same time provide a test platform for integrated research on various layers of the ocean, effectively serving domestic and overseas marine scientific research and practical applications. Breakthrough innovations have been made in technologies such as synchronized observation of networking, the encrypted transmission of data, C/S architecture data service platform, and real-time parameter correction of numerical prediction model accuracy. (1) Island/island margin observation system The observation system of the island/island margin is mainly composed of the following parts: shore-based automatic weather station, wave tide meter/water level gauge, and sea-air flux observation tower and other sub-nodes. • Shore-based automatic weather station An 8 m high mounting bracket is installed on the top of the office building on Yongxing Island in the Paracel Islands, and a mechanical wind speed and direction measuring instrument and temperature, humidity and air pressure sensors are installed on the top of the bracket to observe the land surface observation elements of the island. The relevant observation data is transmitted back to the data collection center in real time via the 3G network. • Tide gauge/water level gauge Using the pressure wave tide gauge independently developed by the SCSIO, CAS it is fixedly installed on the coral reef of the lagoon with a seabed-based mounting bracket. The installation water depth is more than 20 m and the distance from the coast is more than 100 m. Real-time power supply and communication with armored cables, solar panels and data acquisition boxes are installed on the shore, and real-time data transmission is completed through the 3G network. • Construction of sea and air flux observation tower in Xisha The height of the sea-air flux observation tower is 20 m, and the main structure is a galvanized tube self-standing tower (Fig. 7.13). According to the observation requirements of air-sea flux elements, the gradient flux observation system includes: four-layer gradient Veisalla HMP155A temperature and humidity probes (4) at 5, 10, 15 and 18 m, Met-One wind speed and direction sensor, the sampling frequency is 1 times/s; Two pairs of up and down Kipp & Zonen CMP 22 short-wave radiation sensors and Kipp & Zonen CGR 4 long-wave radiation sensors are installed at 10 m, and the sampling frequency is 1 time/s. The eddy correlation rapid response instrument is installed at 20 m; The Gill In. R3-50 three-dimensional ultrasonic wind/temperature meter and Li-cor7500 A infrared water vapor carbon dioxide detector be installed, and the sampling frequency is 10 times/s. The surface water temperature system currently includes an infrared surface thermometer (10 m high). In the future, it is planned to install a surface water temperature meter and other high-performance dynamic water temperature meters not far from the tower.

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Fig. 7.13 Complete view of the flux observation tower instrument installation

Using gradient and eddy correlation algorithms, data such as latent heat flux and sensible heat flux at the air-sea interface, upward and downward long and short wave radiation and net radiation can be obtained. The gradient observation data of wind, temperature and humidity in the lower atmosphere, latent heat flux, sensible heat flux, upward and downward long and short wave radiation and net radiation at seaair interface can be obtained continuously and at high frequency. A large number of observational data will strongly promote the study of the effects of regional sea-air interaction on tropical weather systems and upper ocean physical processes, as well as the improvement of the parameterization scheme of sea-air flux processes related to the sea-air interaction. (2) Upper Marine environmental observation system The upper Marine environment observation buoy is mainly equipped with temperature and salinity sensors, Nortek ADP and YSI ecological sensors to measure the near-surface temperature and salinity elements, ocean current, dissolved oxygen and chlorophyll and other parameters, respectively. The wind meter, visibility meter and weather meter on the buoy tower measure wind speed and direction, visibility, temperature and relative humidity respectively. An electronic compass on the tower, used to measure the buoy’s position, is combined with a wind sensor to obtain the true wind direction. Nortek’s Aquadopp Doppler current meter is installed at the lower end of the buoy, which can measure the ocean current of each 1 m layer within the range of 20 m. YSI ecological sensor can observe 5 ecological parameters such as temperature, salinity, dissolved oxygen, chlorophyll, and pH. A GPS module is also installed on the tower to

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measure the latitude and longitude of the location of the buoy. An air pressure sensor and a temperature sensor are installed in the buoy body to observe the air pressure and cabin temperature respectively. The central controller is also installed in the buoy to control data collection and processing, and send the data to the GPRS module on the tower. The GPRS communication module sends signals to the public wireless communication network and into the Internet, and from the network interface on the client side to the user’s computer. The power supply of the system is provided by a battery bank, which is charged by electricity generated by the solar panels. Users receive data through the Internet, visual integrated software system for realtime receives the analysis of observational data on the screen shows the change of the parameter process curve such as the wind speed, wind direction, air pressure, air temperature, relative humidity, visibility, cabin temperature, flow velocity, flow, water temperature, electrical conductivity, wave height, wave period, dissolved oxygen, chlorophyll, pH, and buoy latitude and longitude. The data collection interval of the system is 10 min (except the multi-parameter instrument, the collection interval is 30 min), and has the function of data self-capacity. The field data memory can store observation data for more than one year. The data collection interval of the system is 10 min (except for the multi-parameter instrument, the collection interval is 30 min), and has the function of data self-capacity. The field data memory can store observation data for more than one year. Central controller design includes power supply system design, solar charge and discharge controller, clock interface circuit, IIC interface circuit, serial port expansion circuit, SD card storage SPI interface circuit, A/D conversion interface circuit, etc. The controller uses a high-performance DSP as the controller, and the software is written in the CCS3.3 environment. The main technical parameters of the buoy sensor are shown in Table 7.1. (3) Ocean optical buoy observation system According to the characteristics of the international development level and trend of optical buoy technology—based on marine buoys and optical radiation measurement technology, combined with the characteristics of the ocean to complete high-tech integration—a set of optical buoys have been developed and used in the waters of the Xisha Islands for a long time (Fig. 7.14), achieved the acquisition of water spectrum data at sea, the laboratory received the data in real-time through the communication system, and the data has been obtained for half a year. The buoy system has achieved a breakthrough in the stability of underwater floating body attitude and optical sensor anti-pollution technology. The entire system has reached the technical level of similar equipment in the world, and the technology is leading domestically, marking that China’s marine optical buoy technology has entered the world frontier level. Through the processing and analysis of on-site realtime spectral data, secondary parameters such as remote sensing reflectivity, light attenuation coefficient, and radiance from water can be extracted. (4) High-Frequency Ground Wave Radar Observation System The large-scale simultaneous observation of surface ocean currents is of great significance for the study of coastal upwellings and mesoscale eddies in the offshore sea,

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Table 7.1 Buoy nodes are equipped with sensor table Parameter

Range

Accuracy

Recommended model

Remarks

MetPak-RG weather station XFY3 Wind direction and speed sensor

The Gill Company, UK National Marine Technology Center

Wind speed

0–60 m/s

± 2%@12 m/s

Wind direction

0–360°

± 3°@12 m/s

Air pressure

600–1100 hPa

± 0.5 hPa

Temperature

−35– + 70 °C

± 0.1°C

Relative humidity 0–100%

± 0.8%@23°C

Visibility

± 10% (10 ~ 10 000 m) ± 15% (10 ~ 20 km)

PWD22

The Vaisala Company, Finland

± 2%

6600EDS

The YSI Company, US

MiniCT

Shanghai P-Nav Scientific Instruments Co., Ltd

TRIAXYS sensor

The AXYS Company, Norge

Nortek’s 600 K ADP

The Nortek Company, Norge

10–20 000 m

Dissolved oxygen 0–500 mg/L Nutrients

0.007–28 mg/L

± 0.08 mg/L

Chlorophyll

0–400 µg/L

± 5%

pH

0–14

± 0.2

Water temperature −5–35 °C

± 0.01 °C

Conductivity

0–80 mS/cm

± 0.01 mS/cm

Effective wave height

0–10 m

± (0.3 + 5% × Measurements)

Significant wave period

3–30 s

±1s

Main wave direction

0–360°

± 10°

Doppler flow velocity

± 10 m/s

± 1% (±0.5 cm/s)

Fig. 7.14 Marine optical observation buoy

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especially for the study of the offshore marine hydrodynamic environment under extreme weather conditions. With the special funding of the CAS, the SCSIO, CAS purchased two domestic high-frequency ground wave radar equipment produced by Wuhan Devices Company in 2011, using portable transceiver antennas. After the equipment was in place in 2012, the equipment single-station performance inspection and test were first carried out at the Bohe Weather Station of Maoming City Meteorological Bureau. Due to the limitation of the observation site, many observation equipment and antennas in the initial observation site seriously affected the ground wave radar waveform, which in turn affected the accuracy of the observation data. After many on-site tests and adjustments by the manufacturer, it was later replaced with an integrated transceiver antenna and the antenna was removed the meteorological observation field moved to a slope closer to the waterline, obtained ideal radar operating parameters, and started business operations. Subsequently, the construction of the dual-station system was completed in 2014, and the two observation stations were located on Naozhou Island in Zhanjiang City and Bohe Town in Maoming City (the Doulong Station and Bohe Station in Fig. 7.15, respectively). The observation results (Fig. 7.16) show that the root mean square error of radial flow detection at Bohe Station and Doulong Station is only 8.62 cm/s and 13.79 cm/s, respectively. There are obvious irregular semidurnal signals in the high-precision

Fig. 7.15 Observation area of high-frequency ground wave radar in western Guangdong and location of mooring array. The blue fan shape and the black fan shape are the maximum detection area and effective detection area of the two radars, respectively

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Fig. 7.16 Contrast curve and scatter diagram of radial velocity observed by single-station HF ground-wave radar and ADCP mooring observation

area, and the M2 tidal currents in the central sea area show obvious characteristics of reciprocating current.

7.2 South China Sea Mooring Observing Network (1) West boundary flow observation system The Western Boundary Current is the strongest flow in the SCS and is the main artery of the SCS. In the past, the understanding of the western boundary current of the SCS was mainly obtained through dynamic calculation, ship drift, floating buoy data, and numerical simulation results. The direct continuous observation of ocean current was never used to obtain the velocity and discharge of the western boundary current of the SCS. In the key sea area of the west boundary current of the SCS, the continuous current data and partial temperature and salinity data were obtained through the deployment of mooring/seabed based observation system in winter with the largest flow. The earliest time-series observations on the western boundary current of the SCS by the SCSIO, CAS can be traced back to the mooring, which was placed on the west side of the Central SCS Basin by the 2004 Nansha Comprehensive Scientific Expedition Voyage. In September 2005, it successfully obtained continuous ocean current profile observations for more than one year. According to the data, the vertical

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Fig. 7.17 Mooring array in the northwestern SCS

structure of the current in this sea area and its seasonal and intraseasonal evolution characteristics are obtained, and a clear baroclinic tidal current signal is given. Subsequently, under the funding of the offshore marine observatory project of the Chinese Academy of Sciences, since 2007, a systematic observational study of the western boundary current in the northwestern SCS has been carried out in Xisha and its adjacent waters, focusing on related ocean processes related to the western boundary current, such as the interaction between boundary currents and mesoscale eddy, the Xisha deep eddy, the Rossby wave of the northwest sub-basin topography, etc., set up a mooring observation array (Fig. 7.17) for long-term continuous observation. The equipment invested includes ADCP, SBE37 CTD, SBE56T, Andra current meter, ALEC CT and MCLANE climb CTD, etc. From December 2013 to July 2015, under the joint support of the project of “The Air-Sea Interaction and Evolution of Ocean Circulation and Eddy in the SCS” and WPOS special funding, the SCSIO, CAS and the First Institute of Oceanography of the State Oceanic Administration has organized and implemented multiple joint observation voyages from Wanning, Hainan to Xisha Observation Section, and deployed 3 sets mooring and 1 seabed-based observation system for continuous observation of ocean currents and temperature and salinity of the western boundary current of the SCS. After July 2015, the observation array has been further expanded and maintained under the funding of the WPOS special project and the major instrument industrialization special project of the Academy of Sciences. So far, observations on the western boundary current in the northwestern SCS has lasted more than 10 years. The observation results show that the intensity of the west boundary current in the continental shelf area in winter is much greater than that in the deep sea area. The width of the current in the southeast of Hainan Island is about 160 km (including

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the continental shelf width of about 70 km), and the depth can reach more than 800 m, with no countercurrent in the middle. The volume transport of the western boundary current is (14.7 ± 3.0) SV, of which about (2.6 ± 1.1) SV flows through the continental shelf. (2) Dongsha separation flow observation system Based on the ADCP data of many years of open voyages in the northern SCS, after the results of the tide filtering process using the polynomial tide filtering method (Fig. 7.18) show that the mid-level flow (about 500 m) on the northern slope of the SCS in early autumn, the seawater west of the Dongsha Islands on the land slope flows to the northeast along the isobath. When it flows to the south of the Dongsha Islands, the seawater begins to deviate from the isobath constraint and flows across the isobath toward the deep sea, which is the Dongsha Separated Current. The circulation of the SCS “973 project” to strengthen the observation summer voyage in August 2000, placed near the Dongsha island, the current meter observations (Fig. 7.19) also confirmed the existence of the east sand separated flow. In the whole observation period, October and March show up shallow water flows across the isobath, other times have obvious characteristics of flow to the deep sea, which is basically consistent with the results of the ADCP analysis of sailing. In order to clarify the distribution of the flow field near Dongsha and determine the driving mechanism of the land slope circulation on the east and west sides of the Dongsha Islands, the SCSIO, CAS and the First Institute of Oceanography of the State Oceanic Administration jointly established five moorings in the Dongsha Islands. In the observation array (Fig. 7.20), the survey lines are set up in the direction perpendicular to the land slope and along the direction of the land slope. The upperocean temperature chains are set up in the 5 moorings. Among them, DS03 and DS04 are equipped with dual temperature chains, one of which is set at a depth of 250 m from the seabed, and the other is set at a depth of 150–00 m from the surface. The upper-ocean temperature chain mainly focuses on the temperature, salinity and dissolved oxygen characteristics of the sub-middle water and middle upper water. Among them, has 3 layers of dissolved oxygen, 3 layers of conductivity, 39 layers of temperature and 1 layer of pressure be used with ADCP pressure probes. The lower ocean temperature chain mainly focuses on the temperature, salinity and dissolved oxygen characteristics of the deep water, including 4 layers of dissolved oxygen, 8 layers of conductivity, 11 layers of temperature (the first layer is the thermometer with the current meter), 1 layer of ocean current, and 3 layers of pressure. (3) Flux observation system in the Luzon Strait The Luzon Strait flux observations by the SCSIO, CAS first started in 2001, and were implemented with the funding of the SCS Circulation “973 Project” intensified observation voyages. At that time, the observation point was still a certain distance from the Luzon Strait, and the purpose was to monitor the basic situation of the SCS branch of the Kuroshio. Subsequently, under the support of the “863 Project” and the construction project of the offshore ocean observatory station of the Chinese Academy of Sciences, continuous observation of the sea current profile on the west

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Fig. 7.18 Initial observation of flow field at 471.5 m near Dongsha Islands. The black triangle is the location of Dongsha Island. The ADCP data acquisition time of the voyage is: a. September 5–23, 2004; b. August 11 to September 2, 2008; c. September 5–23, 2010

side of the Luzon Strait has been carried out since 2008. Initially, only two stations were set up, located at 21° N, 120° E, and 19.5° N, 120° E. The observation equipment includes ADCP, single-point current meter, Self-contained temperature and salt depth instrument, ALEC temperature salinometer, etc. Subsequently, a continuous current profile observation point was maintained at 20.5° N and 120° E under the support of the construction project of Xisha and Nansha Station. In 2015, under the special support of WPOS, in order to better observe flux in the Luzon Strait, the observation point was shifted eastward to 120.5° E, and the current time series observation station was set up at 20° N and 21° N respectively. After 2016, another observation station was added at 20.5° N to improve the current observation capacity in the Luzon Strait (Table 7.2).

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Fig. 7.19 Velocity data at 1500 and 2000 m observed by Andra Current Meter. The observation time is from August 20, 2000 to March 17, 2001. “A” means along the depth contour direction (to the east is positive), “V” means the vertical contour direction (to the shallow water direction is positive); the pentagram in the small picture is the position of the observation station, and the triangle is the position of Dongsha Island. The data has been smoothed for 7 days

In the future development of observing networks, the use of higher-end observing technologies should be encouraged. Since the mooring array can provide long-term, continuous high-precision time series data, it has been widely used in global and regional observation networks. Therefore, the future development of the SCS Observation Network should add the observation network of the mooring array, similar to TAO/TRITON, RMMA (McPhaden et al. 2009), PIRATA (Bourles et al., 2008), BOOS (Dahlin 1997) and MONGOOS. Underwater gliders can use buoyancy and double wings to conduct vertical and horizontal profile observations in the water. It is a very efficient and long-term observation method that can perform multiple observations (Rudnick et al. 2004). Observational data from underwater gliders have been successfully used to reveal the important impact of atmospheric teleconnection on California’s circulation system during El Niño in 2009/2010. Such observations

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Fig. 7.20 Schematic of observation mooring array position in Dongsha Islands

Table 7.2 Basic information of submersible buoy observation station in the Luzon Strait Station

Instrument startup time

Actual location

Depth (m)

latitude

longtitude

E402

August 18, 2008

21° N

120° E

3150

E405

August 20, 2008

19°30, N

120° E

4174

Mooring of Luzon Strait Mouth

November 25, 2010

20°30, N

120° E

3295

Mooring of Luzon Strait Mouth

September 06, 2011

20°30, N

120° E

3342

Mooring of Luzon Strait Mouth

August 12, 2012

20°30, N

120° E

3352

LS01

September 20, 2015

21° N

120°30, E

1650

LS02

September 20, 2015

20° N

120°30, E

3855

LS01

June 19, 2016

21° N

120°30, E

1606

LS03

June 20, 2016

20°30,

120°30,

E

2193

LS02

June 20, 2016

20° N

120°30, E

3866

N

LS01

July 15, 2017

21° N

120°30,

E

1606

LS03

July 15, 2017

20°30, N

120°30, E

2193

LS02

July 15, 2017

20° N

120°30, E

3866

will consume a lot of money and manpower if conventional ship-borne observations are used (Todd et al. 2011). Therefore, in the future development of the SCS Observation Network, a large number of mooring arrays and underwater gliders will be introduced to obtain long-term continuous observation data with high spatial and temporal resolution.

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7.2.1 South China Sea Observation Database With the continuous accumulation of observational data, the management of rapidly growing diversified data and description data has become the core issue of observational data management. Therefore, it is necessary to introduce a complete set of management procedures, including network expansion design, sensor installation and calibration, data collection, point data upscaling, data quality control and data storage, etc. The current voyage data will be directly stored in the data server after the end of each voyage, and the observations from the station can be transmitted to the data server in real-time. Careful quality control will be carried out on all data one by one to remove unreasonable and inaccurate data. The data of individual voyages can be viewed on the data website of the SCSIO, CAS, and relevant data can be obtained through the application (Xu et al. 2010; Huo et al. 2012). Details about the various observation equipment in the observation network can be obtained on the SCSIO Open Voyage website. The data from the observation network can be used not only for scientific research, but also for fusion with data from other sources to develop a special database in the SCS. Based on the collection of open data such as WOD and Argo buoys, a large amount of measured data implemented by SCSIO has been incorporated. After multiple strict quality controls, 51,392 temperature and salt profiles have been collected. After gridding and smoothing, a gridded data set SCSPOD14 containing the average temperature and salinity, the depth of the thermocline/mixed layer, and the thickness of the barrier layer of the SCS climate was established. The establishment of this dataset provides reliable data support for analyzing the thermodynamic processes in the SCS, the temporal and spatial changes of water masses, and the characteristics of the SCS basin and mesoscale ocean structures. SCSIO staff verified the accuracy of the main parameters of the latent heat block formula, sea surface temperature, wind speed, and atmospheric specific humidity through 1,727 sounding observation samples, and further using the Xisha Automatic Meteorological Observatory from 2008 to 2010 and the continuous observations of the shelf buoy from March to May 2011 verified the high accuracy of the newly calculated atmospheric specific humidity parameterization. At the same time, in cooperation with W. Timothy and Liu from NASA Jet Propulsion Laboratory, a set of South China Sea daily satellite-derived latent heat flux (SCSSLH) was constructed based on satellite telemetry technology and fixed-point detection data of the airsea interface. Compare and evaluate with 5 existing global latent heat flux data. The results show that SCSSLH can better distinguish the small-to-medium-scale processes and multi-time-scale characteristics of air-sea flux exchange, which is helpful for related research on flux exchange and ocean response in the SCS.

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7.3 South China Sea Data Assimilation and Reanalysis Products The application of ocean satellite remote sensing provides a large amount of sea surface data for ocean research. The abundant observation methods such as buoy observation and ship observation provide a large amount of three-dimensional observation data for oceanography research. However, due to the particularity of the marine environment and the high investment in ocean observations, these observations still have some defects in their temporal and spatial distribution. For example, satellite remote sensing observations can only provide information on the surface of the ocean; the number of buoy observations and voyage observations is very limited, and they are not continuous in space and time. Ocean data assimilation can effectively integrate the existing ocean observation data into the ocean model, which can provide more complete reanalysis data in temporal and spatial distribution. In the 1960s, the application of Cressman’s assimilation method (Cressman, 1959) marked the beginning of the embryonic form of a commercial assimilation method. Gandin then proposed a statistical optimal estimation method applied to linear systems, namely optimal interpolation. Subsequently, using optimal theoretical control in nonlinear systems, three-dimensional variational and four-dimensional variational assimilation methods were developed. Because of the need to solve the adjoint equation of the ocean forecast equation and a large amount of calculation, the four-dimensional variational is less applied in the operational ocean forecast. The Kalman filter was proposed for linear systems in the early 1960s. Its characteristic is that the background field information of the model can be transferred forward with the integration of time, ensuring the consistency and stability of the dynamic system during the assimilation process. Since the Kaman filter needs to store the background error covariance matrix during the mode integration process, this matrix is so large that it is difficult to be practically applied to the real ocean three-dimensional original equation model under the existing calculation conditions. The Ensemble Kalman filter is introduced into ocean data assimilation by Evensen (1994) on the basis of the Kalman filter. Ensemble Kalman filter does not need to explicitly solve the background error covariance matrix, which makes its requirement on computing resources significantly lower than that of the Kalman filter, and has developed rapidly in the past ten years. Ensemble Kaman smoothing is that the analysis field at a certain time in the process of data assimilation not only uses the observation data before this time, but also uses the observation data after this time. This method has obvious advantages in the reanalysis of ocean data, but compared to ensemble Kalman filtering, ensemble Kalman smoothing requires a larger amount of calculation. In order to reduce the requirement for computing resources, an ensemble Kalman smoothing method with two-step filtering of “forward–backward” in time is adopted. In view of the limitation of computing resources, most of the current marine data assimilation systems in foreign operations still use three-dimensional variational and optimal interpolation assimilation methods, such as the FOAM assimilation

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system established by the UK meteorological agency, the ENSO prediction system of the Japan meteorological agency, and the US national center for environmental prediction of global ocean data assimilation system GODAS, Italy’s Mediterranean forecast system SOFA, etc. The data assimilated by these assimilation systems are mainly satellite observation data, buoy observation data and other field observation data. In China, the Marine data assimilation started late, among which the relatively early Marine data assimilation system is Ovals assimilation system based on three-dimensional variation established by Zhu Jiang and other in 2006. This assimilation system is mainly applied to the assimilation of satellite altimeter data and buoy temperature and salinity data in the Pacific Ocean. The National Oceanographic Information Center has established a reanalysis system that can simultaneously assimilate the data of Nansen sampler, buoy temperature and salt profile, multi-source satellite sea surface height anomaly and satellite remote sensing sea surface temperature in China seas by using the multi-grid three-dimensional variational method. In recent years, the number of voyage observation data and the available remote sensing sea surface observation data in the SCS have been increasing. The special geographical location of the SCS and its abundant marine resources determine its environmental and military importance. In order to better understand the dynamic and thermal processes of the SCS and provide more accurate initial conditions for forecasting in the SCS, the SCSIO, CAS has established multiple sets of oceanic data assimilation system based on the optimal interpolation, ensemble Kalman filter, ensemble Kalman smoothing, and three-dimensional variational for the SCS science requirements. And provides a set of reanalysis products (REDOS) with high spatiotemporal resolution in the SCS for 20 years (1992–2011) (Zeng et al. 2014).

7.3.1 Application of Optimal Interpolation Method to Assimilate SST Because ocean data assimilation requires high computing resources, the optimal interpolation assimilation method occupies an important position in today’s operational ocean data assimilation. The key issue when assimilating the sea surface temperature is how to project the sea surface information downward. In the process of assimilating sea surface temperature, a variety of assimilation schemes based on optimal interpolation have been extensively studied, but most schemes often use sea surface temperature assimilation to study the correlation between surface and subsurface temperatures. While the SCS is in a seasonally inverted monsoon system, the depth of its mixed layer varies greatly seasonally, and compared to the ocean, the depth of the mixed layer is shallower. These special circumstances determine that the correlation between surface SST and subsurface SST in the SCS varies with the depth of the mixed layer, which is different from that of the ocean. Therefore, in order to test the assimilation scheme in the SCS sea surface temperature in the assimilation system performance and the difference, in order to provide a reference

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for the SCS the sea surface temperature of assimilation, the four existing sea surface temperatures assimilation scheme based on the optimal interpolation is applied to the SCS, and using the data of the SCS monsoon experiment voyage observation of thermohaline compared to its evaluation, is to find out about the sea surface temperature of assimilation scheme (Shu et al. 2009). Scheme 1 is to use the statistical correlation between surface SST and subsurface SST to directly project the SST information downward to get the pseudo-observation of the subsurface and further assimilate layer by layer. Scheme 2 is an improvement of Scheme 1. Before vertical projection of SST observations, objective analysis of SST at the surface is carried out to obtain pseudo observations at each pattern grid point on the surface, and then assimilation is carried out using Scheme 1. Scheme 3 is to use the definition of the mixing layer (the mixing layer is fully mixed with a consistent temperature) to project SST information in the mixing layer. Scheme 4 is to decompose the mode results on each layer by EOF, assuming their spatial modes remain unchanged, and project their time coefficients downward. Considering that the correlation between the adjacent vertical layers is better than the direct correlation between the surface layer and the subsurface layer, Scheme 4 is divided into Scheme 4a (using the correlation between the adjacent two layers to project the sea surface information layer by layer) and Scheme 4b (using the correlation between the surface layer and the subsurface layer to project the sea surface information). The results show that the above four assimilation schemes can greatly improve the simulation of the model in the surface layer, and can better correct the cold deviation of the model (Fig. 7.21). Relatively speaking, scheme 4a, based on EOF decomposition and layer-by-layer downward projection of EOF principal components, can deepen the depth of downward projection of SST information without damaging the temperature structure of the subsurface layer. It is a relatively more effective scheme for optimal interpolation and assimilation of SST in the SCS. However, it is also found that the four assimilation schemes have some difficulties in improving the fine structure of subsurface temperature in the eddy active region of the SCS.

7.3.2 Application of Ensemble Karman Filter and Ensemble Karman Smooth Assimilation in the SCS Considering that univariate assimilation schemes such as optimal interpolation lead to dynamic imbalance in continental shelf ocean processes, an advanced ensemble Kalman filter assimilation system which can update all model predictors simultaneously is established in the northern SCS (Shu et al. 2011b). In the optimal interpolation assimilation system, it has been proved that the improvement of subsurface layer only by assimilating SST is limited. In recent years, the SCSIO has accumulated a large number of voyage temperature and salinity observation data in the northern SCS. Therefore, in this assimilation system, the temperature and salinity data of sea surface temperature and voyage observations are assimilated simultaneously. The

7.3 South China Sea Data Assimilation and Reanalysis Products

431

Fig. 7.21 Monthly mean of AVHRR SST in January 1998 (a) monthly mean of surface temperature deviation between control run and AVHRR SST (b–f) (Shu et al. 2009)

ocean data assimilation system based on the ensemble Kalman filter assimilation method has good performance, can greatly improve the simulation of upwelling intensity and structure, and present a more accurate position of the main axis of the Pearl River dilute water. At the same time, the salinity deviation of the model above the thermocline is corrected to a certain extent (Figs. 7.22 and 7.23). Compared with assimilation methods such as the ensemble Karman filter, the ensemble Karman smoothing assimilation method has unique advantages in data assimilation systems because it can transfer observation information both forward and backward at the same time. However, ensemble Karman smoothing is a more computationally expensive data reanalysis method. At present, it is difficult to carry out a long time, large area, and high-resolution data assimilation. In order to make

Fig. 7.22 Vertical temperature section (Shu et al., 2011b)

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7 South China Sea Observation and Data Assimilation

Fig. 7.23 Vertical salinity section (Shu et al., 2011b)

more effective use of voyage observation data in the northern SCS and obtain high-quality regional oceanic numerical analysis data in a relatively short period of time (generally referring to the voyage observation period). In the basic of abovementioned the ensemble Kalman filter assimilation system, a data assimilation system based on the ensemble Kaman smooth assimilation method in the northern SCS was established. The use of the data assimilation system to assimilate the temperature and salinity observation data of the SCOPE-PP voyage revealed the path and intensity of the eastward propagation of the Pearl River dilute the water in summer, the spatial distribution characteristics and temporal evolution of the upwelling in the northern SCS, and the interaction between the Pearl River dilute water and the upwelling. Mechanism etc. (Shu et al. 2011a).

7.3.3 Redos Reanalysis Products The study of the SCS ocean thermodynamic process and its Spatio-temporal variability requires a set of long-term continuous high-resolution data sets as support. In recent years, although the on-site temperature and salinity data of Argo, buoys, Mooring and ship observations in the SCS have been increasing, the spatial resolution of on-site temperature and salinity observations is still relatively low and the time is very discontinuous compared to the vast ocean, especially the deep ocean. The development of satellite observation technology in the past two to three decades has provided ocean information with a better temporal and spatial resolution than traditional field observations. However, the information obtained by satellite observations is limited to the surface of the ocean and cannot do anything about the interior of the ocean. As an alternative to providing oceanographic data sets, model results provide time-continuous grid oceanographic information and are relatively easy to obtain. However, there are still many uncertainties in the numerical simulation of the SCS and its adjacent waters, such as the water exchange between the SCS and the offshore sea, the generation and degradation evolution of mesoscale dynamic processes in the

7.3 South China Sea Data Assimilation and Reanalysis Products

433

SCS, the heat exchange between sea and air, the mixing within the SCS, and the variability of the main stream systems in the SCS. Because the error accumulation of numerical calculation and the parameterization scheme can not fully fit the real ocean conditions, the simple numerical model is difficult to accurately predict the ocean circulation, and the data assimilation with the observation information is a good supplement to the numerical model. Although global ocean reanalysis products and some regional ocean reanalysis products cover the SCS area, their horizontal resolution is low. In the SCS area, the horizontal resolution is generally from (1/2)° to (1/3)°, which is not enough to study the complex mesoscale processes in the SCS. In the past two or three decades, with the support of the NSFC, the SCSIO, CAS has accumulated a large amount of onsite temperature and salinity observation data in the SCS through a series of voyage observations. These valuable on-site observations, as well as satellite observations of SST and SST data, provide a guarantee for the construction of a set of high-resolution reanalysis products for the SCS. REDOS reanalysis product is a set of reanalysis products with high spatial and temporal resolution in the SCS region for 20 years (1992–2011). It integrates the satellite observations of sea surface height, sea surface temperature and historical temperature and salinity profile data in the SCS and its surrounding waters into the regional ocean circulation model of the SCS.

7.3.3.1

Production of REDOS Reanalysis Products

The production of Marine reanalysis products requires an ocean data assimilation system. The Marine data assimilation system generally consists of three parts: ocean dynamic model, data assimilation technology and observation data. The dynamic module of the assimilation system adopts the Regional Oceanic Modeling System (ROMS). The regional scope is 1°–30° N, 99°–134° E, including the whole SCS and part of the Northwest Pacific Ocean. Horizontal resolution of the model is about 10 km. The data of sea surface height and three-dimensional temperature and salinity current data used for the model boundary were obtained from the monthly average results of SODA. The west boundary is a closed boundary, the remaining three boundaries are open boundaries, and the selected boundary condition is a radiating boundary. Wind field data comes from cross-calibrated multi-platform (CCMP) wind speed data every 6 h. The wind field data is converted to wind stress by the block formula. The temperature, humidity, precipitation rate, and short and long wave radiation of the sea surface from NCEP reanalysis data are also converted into heat flux and fresh water flux by the block formula. The model does not take into account river runoff and tides. The assimilation method uses a multi-scale three-dimensional variational assimilation method, which can solve the “bull eye” phenomenon in assimilation. That is, when the sparse observation data is assimilated on a higher resolution grid, it is easy to have a large local observation increment, which affects the stability of the model. Therefore, it is necessary to obtain smooth large-scale information on

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a lower-resolution grid, and then obtain small-scale information of the observation data on a high-resolution grid. The high-resolution observation data only needs to be assimilated on a high-resolution grid. At the same time, two balance relationships are considered in the multi-scale three-dimensional variational assimilation system: static pressure balance and geostrophic balance. In other words, when assimilating a certain element, according to the dynamic relationship, other elements are adjusted at the same time to make the state field close to the dynamic balance. The construction method of the background error covariance matrix (B matrix) in the assimilation system is to take the difference between the daily simulated value of the ocean model state variable and the average value of the state variable for a total of 90 days before and after it as the forecast error. From this, a long-term state variable error sequence is obtained, and based on this sequence, the spatial distribution and vertical correlation of the state variable standard deviation are calculated, and finally the B matrix is estimated. The data used to construct the B matrix comes from the simulation results of the SCS for 20 years. The observation data involved in assimilation is divided into three categories: sea surface height data, sea surface temperature data, and temperature-salinity profile data. The sea surface height information comes from the delayed on-orbit data of the AVISO program. Delayed data undergoes certain quality control. The specific methods are as follows: (1) Compare with a 12 year average climatic average field and eliminate observations greater than 3 times the standard deviation; (2) Use a Lanczos filter to remove small-scale information; (3) Resample the data to make the data-sparse. In addition, satellite sea surface height observations are prone to “pollution” in the nearshore, and the results of tidal models in shallow water areas are poor. After the tidal signals are filtered out, the sea surface height anomaly data obtained are less accurate in shallow water areas. Therefore, when the SCS ocean reanalysis product is being developed, the sea surface satellite observation data in areas shallower than 200 m will not participate in assimilation for the time being. SST data are derived from satellite observations and ship observations. Satellite observations come from two aspects: AVHRR Pathfinder Version 5.2 data was used from 1992 to 1998, and MCSST data was used from 1999 to 2011, which is AVHRR SST data after quality control by the U.S. Fleet Numerical Meteorology and Oceanography Center (FNMOC). SST data from the ship observations were obtained from the United States Global Ocean Assimilation Experiment (USGODAE). The temperature and salinity profile data mainly come from WOD09 and WOD13, the Argo project data set, and the CTD and XBT data from the voyage observations of the SCSIO, CAS. The observation types in the area of WOD09 and WOD13 data include CTD, XBT, etc. Argo buoy data comes from the French data center. The PFL data also contains part of the Argo data, which needs to be checked during quality control. The spatial distribution of temperature and salinity profiles is shown in Fig. 7.24. It can be seen that the number of observations in the Northwest Pacific is the largest, while the observation points in the SCS are concentrated in the northern SCS. There are fewer observation points in the southern SCS, especially the weak current area in the southeastern SCS. In addition, observations in the shelf area are

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Fig. 7.24 Spatial distribution of temperature profile a and salinity profile, b within the range of the model from 1992 to 2011 (Zeng, 2015)

very rare. Except for more observations along the coast of Guangdong, there are very few observations of temperature and salinity profiles in shallow water areas such as the East China Sea, the Taiwan Strait, the Beibu Gulf, and the Gulf of Thailand.

7.3.3.2

Redos Reanalysis Product Inspection

Compare REDOS with multiple independent observations and other reanalysis data. Preliminary results show that the REDOS results can reproduce the sea surface height, temperature and salinity field and flow field conditions well, and can also simulate some eddy processes, the form of Kuroshio invasion in the SCS, and the distribution of thermocline, mixing layer and barrier layer well. (1) Verification of temperature-salinity field The comparison with more than 2000 independent temperature and salinity profiles (Fig. 7.25) shows that the average root mean square difference of temperature (salinity) of each layer of REDOS is less than 1 °C (0.1 psu), and the maximum value is located in the seasonal thermocline, about it is 1.2 °C (0.12 psu), and the vertical average is about 0.6 °C (0.06 psu). Compared with REDOS, the temperature (salinity) vertical average and maximum root mean square difference of the simulation results are 1.24 (0.16 psu) and 2 °C (0.24 psu), respectively, which are approximately twice that of REDOS. In addition, the REDOS results are compared with the results of the HYCOM reanalysis products. The vertical average and maximum root mean square difference of HYCOM temperature (salinity) are 0.7 °C (0.14 psu) and 1.1 °C (0.22 psu), respectively. The temperature and salinity results of REDOS are better than the results of HYCOM (especially the salinity results) for two reasons: one is that REDOS has constructed a B matrix for the SCS and the Northwest Pacific; the other is that REDOS has assimilated more Observational data in SCS compared to HYCOM.

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Fig. 7.25 Comparison and verification of REDOS and HYCOM temperature and salinity data with independent observations (Zeng, 2015). The light-colored line represents the results of each month for 12 months; the thick-colored line represents the results of the 12-month average

(2) Verification of height field The verification of the sea surface height field is mainly compared with the sea surface height information observed by satellite and water level data observed by hydrological stations. Figure 7.26 shows the correlation coefficient between the sea surface height field of REDOS and the sea surface height field observed by satellite from 1992 to 2011, as well as the standard deviation field of the sea surface height field of reanalyzed products and the sea surface height observed by satellite. It can be seen that in most sea areas, the reanalysis products have a good correlation with the satellite observation results, with the correlation coefficient reaching above 0.8 (passing the 95% confidence test). The correlation of multiple eddy regions is poor, such as the Kuroshio area, the waters east of Vietnam, the waters west of the Luzon Strait, and the waters of Mindanao. In terms of the distribution of the standard deviation field, REDOS is also in good agreement with the satellite observation results. The largest values of sea surface variability are located in the Mindanao Sea Area, the Kuroshio area east of Taiwan, the waters west of the Luzon Strait and the Gulf of Thailand. In addition, geostrophic current anomalies are obtained from sea surface height anomalies according to geostrophic relation, and the eddy kinetic energy of REDOS and satellite observation data is calculated accordingly. The region near the equator does not satisfy the geostrophic equilibrium relation, so the calculation of eddy kinetic energy is only carried out in the region north of 5° N. The mean eddy kinetic energy distribution of satellite observation and REDOS is shown in Fig. 7.26d and Fig. 7.26e, respectively. The results show that the distribution pattern of the mean eddy kinetic energy calculated by REDOS and satellite observation is basically consistent, and

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Fig. 7.26 The sea surface height field of the correlation coefficient between REDOS and satellite observation from 1992–2010 (a); The standard deviation field (unit: m) of the sea surface height field from 1992–2010 satellite observation (b) and REDOS (c); The mean eddy kinetic energy (unit: cm2 /s2 of 1992 ~ 2010 satellite observations (d) and REDOS (e). Red contour represent 100 m isobath lines (Zeng, 2015)

the high-value area of eddy kinetic energy is located in the sea area east of Vietnam, the north equatorial countercurrent area and the Kuroshi area east of Taiwan Island. The REDOS average eddy kinetic energy is weaker than satellite observations in the Kuroshio area to the east of Vietnam and to the east of Taiwan Island, while it is stronger in the north equator against the tide area. (3) Verification of flow field The trajectory data of drifting buoys provided by the Surface Velocity Program was used to qualitatively compare the flow field of REDOS. Figure 7.27 shows the trajectory of the drifting buoy and the distribution of the sea surface height field and the 15 m laminar flow field of the REDOS reanalysis product during the same period. The results show that the subsurface flow field of REDOS is highly consistent with the trajectory of the drifting buoy, especially in some eddy areas, such as the eastern seas of Vietnam (Fig. 7.27a), the eastern seas of Hainan Island (Fig. 7.27b), and the Kuroshio area (Fig. 7.27) and the eastern waters of Taiwan Island (Fig. 7.27d). It is worth noting that REDOS has also successfully reproduced the various ways in which the Kuroshio has invaded the SCS, such as the intrusion in the form of flow sleeves (Fig. 7.27e), the intrusion of eddy shedding (Fig. 7.27f) and direct invasion (Fig. 7.27g).

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Fig. 7.27 Trajectories of drifting buoys (black line, red asterisk represents the starting point of trajectory) and the distribution of REDOS reanalyze the product sea surface height field (contour line, unit: m) and 15 m laminar flow field (unit: m/s) in the same period (Zeng, 2015)

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7.4 Summary and Outlook At present, the South China Sea has formed a regional ocean observation network focusing on the research and service guarantee of the circulation dynamics in the key areas of the South China Sea. The observation covers not only the key areas of the Luzon Strait water exchange, the northern South China Sea land slope current and the western boundary current, which are important large-scale circulation in the South China Sea through the current, but also the coastal upwelling (such as the upwelling in the northern part of the South China Sea, Hainan Island and Vietnam coast), the active mesoscale eddies and small warm pools. The network also covers areas with active mesoscale eddies and the prevalence of small warm pools. The network combines various observation equipment and means, and has both comprehensive observation and special investigation functions. In addition to the upper-level circulation system, the network has been expanding to the middle and deep layers of the South China Sea with the help of submersible and other observation equipment. The long-term observation data accumulated by the South China Sea Observatory Network have strongly supported the systematic development of scientific research on the South China Sea circulation, mesoscale eddies, internal waves, mixing and other multi-scale dynamical processes. In the future, the construction of the South China Sea Ocean Observing Network will further fill the monitoring gaps in key areas and optimize the existing observations. The development of the South China Sea ocean observation network should include sub-networks similar to the submerged marker arrays in other ocean basins to achieve long-term and continuous observations. At the same time, in the stable observation network, we should build mobile observation groups such as unmanned boats and underwater gliders to observe extreme and typical rapid oceanic processes, accelerate the three-dimensional expansion of the South China Sea observation network from the upper layer to the middle and deep layers, and strengthen the coordinated development of observation network construction and observation technology research and development. In addition, it is necessary to improve the capability of real-time transmission and management integration of necessary observation data to serve the forecast system and marine security on time.

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