Remote Sensing Land Surface Changes: The 1981-2020 Intensive Global Warming 303096809X, 9783030968090

This book discusses the detrimental consequences of climate-related land changes over a 40-year period between 1981 and

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Table of contents :
Contents
Chapter 1: Why This Book?
1.1 Land Changes Due to Global Warming
1.2 Living on Warmer Land
1.3 The Goals of the Book
1.4 Book Composition
1.5 Short Summary
References
Chapter 2: Global Warming Impacts on Earth Systems
2.1 Introduction
2.2 Global Temperature and Anomalies for Climate Studies
2.2.1 Development and Accuracy of the Global TA Time Series and UN-Based IPCC Activities
Land, Ocean, and Global Temperature Records
Land Temperature
Ocean: Sea Surface Temperature from Buys
Ocean: SST from Ships
Ocean: Combine SST from Buys and Ships
Global Mean Temperature, Temperature Climatology, and Temperature Anomaly
Multiyear Global Mean Temperature Anomaly Time Series
Basic Assumption Used for the Development of Temperature Anomaly’s Time Series
Preliminary Evaluation
2.2.2 Land, Ocean, and Global Temperature Anomalies from NOAA
Development of Erroneous TA Trend, Using Non-corrected Ships’ SST T Measurements
2.3 IPCC Program: Global Warming and Impacts on Earth
2.3.1 Global Warming and IPCC-Based Earth/Land Changes
Global Temperature
Sea Ice
Arctic
Antarctic
Glaciers and Permafrost
Snow
Sea Level
Ocean
Land
Ecosystems
Greenhouse Gases
Extreme Events
Food Security
2.4 Conclusion
References
Chapter 3: The IPCC Reports on Global Warming and Land Changes
3.1 Introduction
3.2 Climate Warming and Land Changes from the IPCC Reports
3.2.1 Land Changes
3.2.2 Temperature
3.2.3 Land Degradation and Desertification
3.2.4 Food Security
3.2.5 General IPCC Statements and Brief Comments
3.2.6 The Statements
3.3 Evaluation of the IPCC Statements
3.4 Summary
References
Chapter 4: NOAA Operational Environmental Satellites for Earth Monitoring
4.1 Introduction
4.2 NOAA Operational Polar-Orbiting Environmental Satellites (POES)
4.2.1 AVHRR Sensor
4.2.2 AVHRR Data for Vegetation Monitoring
4.2.3 Initial Algorithm for Data Collection
4.2.4 Normalized Difference Vegetation Index and Brightness Temperature
4.2.5 Removing Noise from NDVI and BT
Removing Long-Term Noise
Removing Short-Term Noise
4.2.6 VIIRS Data for Vegetation Monitoring
4.2.7 Continuity of NOAA/AVHRR, S-NPP/VIIRS, and NOAA-20/VIIRS Data Records
4.3 Conclusion
References
Chapter 5: New Remote Sensing Vegetation Health Technology
5.1 Introduction
5.2 What Is Vegetation Health?
5.3 Theoretical Base of Vegetation Health Method
5.3.1 Biophysical Considerations
5.3.2 Basic Laws for Extracting Weather Component from NDVI and BT
5.4 Renewed Vegetation Health Algorithm
5.5 Vegetation Health at Work
5.6 Validation
5.7 Conclusion
References
Chapter 6: Causes of Climate Warming
6.1 Introduction
6.2 Global Warming and Major Earth Changes
6.3 What Is Controlling Global Warming?
6.3.1 Climate System
6.3.2 CO2 and Global Warming
Activities to Reduce CO2
Other Environmental Sources of Global Warming
Prove That CO2 Is Controlling Global Temperature
6.3.3 CO2–TA Match: New Analysis
6.4 New Ideas About the Causes of Global Warming
6.4.1 Warming Due to Ozone Depletion
6.4.2 Earth Climate and Milankovitch Cycle
6.4.3 Milankovitch-Based Precession Cycle
6.5 Summary
References
Chapter 7: Land Cover Changes from Intensive Climate Warming
7.1 Introduction
7.1.1 General Statements
7.1.2 NOAA Satellites, Used for This Analysis
7.2 Land Cover Temperature
7.2.1 Global-Regional Land Cover Temperature (SMT)
World
Hemispheres
Countries
Countries Producing 10–21% of Global Cereals
Countries Producing 3–4% of Global Cereals
Countries Producing Around 2% of Global Cereals
Several Other Countries
7.3 Land Cover Greenness
7.3.1 World and Hemispheres
7.3.2 China, the USA, and India
7.3.3 Brazil, Indonesia, Russia
7.3.4 Argentina, Ukraine, France, Canada
7.3.5 Other Countries
7.4 Summary
References
Chapter 8: Global Warming Crop Yield and Food Security
8.1 Introduction
8.2 Modeling Principles
8.2.1 Yield Time Series
8.2.2 Vegetation Health Indices
8.2.3 Yield-Vegetation Health Models
8.3 Yield-Vegetation Health Models
8.3.1 Global Grain and Food Security
8.3.2 Corn in China
8.3.3 Winter Wheat, Corn, and Sorghum in the USA
8.3.4 Winter Wheat in Ukraine
8.3.5 Corn in Argentina
8.3.6 Wheat in Australia
8.3.7 Rice in Bangladesh
8.3.8 Cereals in Russia
8.3.9 Spring Wheat in Kazakhstan
8.3.10 Corn in Zimbabwe
8.3.11 Other Countries and Crops
8.3.12 VH-crop Modeling for Food Security: Concluding Remarks
8.4 Short Summary
References
Chapter 9: Remote Sensing Malaria During Global Warming
9.1 Introduction
9.2 Modeling Principles
9.2.1 Malaria’s Multiyear Time Series
9.2.2 VHI Applied to Malaria
9.3 Malaria-VH Models
9.3.1 Southeast Asia
Bangladesh
Large Area
Correlation and Regression Analysis
Midsize Area
Correlation and Regression Analysis
Model Validation
Small Area
Data
Correlation and Regression Analysis
Model Validation
Summary
India
Tripura State, India
Environment
Data
Matching Malaria and VH Data
Correlation Regression Analysis
Orissa State, India
Data
Malaria Time Series Analysis
Correlation and Regression Analysis
South Korea
9.3.2 Africa
Swaziland
Tanzania
Malaria Risk Index (MRI)
9.3.3 South America
9.4 Summary
References
Chapter 10: Malaria Performance Trend During 1981–2020 Global Warming
10.1 Introduction
10.2 Earth Climate Warming and Consequences
10.3 Strong Global Warming During 2015–2018
10.4 Global and Continental Malaria Activities, Assessed from 1981 to 2018 Satellite-Based Moisture-Thermal Characteristics
10.4.1 Malaria Activities Assessed Form Vegetation Greenness and Temperature
10.4.2 Vegetation Health Indices as the Indicators of Malaria activities
10.4.3 High Malaria (HM) and Low Malaria (LM), Assessed from Vegetation Health Indices
10.4.4 Percent Global Malaria Area with HM and LM from the 1981–2018 Moisture-Thermal Index (VHI)
10.4.5 Percent Global Malaria Area with HM and LM from the 1981–2018 Moisture (VCI) and Thermal (TCI) Indices
10.4.6 Percent Continental (South America, Africa and Southeast Asia) Malaria Area with HM and LM from 1981 to 2018 Thermal (TCI) and Moisture (VCI) Conditions During Climate Warming
10.5 Percent Malaria Endemic Area with HM and LM (Assessed from 1981 to 2019 Moisture (VCI) and Thermal (TCI) Vegetation Condition) in the Most Malaria-Affected Countries During 1981–2019 Global Warming
10.5.1 Brazil and Colombia (South America (SA))
10.6 Conclusion
References
Chapter 11: Remote Sensing Drought Watch and Food Security
11.1 Introduction
11.2 Drought as Natural Disaster
11.3 What Is Drought?
11.3.1 Drought Features
11.3.2 Measuring Drought
11.3.3 Drought Types
11.4 Drought Detection and Monitoring Methods
11.4.1 Meteorological Methods
11.4.2 Soil Moisture Methods
11.4.3 Satellite-Derived Methods
11.5 Vegetation Health-Based Droughts: Past to Present
11.6 Droughts at 0.5 and 1 km2 Resolution from NOAA/VIIRS
11.7 Devastating Droughts in 2017 and 2018
11.8 Drought, Food Insecurity, and Hunger in Africa
11.9 Unusual 2021 Droughts
11.10 Conclusions
References
Chapter 12: Has Drought Intensified During 1981–2021 Global Warming?
12.1 Introduction
12.2 Global Warming and Droughts
12.3 How to Measure Drought from NOAA/POES?
12.4 41-Year (1981–2021) Drought Dynamics
12.4.1 Thermal Vegetations Stress and Drought Dynamics During 1981–2021 Global Warming
World and Hemispheres
Countries
12.4.2 Dynamics of Moisture Vegetation Stress During 1981–2021 Global Warming
12.5 Conclusion
References
Chapter 13: Summary
Index
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Felix Kogan

Remote Sensing Land Surface Changes The 1981-2020 Intensive Global Warming

Remote Sensing Land Surface Changes

Felix Kogan

Remote Sensing Land Surface Changes The 1981-2020 Intensive Global Warming

Felix Kogan National Oceanic and Atmospheric Administration Rockville, MD, USA

ISBN 978-3-030-96809-0    ISBN 978-3-030-96810-6 (eBook) https://doi.org/10.1007/978-3-030-96810-6 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, 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 publisher, 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 publisher 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 publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Contents

1 Why This Book? ��������������������������������������������������������������������������������������    1 1.1 Land Changes Due to Global Warming��������������������������������������������    1 1.2 Living on Warmer Land��������������������������������������������������������������������    4 1.3 The Goals of the Book����������������������������������������������������������������������   10 1.4 Book Composition����������������������������������������������������������������������������   12 1.5 Short Summary ��������������������������������������������������������������������������������   17 References��������������������������������������������������������������������������������������������������   18 2 Global  Warming Impacts on Earth Systems ����������������������������������������   21 2.1 Introduction��������������������������������������������������������������������������������������   21 2.2 Global Temperature and Anomalies for Climate Studies������������������   25 2.2.1 Development and Accuracy of the Global TA Time Series and UN-Based IPCC Activities����������������������������������   26 2.2.2 Land, Ocean, and Global Temperature Anomalies from NOAA��������������������������������������������������������������������������   39 2.3 IPCC Program: Global Warming and Impacts on Earth ������������������   44 2.3.1 Global Warming and IPCC-Based Earth/Land Changes������   47 2.4 Conclusion����������������������������������������������������������������������������������������   59 References��������������������������������������������������������������������������������������������������   61 3 The  IPCC Reports on Global Warming and Land Changes ��������������   67 3.1 Introduction��������������������������������������������������������������������������������������   67 3.2 Climate Warming and Land Changes from the IPCC Reports ��������   69 3.2.1 Land Changes�����������������������������������������������������������������������   69 3.2.2 Temperature��������������������������������������������������������������������������   70 3.2.3 Land Degradation and Desertification����������������������������������   70 3.2.4 Food Security������������������������������������������������������������������������   72 3.2.5 General IPCC Statements and Brief Comments ������������������   73 3.2.6 The Statements����������������������������������������������������������������������   73 3.3 Evaluation of the IPCC Statements��������������������������������������������������   75 3.4 Summary ������������������������������������������������������������������������������������������   77 References��������������������������������������������������������������������������������������������������   78 v

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4 NOAA  Operational Environmental Satellites for Earth Monitoring������������������������������������������������������������������������������������������������   81 4.1 Introduction��������������������������������������������������������������������������������������   81 4.2 NOAA Operational Polar-Orbiting Environmental Satellites (POES)����������������������������������������������������������������������������������������������   82 4.2.1 AVHRR Sensor ��������������������������������������������������������������������   83 4.2.2 AVHRR Data for Vegetation Monitoring������������������������������   84 4.2.3 Initial Algorithm for Data Collection������������������������������������   85 4.2.4 Normalized Difference Vegetation Index and Brightness Temperature��������������������������������������������������������������������������   88 4.2.5 Removing Noise from NDVI and BT ����������������������������������   91 4.2.6 VIIRS Data for Vegetation Monitoring��������������������������������  106 4.2.7 Continuity of NOAA/AVHRR, S-NPP/VIIRS, and NOAA-20/VIIRS Data Records������������������������������������  110 4.3 Conclusion����������������������������������������������������������������������������������������  114 References��������������������������������������������������������������������������������������������������  115 5 New  Remote Sensing Vegetation Health Technology����������������������������  121 5.1 Introduction��������������������������������������������������������������������������������������  121 5.2 What Is Vegetation Health?��������������������������������������������������������������  122 5.3 Theoretical Base of Vegetation Health Method��������������������������������  123 5.3.1 Biophysical Considerations��������������������������������������������������  124 5.3.2 Basic Laws for Extracting Weather Component from NDVI and BT ��������������������������������������������������������������  125 5.4 Renewed Vegetation Health Algorithm��������������������������������������������  126 5.5 Vegetation Health at Work����������������������������������������������������������������  133 5.6 Validation������������������������������������������������������������������������������������������  137 5.7 Conclusion����������������������������������������������������������������������������������������  145 References��������������������������������������������������������������������������������������������������  146 6 Causes of Climate Warming��������������������������������������������������������������������  149 6.1 Introduction��������������������������������������������������������������������������������������  149 6.2 Global Warming and Major Earth Changes��������������������������������������  151 6.3 What Is Controlling Global Warming? ��������������������������������������������  154 6.3.1 Climate System ��������������������������������������������������������������������  154 6.3.2 CO2 and Global Warming ����������������������������������������������������  155 6.3.3 CO2–TA Match: New Analysis ��������������������������������������������  159 6.4 New Ideas About the Causes of Global Warming����������������������������  163 6.4.1 Warming Due to Ozone Depletion����������������������������������������  163 6.4.2 Earth Climate and Milankovitch Cycle��������������������������������  166 6.4.3 Milankovitch-Based Precession Cycle ��������������������������������  168 6.5 Summary ������������������������������������������������������������������������������������������  170 References��������������������������������������������������������������������������������������������������  173

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7 Land  Cover Changes from Intensive Climate Warming����������������������  181 7.1 Introduction��������������������������������������������������������������������������������������  181 7.1.1 General Statements ��������������������������������������������������������������  181 7.1.2 NOAA Satellites, Used for This Analysis����������������������������  182 7.2 Land Cover Temperature������������������������������������������������������������������  184 7.2.1 Global-Regional Land Cover Temperature (SMT) ��������������  185 7.3 Land Cover Greenness����������������������������������������������������������������������  201 7.3.1 World and Hemispheres��������������������������������������������������������  202 7.3.2 China, the USA, and India����������������������������������������������������  203 7.3.3 Brazil, Indonesia, Russia������������������������������������������������������  204 7.3.4 Argentina, Ukraine, France, Canada������������������������������������  205 7.3.5 Other Countries��������������������������������������������������������������������  207 7.4 Summary ������������������������������������������������������������������������������������������  209 References��������������������������������������������������������������������������������������������������  211 8 Global  Warming Crop Yield and Food Security ����������������������������������  217 8.1 Introduction��������������������������������������������������������������������������������������  217 8.2 Modeling Principles��������������������������������������������������������������������������  219 8.2.1 Yield Time Series������������������������������������������������������������������  219 8.2.2 Vegetation Health Indices ����������������������������������������������������  220 8.2.3 Yield-Vegetation Health Models������������������������������������������  221 8.3 Yield-Vegetation Health Models������������������������������������������������������  223 8.3.1 Global Grain and Food Security ������������������������������������������  223 8.3.2 Corn in China������������������������������������������������������������������������  223 8.3.3 Winter Wheat, Corn, and Sorghum in the USA��������������������  227 8.3.4 Winter Wheat in Ukraine������������������������������������������������������  234 8.3.5 Corn in Argentina������������������������������������������������������������������  236 8.3.6 Wheat in Australia����������������������������������������������������������������  240 8.3.7 Rice in Bangladesh ��������������������������������������������������������������  245 8.3.8 Cereals in Russia������������������������������������������������������������������  248 8.3.9 Spring Wheat in Kazakhstan������������������������������������������������  254 8.3.10 Corn in Zimbabwe����������������������������������������������������������������  258 8.3.11 Other Countries and Crops���������������������������������������������������  262 8.3.12 VH-crop Modeling for Food Security: Concluding Remarks��������������������������������������������������������������������������������  269 8.4 Short Summary ��������������������������������������������������������������������������������  271 References��������������������������������������������������������������������������������������������������  271 9 Remote  Sensing Malaria During Global Warming������������������������������  277 9.1 Introduction��������������������������������������������������������������������������������������  277 9.2 Modeling Principles��������������������������������������������������������������������������  278 9.2.1 Malaria’s Multiyear Time Series������������������������������������������  280 9.2.2 VHI Applied to Malaria��������������������������������������������������������  282

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9.3 Malaria-VH Models��������������������������������������������������������������������������  284 9.3.1 Southeast Asia����������������������������������������������������������������������  284 9.3.2 Africa������������������������������������������������������������������������������������  319 9.3.3 South America����������������������������������������������������������������������  325 9.4 Summary ������������������������������������������������������������������������������������������  327 References��������������������������������������������������������������������������������������������������  328 10 Malaria  Performance Trend During 1981–2020 Global Warming������  333 10.1 Introduction������������������������������������������������������������������������������������  333 10.2 Earth Climate Warming and Consequences������������������������������������  335 10.3 Strong Global Warming During 2015–2018 ����������������������������������  337 10.4 Global and Continental Malaria Activities, Assessed from 1981 to 2018 Satellite-Based Moisture-Thermal Characteristics��������������������������������������������������������������������������������  339 10.4.1 Malaria Activities Assessed Form Vegetation Greenness and Temperature��������������������������������������������  340 10.4.2 Vegetation Health Indices as the Indicators of Malaria activities ��������������������������������������������������������  344 10.4.3 High Malaria (HM) and Low Malaria (LM), Assessed from Vegetation Health Indices������������������������  345 10.4.4 Percent Global Malaria Area with HM and LM from the 1981–2018 Moisture-Thermal Index (VHI) ����  345 10.4.5 Percent Global Malaria Area with HM and LM from the 1981–2018 Moisture (VCI) and Thermal (TCI) Indices������������������������������������������������������������������������������  346 10.4.6 Percent Continental (South America, Africa and Southeast Asia) Malaria Area with HM and LM from 1981 to 2018 Thermal (TCI) and Moisture (VCI) Conditions During Climate Warming������������������������������  348 10.5 Percent Malaria Endemic Area with HM and LM (Assessed from 1981 to 2019 Moisture (VCI) and Thermal (TCI) Vegetation Condition) in the Most Malaria-Affected Countries During 1981–2019 Global Warming������������������������������������������������������������������������������  353 10.5.1 Brazil and Colombia (South America (SA)) ������������������  354 10.6 Conclusion��������������������������������������������������������������������������������������  364 References��������������������������������������������������������������������������������������������������  366 11 Remote  Sensing Drought Watch and Food Security����������������������������  373 11.1 Introduction������������������������������������������������������������������������������������  373 11.2 Drought as Natural Disaster������������������������������������������������������������  374 11.3 What Is Drought?����������������������������������������������������������������������������  375 11.3.1 Drought Features ������������������������������������������������������������  377 11.3.2 Measuring Drought����������������������������������������������������������  377 11.3.3 Drought Types ����������������������������������������������������������������  378

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11.4 Drought Detection and Monitoring Methods����������������������������������  379 11.4.1 Meteorological Methods��������������������������������������������������  379 11.4.2 Soil Moisture Methods����������������������������������������������������  381 11.4.3 Satellite-Derived Methods ����������������������������������������������  382 11.5 Vegetation Health-Based Droughts: Past to Present ����������������������  390 11.6 Droughts at 0.5 and 1 km2 Resolution from NOAA/VIIRS������������  405 11.7 Devastating Droughts in 2017 and 2018����������������������������������������  412 11.8 Drought, Food Insecurity, and Hunger in Africa����������������������������  414 11.9 Unusual 2021 Droughts������������������������������������������������������������������  415 11.10 Conclusions������������������������������������������������������������������������������������  418 References��������������������������������������������������������������������������������������������������  419 12 Has  Drought Intensified During 1981–2021 Global Warming?����������  425 12.1 Introduction������������������������������������������������������������������������������������  425 12.2 Global Warming and Droughts ������������������������������������������������������  427 12.3 How to Measure Drought from NOAA/POES?������������������������������  429 12.4 41-Year (1981–2021) Drought Dynamics��������������������������������������  430 12.4.1 Thermal Vegetations Stress and Drought Dynamics During 1981–2021 Global Warming ������������������������������  431 12.4.2 Dynamics of Moisture Vegetation Stress During 1981–2021 Global Warming��������������������������������������������  444 12.5 Conclusion��������������������������������������������������������������������������������������  445 References��������������������������������������������������������������������������������������������������  446 13 Summary��������������������������������������������������������������������������������������������������  449 Index������������������������������������������������������������������������������������������������������������������  453

Chapter 1

Why This Book?

1.1 Land Changes Due to Global Warming This Book is studying numerical land changes due to an intensive global warming. The recent climate warming has affected the entire earth. Why the major focus of the Book is on land? Land is the only earth system supporting people’s living. Land area is not big, occupying 148.3  million  km2 or 29% of the total earth surface (510.1 million km2). Although the land is 2.4 times smaller than ocean, nearly 80% of Earth’s species live on land and 5% are living in land’s freshwater (IGBP 2020). The rest 15% species are remaining in the ocean. The most important land’s goals are supporting living 7.8 billion people. Considering the size of land (excluding two Poles) and assuming uniform population distribution, each land’s 1 km2 contains 50 people. Meanwhile, people are distributed not uniformly. Nearly two-thirds of the world’s population lives in Asia, with nearly 2.7 billion in the two countries, China and India. Supporting currently the living of 7.8 billion earth population, and having relatively limited land’s resources, any deviations of land conditions from the established over many years might produce negative impacts on land resources and population living. Such strong deviations of the conditions have been currently created by the global warming, which is affecting the entire earth and especially land. Earth climate has been warming up since the mid-eighteenth century (IPCC 2007, 2014, 2018a, b, 2019a, b, c, d, e, f, g, h). This process has intensified, from the late-­1970s, and by the turn of the twentieth century, global temperature anomaly (TA) increased by nearly 0.9 °C (over the preindustrial time (1850–1900) (IPCC 2007, 2014, 2019b). Such a strong increase in global temperature anomaly (TA) has been leading to quite unusual changes in Earth and specifically land environmental, economic, and social events (IPCC 2014, 2019d).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 F. Kogan, Remote Sensing Land Surface Changes, https://doi.org/10.1007/978-3-030-96810-6_1

1

2

1  Why This Book?

An intensive climate warming has been reported to: speed up ice melting in the Northern Pole, sea level rise, reduction of global snow, increase water deficit, intensify natural disasters, change biological components of earth systems, and produce other earth changes (IPCC 2014). The strongest global warming affected earth in the recent 41-year (1981–2021) impacting severely the land, where we are living. One of the strongest global warming impacts on land and the quality of human life is intensification of hot weather, lack of water, drought expansion and intensification, increase in natural disasters (tornadoes, hurricanes, cyclones, etc.), spreading weather-related diseases (malaria) and insects (locust) and causing other environmental problems, and deteriorating human living. From the indicated events, drought intensification and expansion since 1980 has been the leading phenomenon stimulating frequent reduction of agricultural production, leading to a lack of food for almost half of the world population and even hunger in the developing countries of Africa, Southeast Asia, and South America. Experts from the United Nations, Governments, and even scientists are warning that continuation of climate warming (especially, expected 2.5 °C global TA increase by the end of this century) would lead to considerable shortages of water on land, strong drought intensification and expansion, affecting more than 70% of the major crop area, and considerable reduction of crop production, especially in the developing countries. All these climate impacts events are expected to deteriorate land conditions and human living. People on land will suffer from considerable shortages of agricultural production and a lack of food, leading to hunger intensification for almost half of the earth population. All of these problems would deteriorate food security for the entire land, increasing the number of affected people (IPCC 2018a, b, 2019a, b, c, d, e). Why Land, if most of the Earth’s surface is ocean, which is extremely important for Earth system? Ocean occupies 71% (361.8  million  km2) of Earth surface. It contains nearly 97% of the Earth water, although salted, but useful for many activities. The top 10 ft of ocean’s water hold as much heat as our entire atmosphere. This heat is strongly affecting earth climate, changing also conditions of land surface. Ocean carries a very important economic task, providing more than 90% of the trade between the countries (carried out by ships) and about half of the communications between nations using underwater cables. Another important ocean task is fish supplies, which is very popular as a source of protein for the world. Meanwhile, fish and other ocean products are quite limited for the world population (Tables 1.1 and 1.2). Only people living within 40–60 km from the ocean shore (less than 0.1% of earth population) are using ocean products as the main source of food. In 20 years, the number of people using ocean food is expected to double. But there is currently a trend towards reduction of ocean products use and gradual switching to grain’s and animal’s protein, since ocean is extremely polluted, 80% of which comes from the land’s activities (IPCC 2012, 2019a, b, c).

1.1  Land Changes Due to Global Warming

3

Table 1.1  Food provided by land and water for the Earth population (Ritchie 2017; FAO 2006a, b, c) Group Land

Type Agriculture Livestock Aquatic Cultured harvest

Wild harvest

Fields All Meet Freshwater animals Marine animals Marine plants Fisheries Aquatic plants

Million metric tons 7000 548 26

Growth rate 1994–2004 (%/ year) 2.0 2.6 7.3

20 14 96 1.4

7.4 7.5 0.1 0.5

Table 1.2  Summary of Table 1.1: Land and Aquatic harvest in MMT and % of the total Group Land total Aquatic total Total (land and aquatic)

Million metric tons (MMT) 7548.0 157.4 7805.4

% of the total 98 2 100

Still, why are we focusing on land? The answer is very simple: 1. We are living on land. 2. Land supports currently existence of nearly 7.8 billion people. 3. By the 2050s, land is expected to have 9.7  billion people and provide some support. 4. By the 2100, land is expected to have 11.2 billion people and provide limited support. Supporting the life of such a huge number of people would exhaust a very limited land resources, considering current and expected strong global warming. Therefore, it is important to evaluate the available land resources, concentrating on land limitations for humans’ existence, and assess what should be done to save land profitability, considering an intensively growing population, strong climate warming, and a lack of agricultural production. First of all, unlike ocean uniformity, the land use is limited by its ecosystems, which are reducing land habitability to minimum. Only 71% (104 million km2) of land is habitable (excluded are deserts, tropical forests, some mid-latitude forests, glaciers, and a few other smaller areas). Agriculture is more restricted, occupying 50% (51 million km2) of land area. Forest, which is also used for food production, is occupying 37% (39 million km2) of land area. The unused land areas are glaciers 10% (15 million km2) and 19% (28 million km2) barren land (IPCC 2019c).

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1  Why This Book?

From all Earth systems, land is one providing principal food supplies for people (ocean is providing food for 0.1% of Earth population). Also, land provides dwelling, work, climate/weather resources, and intensive socioeconomic activities. Food-­ wise, land provides 83% of global calorie supplies and 63% global protein supplies (IPCC 2019b, c, d). The food is the number one component of land’s support for human life (Tables 1.1 and 1.2). The Table 1.1 is estimating some details on different sources of food availability, from Land and Aquatic. Summarizing Table 1.1 into Table 1.2, it is possible to state firmly that the 7548 million metric tons of land food come from agriculture and livestock. They provide 98% of foods for the current, nearly 7.8  billion people, living currently on land (WorldInTheData 2020). The aquatic source of food provides only 2% of the population feeding, which is coming completely from ocean (Table 1.2). Unfortunately, land’s food (agriculture, livestock) is generally growing three-­ time slower (last column in Table 1.1) than wild harvest from ocean and fresh water. Meanwhile, considering that land is the principal food supplies, but slow-growing, it is possible that in the next 30-year (by the 2050), when the earth population is supposed to increase close to nine billion, this food amount might be deficient. Moreover, by the end of the twenty-first century, it is expected that the amount of food from land is supposed to be more deficient, although the crops and grazing lands have currently been increasing (Fig. 1.1a, Ritchie and Roser 2019). Following Fig. 1.1a, crops and grazing land areas have been stable before 1000 and mid-1800. After year 1000, both areas have increased slightly, but were stable in the next 130–150  years at the level of nearly 0.25  billion  ha for crops and 0.7–0.9 billion  ha for grazing land. The main increases in crop and grazing land areas have been initiated close to the nineteenth century and intensified strongly until the early twenty-first century. Following Fig. 1.1b, during the period of over the 3-time earth population increase (from around 2–6.8 billion), crop and grazing land areas increased strongly from 0.25 to 1.5 billion ha and from 1.0 to nearly 5 billion ha (both nearly 5 times), respectively. Meanwhile, Fig. 1.1a also indicates that from the late twentieth to the early twenty-first centuries, increase in crop and grazing land areas has slowed down considerably, indicating that the productive land resources have been gradually exhausting (probably from negative climate warming impacts). Summarizing this analysis, it should be emphasized that population increase has stimulated crop and grazing land areas growth prior to twenty-first century, but strong slowdown of this growth in the early twenty-first century.

1.2 Living on Warmer Land Life on land can be considered from a few points of views: 1. Available land resources, supporting food security. 2. Land changes from intensive climate warming. 3. The number of people to support living on land.

1.2  Living on Warmer Land

5

Fig. 1.1 (a) Dynamics of crop and grazing land areas (million ha) during 500–2016 and (b) the world population dynamics after 1500 and predictions until the end of the current century

Following the available land resources, land provides the main basis for human’s livelihoods and well-being, including food, freshwater, energy, dwelling, work, multiple services (from agriculture to forestry), and socioeconomic activities. Land is playing a key role in the exchange of energy, water and food supplies, greenhouse gases (GHG), and pollution. The amount of land resources together with the provided technology and sustainable land management are contributing to a reduction of the negative impacts of multiple stressors, including climate change impacts on ecosystems, available water, energy, environment, and human life (BerekelyEarth 2020; HadCRU 2020; NOAA 2020; NASA/GISS 2020; IPCC 2007, 2014, 2018a, b, 2019a, b, c). Land-living experience has been showing that people are using not more than one third of land’s potential net primary production for food, feed, fiber, timber, and energy. Unfortunately, it is impossible to use more than one third, because 33% of global land area is desert, 10% is polar regions, 13% is cryosphere, and 31% is heavy forest (HadCRU 2020). Meanwhile, it should be emphasized that the limited land resources have currently supported ecosystems’ functioning, agriculture, grazing land, and food security for a decent people’s living.

6

1  Why This Book?

Meanwhile, in the recent 40 years, an intensive climate warming and global population increase have caused unprecedented use of land’s resources: freshwater, food, feed, fiber, timber, and the total land’s energy (IPCC 2007, 2014, 2018a, b, 2019b, c, d). The worth situation is with agriculture, which has currently consumed 70% of global fresh water. Further efforts of increasing agricultural production are leading to a considerable deterioration of natural ecosystems, including wetlands, declining water resources, and biodiversity. In addition, an exhaustion of the land’s natural resource, due to the growing population and a very intensive climate warming, has deteriorated land surface conditions. Figure 1.2 investigates: (1) How much the global climate warmed up? and (2) How much this warming increased global land surface temperature? The annual mean temperature anomaly (TA) data have started in 1850 and were expressed relative to the average temperature during 1850–1900, which is the preindustrial time temperature. Following this diagram, the annual TA of both global surfaces (ocean and land together, and land only) have started to increase in the early 1900s, from near 0.1  °C for global ocean and land and 0.25  °C for land TA.  Even negligible initial TA increase showed that land was 2.5 times warmer than the global (two surfaces together). During approximately 120 years (from the end of the eighteenth century to the 2018), the global TA increased approximately from 0.1 to 1.0 °C and the land TA increased from 0.25 to 1.75 °C. Therefore, the global land has been warming stronger: 1.5 °C versus 0.9 °C (ocean and land). An interesting fact, when global warming intensified from the early 1990s, the difference between global TA and land TA is gradually increasing, while the time is going by (the two trend lines are expending, approaching to 2018). In other words, land is accumulating more heat, when global TA is exceeding 0.5 °C (around mid-1980s). Summarizing this discussion, we should emphasize that by the 2018, land TA and global TA have reached approximately 1.75 and 0.9  °C.  And these TA are expecting to increase after 2018.

Fig. 1.2 Annual temperature anomaly (TA) global (ocean and land) and land only during 1850–2018 (IPCC 2019d)

1.2  Living on Warmer Land

7

The expected continuation of global warming (IPCC 2019d, e) will be strongly increasing land temperature, deteriorating land environment, reducing land productivity, and worthening living conditions. Besides, heat-related events have enhanced desertification and land degradation in Africa, Southeast Asia, and some areas of Australia since the late 1890s (NOAA 2020; NASA/GISS 2020; IPCC 2007, 2014, 2018a, b, 2019a, b, c). A very unpleasant fact is that an intensive land warming is expecting to intensify water and thermal stress of crops and pasture, intensify and expand droughts, reduce agricultural production, and worthen food security. Knowing an intensity of global warming (IPCC 2019b, c, d) and much stronger land heating (Fig. 1.2), we investigated: how much an intensively warm land from 1960 has deteriorated land resource and land productivity, negatively affecting agriculture, food security, and population living? Figure 1.3a shows that the areas of major crops (cereals and coarse grain) and secondary crops (pulses, vegetables, and a few others) in the past 55-year (since 1961) remain stable. This indicates that land resource for expanding crop areas has been exhausted. Opposite to crop areas, the multi-decadal of major cereal crops (wheat, rice and corn) has currently increasing trends (Fig.  1.3b), indicating agricultural yield growth and global food security stimulation since 1960s.

Fig. 1.3  Time series of (a) global crops’ area, (b) global crops’ yield, (c) global population, and (d) crops yield of European and Asian countries

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1  Why This Book?

The 1961–2005 yield increase has been stimulated by the advances in agricultural technology (fertilizers, irrigation, diseases and insects’ control, agricultural management, etc.), developed after the World War-2 (Kogan 2018). Important, that during 1961–2005, an intensity of yield increase for major grain crops (130–200%) has corresponded to an intensive population growth (130%, Table 1.3, Fig. 1.3c). Only corn yield advanced faster, since the new corn technology in the past 30-year has provided much faster corn yield growth. Following this discussion, it is possible to conclude that in the past 50 years, an intensive land warming has little affected crop yield and food security, because the land has still had some resource supported by the advanced agricultural technology (Kogan 2018). Meanwhile, since the end of the twentieth century, world food security situation has deteriorated, when the global yields of the major grain crops (wheat, rice, corn, Fig.  1.3b) have started leveling off, indicating stagnation of global and countries yields (Kogan 2018). Following Fig. 1.3d, grain yield stagnation is also going on in the major European (maize, wheat) and Asian (rice) countries (Fig. 1.3d). The scientific literature indicates that in Africa, the yield-stagnated food security deterioration has initiated in the 1980s, when the average per capita food production has been consistently falling down for the past 40-year, with bad consequences for a very high-level poverty, particularly in rural areas. Yield stagnation (leveling off trend) is normally stimulated by the two major factors (a) lack of agricultural technology and (b) climate change (warming). Following numerous publications, agricultural technology (fertilizers, insects-diseases control irrigation, management, etc.) has strongly intensified crops’ yield growth since the 1950s. Considerable investments in agricultural technology during 1950–1970 have stimulated yield increase for 20–35 years. Meanwhile the agricultural technology has gradually deteriorated (lack of water specifically), causing crop yield leveling off (Kogan 2018). Besides agricultural technology, yield stagnation was also stimulated by an intensive land surface temperature increase. It is generally hard to find the appropriate data to prove this statement. Meanwhile, Fig.  1.4 is showing contribution of strong land warming to wheat yield changes in Nigeria. When mean country temperature was changing negligibly (from 26.1 to 26.2 °C) during 1950–1960, country’s wheat production was relatively stable (around 18 ton). But after several years of mean temperature increase to 27.1–27.5 °C, wheat production has started to jump

Table 1.3  Global crop yields and population growth during 1961–2005 Item Wheat (T/ha) Rice (T/ha) Corn (T/ha) Population (billion)

1961 1.2 1.5 1.6 3.4

2005 2.8 3.6 4.9 7.7

% Increase 130 140 200 130

1.2  Living on Warmer Land

9

up and down reacting to changes in precipitation and drought. Following this diagram, climate/weather factors are important not only for the year-to-year weather fluctuations in crop yield, but also for the long-term climate change. “Living on Warm Land” discussion was focused primarily on leveling off yield and deterioration of food security, which is the most important Earth problem, “How to provide decent food supplies for the growing earth population?” 1. Since the late 1940s (after the World War-2), these efforts have been successful, since the advances in agricultural technology have stimulated crop yield growth (130–200% during 1961–late 1980s) to satisfy identical population increase (130%). But this success has been temporary. During the recent 35–40  years, land resources have been gradually exhausting, because: (1) Grain crops areas could not be expanded anymore (Fig. 1.3a), since all good lands have already been used in agriculture; (2) Since the 1980s, gradual slowdown of agricultural technology (water limitation, exhaustion of soil quality, economic problems, lack of managements, etc.) has caused grain yields’ gradual stagnation (leveling off yield time series after the 1980s, Fig.  1.3b, d). (3) An intensive global warming since the mid-1980s has strongly increased global land surface TA to 1.58–1.83  °C during 20-year from 1997 through 2017 (Fig. 1.2). Such an intensive land warming has contributed to stagnation (leveling off) of cereal crops yield. So, yield stagnation (global and major

Fig. 1.4  Mean Nigeria temperature during 1901–2005 (a) and (b) total Nigeria wheat production during 1961–2017. The equation approximates sick line trend (1901–2005). Thin lines are showing two types of temperature trends (slow temperature increase during 1901–1968 and intensive temperature increase during 1969–2005)

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1  Why This Book?

grain countries) due to the strongest land warming and slowdown of agricultural technology has deteriorated food security, causing shortages of food and hunger in the developing countries, affecting almost one half of the world population.

1.3 The Goals of the Book The goals of this Book have been developed considering, first of all, an intensive climate warming and its adverse impacts on earth, land, and humans (IPCC 2007, 2014, 2018a, b, 2019b, c). Second, the goals were also stimulated by a huge disbalance between food supply and demand in the recent 3–4 decades. The problem is that the rate of agricultural production growth is behind the population increase rate (Kogan 2018). Population growth is projected to increase nearly 30% over the next three decades and nearly 55% by the end of this century (Roser 2019). Third, such intensive population growth in the presence of global warming, yield leveling off, and a very intensive land cover stress is requiring considerable amount of additional food, energy, and water, creating huge challenges the world is facing today. Other detrimental consequences of global climate warming for agriculture are strong land surface warming and intensifying and expanding droughts (IPCC 2019b, c). In these regards, one of the biggest socioeconomic concerns of the impacts is how, in the recent 40–50  years, strong global warming has changed land cover, since these changes are additional impacts blamed for gradual levelling off agricultural production trends, stronger reduction of crop yields, and pasture deterioration. The decrease in agricultural production is leading to population malnutrition and even hunger in the developing countries. Another very important aspect of studying global climate warming is what to expect in the near and distant future: will these negative land cover changes and trends continue further deterioration of agriculture, leading to more people suffering from a lack of food and hunger? This is a very important concern since in the recent half a century, earth population has been increasing much faster than food production growth. The most affected are developing countries of Africa, South-East Asia, and Latin America. Most scientific and social publications, discussing climate warming and its consequences, are based on analysis of mostly weather-type observations (IPCC 2007, 2012, 2014, 2018a, b, 2019a, b, c, d, e, f). One of the biggest problems with using these observations for analysis of land condition is limited amount of land observing stations. Although following, there are over 10,000 manned and automatic weather stations, 1000 upper air stations, 7000 ships, 1000 drifting buys, and some radars. Meanwhile, for high-resolution analysis of land conditions, this number of stations is very limited, especially, in Africa, Asia, and South America. Even in the USA, with well-developed weather stations network, each station is available for a very large area. For example, there are 274 weather stations in California for the area of 450,000 km2. On the average, each station covers nearly 1500 km2. Much

1.3  The Goals of the Book

11

worth situation is in Africa, where each weather station covers (on the average) from 10,000 to 30,000 km2. Therefore, land cover data and comprehensive analysis, presented in this Book, are based on the data obtained from NOAA operational polar-orbiting satellites (NOAA/OSDP 2021). Currently, 40  years (since 1981) of global high-resolution (both temporal (weekly) and spatial (1 and 4 km2)) land surface satellite data have been accumulated. Moreover, special technology, called Vegetation Health (VH), has been developed for estimation of land’s moisture, thermal, and combine conditions (NOAA/NESDIS 2021). The VH data are frequently used for land cover change analysis. Specific attention will be devoted to 40-year trend analysis of global, hemispheric, countries, and even one or few pixels areas, investigating land’s temperature, moisture, droughts, vegetation greenness, stress, and other land characteristics and if their trends are matching with global warming trend. The presented earth challenges and problems are summarized in Table  1.4 and will be discussed in the book.

Table 1.4 Global land’s environmental and socioeconomic challenges and problems (BerekelyEarth 2020; IPCC 2007, 2012, 2014, 2018a, b, 2019a, b, c, d, e, f) Problems and challenges Intensive earth population growth Strong warming of global climate and land since the 1980s Declining stock of land’s natural resources (water, soil, forest, withdrawal for real-estate) Intensification of land degradation (desertification, deforestation, weather extremes) Current and future climate constraints Food growth is lacking population increase Leveling off yield of the major grain crops in the recent 2–3 decades Unbalance food supply and demands Land surface temperature anomaly (TA) is twice warmer than the global (ocean and land) TA Climate warming reduced water, increased soil erosion and vegetation loss CO2, released by human activities, is causing global warming Increased demand for food, feed, and water (due to increase in population, income and food consumption Agricultural losses Drought intensification and expansion Lack of agricultural production to feed the entire earth population Limited adaptation strategies Nearly 800 million hungry people in the developing countries Intensification of mosquitoes-borne diseases, insects, and crops diseases Intensification of annual yield variations due to weather fluctuation Land degradation impacts on climate

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1  Why This Book?

1.4 Book Composition This book contains 13for. Their short description is presented below. Chapter 1: Why This Book? There are two reasons for writing the Book: (a) strong climate warming and (b) considerable land cover changes with strong impacts on food availability. The global climate has warmed up strongly in the past 40–50 years. What happened with both environmental and Earth, when the global temperature anomaly (TA) increased nearly 0.9 °C (relative to T during the preindustrial time (1850–1900)). All earth systems were severely affected by global T increase, including ice melting, sea level raise, global snow reduction, intensification of natural disasters, etc. Global warming has strongly increased land’s TA up to 1.75 °C (over preindustrial time T). Such high temperature has intensified evaporation, increasing water deficit on land, expended and intensified droughts, and increased vegetation stress (both moisture and thermal). These events have led to a reduction of agricultural production (IPCC 2019b). Currently, nearly 30% of land population have been already suffering from global warming. This number is expected to increase, considering that global TA might raise to 1.5 °C or even to 2.0 °C by the end of this century and the earth population would increase by that time to nearly ten billion people (IPCC 2019d, e). Chapter 2: Global Warming Impacts on Earth Systems Over the long Earth history, climate has been changing many times from warm to cold and back to warm, etc. For example, between 100,000 and 15,000 years ago, the Earth climate has changed from warm to ice age and back nearly 25 times. These changes have been estimated approximately with “temperature proxies”. The current climate warming, which has continued since 1850, has produced strong changes in earth systems, such as ice melting, ocean level rise, intensification of natural disasters, and other changes. These and other changes need to be assessed numerically for modeling how to deal with current and future climate warming dynamics and land changes, where we are living. Following these goals, world management, international organization, and climate communities have introduced two general activities. Development of: (a) multiyear numerical records of global annual temperature anomaly (TA) and (b) International Panel on Climate Change (IPCC). Following the first goal, 170-year TA records have been developed by five respectful climate groups. The IPCC Program was organized by the UN-based WMO and UNEP with the goals to summarize climate research from 1000 published papers and present them in the Reports, understandable to governments and decision makers. The numerical assessments of global warming and impacts on earth have been presented in these two programs. Chapter 3: The IPCC Reports on Global Warming and Land Changes In the recent 40–50 years, land changes have attracted serious attention by the world community, since, in addition to global TA increase (around 1.1 °C above preindustrial time (1850–1900) average temperature, IPCC 2021), global land surface TA has twice exceeded the global (ocean and land) TA, reaching around 1.75 °C (above preindustrial time average temperature). An extremely high land surface

1.4  Book Composition

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temperatures have degraded land ecosystem and soils, intensified and expanded droughts, reduced water availability, intensified thermal stress of vegetation, decreased agricultural production, causing shortages of food and hunger in the developing countries (IPCC 2007, 2014, 2018a, b, 2019b, c, d, e, 2021). The IPCC Reports have analyzed land changes under an intensive climate warming. Meanwhile, the produced assessments were mostly qualitative (“land degraded,” “desert expanded,” “drought intensified”), while for assessment of land changes we need qualitative assessments in order to evaluate deterioration of the growing land population’s life. Chapter 4: NOAA Operational Environmental Satellites for Earth Monitoring This Chapter describes the NOAA operational afternoon polar-orbiting satellites, their operations, measurements, and data. From 1981, they were used for measuring land cover characteristics and their 40-year dynamics. Two operational satellite systems, geostationary (GOES) and polar-orbiting (POES), were developed to observe the Earth (ocean, atmosphere, cryosphere, and land), for modelling and predicting environmental impacts on earth, economy, and human life. If the GOES system was used effectively for weather analysis and prediction, the POES system was applied for monitoring Earth cover and atmosphere near the ground. In order that the readers and data users be confident in satellite-based land cover measurements and analysis, this chapter describes a very comprehensive procedure for POES data collection and processing (especially noise removal, sensor adjustment, and others). During the 40-year, the three NOAA operational polar-orbiting satellite systems were used: initial—NOAA/AVHRR, intermediate—SNPP/VIIRS, and the new one—JPSS/ VIIRS. Current operational satellite in space is NOAA-20. In the next 30–35 years, the current generation of satellites is planned to continue with the operation of NOAA-21 through NOAA-24. After that, the new system is planned to be developed and used. Chapter 5: New Remote Sensing Vegetation Health Technology The Vegetation Health System is the new remote sensing biophysically based Vegetation Health (VH) method, developed specifically for numerical approximation of environmental impact on land surface, specifically on vegetation, crops, pastures, forests, etc. Following vegetation productivity tests (Kogan 2020, 2018), the VH monitors accurately reaction of vegetation to moisture and thermal conditions. In the other words, VH determines if vegetation is healthy (very productive), normal (mid-productive), or stressed (low-productive). Using VH values, some events and products, such as drought, crop production, fire risk, etc., might be determined. Figure  1.5 shows USA’s Vegetation Health on July 1, 2012 and June 30, 2019 stressed and healthy, correspondingly, vegetation conditions. In mid-summer 2012, USA experienced a very intensive drought (red color, indicating extreme vegetation stress) in the central portion of the country (the principal area of corn), while in 2019, that area has extremely favorable conditions. Following these VH estimates, corn production in 2012 was supposed to be lower than in 2019. The numbers of the US Department of Agriculture indicated that corn production was 10.4 and nearly 14 million bushels in 2012 and 2019, respectively.

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Fig. 1.5  Global 4 km2 resolution Vegetation Health index in mid-summer 2012 and 2019

This chapter is very important in explaining the theoretical and practical principles of VH system. The VH method stems from the properties of green vegetation to reflect sunlight in the visible (VIS) and near infrared (NIR) parts of solar spectrum and emit absorbed solar radiation in infrared (IR) part. From VIS and NIR, Normalized Difference Vegetation Index (NDVI) is calculated (Rose et al. 1973), which characterizes chlorophyll-dependent vegetation greenness and also moisture content. From IR measurements vegetation cover temperature is calculated. Following the biophysical laws, three VH indices were developed: Vegetation Condition Index (VCI), Temperature Condition index (TCI), and Vegetation Health Index (VHI). These indices were used to approximate moisture conditions (VCI), thermal condition (TCI), and total vegetation health (VHI, combining VCI and TCI). These indices have multiple applications, discussed in the following Chapters. Chapter 6: Causes of Climate Warming

1.4  Book Composition

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Over the Earth’s long history, climate has never been settled, since multiple causes were changing it and sometimes in opposite directions. For example, between 100,000 and 15,000 years before present, Earth’s climate changed nearly 25 times from warm to ice age and back. In the relatively recent time, a small ice age, between 1340 and 1700, has switched to warming from the eighteenth century. There are many phenomena controlling climate change. They include combined thermal balance from ocean, atmosphere, and land, atmospheric pressure, land surface albedo, solar activity, the distance between the Earth and the Sun, the angle of Earth’s rotation axes, volcanoes, natural and anthropogenic radiative forcing, human activities, and others. Following IPCC reports, continuous global warming since 1850 is the result of human activities in releasing greenhouse gases (GHG) from burning fuel (coal, wood, oil, etc.), producing cement, etc. The GHGs included CO2, CH4, N2O, and SF6. These gases, specifically CO2, intercept infrared solar radiation emitted from land and send it back to the surface, warming the Earth. Other aspects of climate warming would be also discussed in this chapter, especially in the recent 170 years. This chapter is also discussing the current climate warming views especially since 1980s, when temperature has almost doubled. An important emphasis is on global temperature and CO2 trends and new ideas about the causes of global warming. Chapter 7: Land Cover Changes from Intensive Climate Warming. Since 1988, the IPCC Program has analyzed climate studies by thousands research papers and summarized them in the IPCC Reports to provide this information to the world governments and decision makers (IPCC 2007, 2014, 2018a, b, 2019a, b, c, d, 2020, 2021). These reports provided numerical data showing intensive global and land temperature increase, ice melting, ocean level rise, global snow redaction, and some other events. However, the land has not been evaluated numerically, except global temperature increase. Since earth population is not distributed uniformly over the land, numerical temperature estimation must be done regionally. The IPCC Reports presented some discussions about land degradation, desertification, drought, food security, etc., but only qualitatively (not numerically). For evaluation of land reaction to an intensive global warming, land cover needs to be assessed numerically at global, continental, countries, regions etc. Besides, the IPCC Reports have not assessed changes in land cover greenness, temperature, moisture stress, thermal stress, drought, insect’s invasion, mosquitos’ diseases, and many other unfavorable population events. Chapter 8: Global Warming Crop Yield and Food Security A major world task is to produce enough food to feed Earth’s fast-growing population. Currently, the world population is growing faster than agricultural production. A lack of agricultural production compared to the demands for food is normally intensified in years with weather-related disasters, especially drought. Therefore, weather-driven crop losses have always been a big concern for farmers, traders, governments, policy makers, and international organizations for the purpose of balanced food supply/demands, trade, and distribution of aid to the nations in need, especially in the years with food security problems. Recent tendencies with agricultural production leveling off have not been favorable since almost every other year

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of the twenty-first century has experienced large-scale crop losses mostly due to droughts. Among the different types of agricultural production, grain is a major source of food supply. The amount of grain produced by agriculture depends on yield and planted area. While crop area is relatively stable, yield fluctuates considerably with weather changes from year-to-year. Among weather disasters, drought plays a major role in large-scale crop losses. In the most recent two-three decades, drought-related crop losses have been reported to increase due to climate change. Therefore, it is very important to estimate crop yield in advance of harvest. There are currently two known methods for modeling an advanced estimation of crop yield. These estimates are based on weather variables (precipitation, temperature, soil moisture, weather indices). The new satellite-based vegetation health (VH) method introduced in the 1980s showed very good results for modeling and accurate monitoring crop yield well in advance of harvest. The VH method is working well because the parameters of this method are based on biological laws of characterizing vegetation condition. Besides, these parameters are distributed frequently over space compared to weather data. This chapter introduces yield modeling with operational satellites’ VH indices and provides modeling and validation results for grain crops in major grain producing countries such as US, China, Russia, Argentina, Australia, Ukraine, India, and others. Some examples are also shown for other crops and pasture. Chapter 9: Remote Sensing Malaria During Global Warming Malaria is a huge global burden, endemic to nearly 120 world countries with more than 200 million clinical cases and nearly a million deaths each year. Annually, the number of malaria cases fluctuates from low to high, depending on weather conditions. Moist and warm weather stimulates mosquitoes’ activity in spreading malaria, while drought suppresses vector activity, reducing malaria transmission. Many attempts to use weather parameters, mostly precipitation and temperature, for global and regional malaria modeling and monitoring have not been successful since the weather station network is very limited and stations are spread far apart from each other, especially in places of malaria activity. Therefore, the recent two-­ decade efforts to monitor malaria were focused on high spatial resolution satellite data. Very successful malaria modeling results were obtained with the introduction of satellite-based Vegetation Health (VH) method. The VH assesses vegetation health in response to the impacts of seasonal weather conditions. Since vegetation is the place of mosquitoes and parasite habitat, VH-based vegetation conditions are a good indicator of seasonal mosquitoes’ activity in spreading malaria. This chapter provides modeling results of malaria area and intensity from VH-based estimates of moisture and thermal vegetation condition. Chapter 10: What to Expect with Malaria Intensity During Global Warming? In the twenty-first century, global climate has warmed up to nearly 1.1 °C (relative to preindustrial time average earth temperature (T)). Unfortunately, it is expected that by the end of the twenty-first century, climate would warm up to nearly 1.5 °C (above preindustrial average T) and some scientists warned about possibility that temperature might increase up to 2.5  °C and more (Vicedo-Cabrera et  al. 2021). Such expectations require development of the numerical models to assess global

1.5  Short Summary

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warming impacts on land temperature and land’s environmental resources supporting people’s living. Following climate and land cover changes, What to Expect with Stressed and Healthy Vegetation? Chapter 11: Remote Sensing Drought Watch and Food Security Drought is a typical phenomenon of the Earth’s climate. Losses from drought, especially in agriculture, are staggering. For example, in the USA, the average annual drought damages are around $6 billion. In extreme drought years (Dust Bowl of 1930s, 1988, 2012–2014), costs jump to tenth of billions. Between 2001 and 2021, nearly 20% of land around the world was stricken by drought every year regions in 2007, 2009, 2010, 2012, and 2013. This Chapter discusses how the new Vegetation Health (VH) technology is applying for drought monitoring and assessment of food security from NOAA operational polar-orbiting satellite (POES) data. NOAA/POES is observing currently the Earth with the most advanced VIIRS sensor, which is monitoring droughts for each 0.5, 1, and 4 km2 of global land surface. The VIIRS sensor is detecting drought early and estimating drought area, intensity, duration and, what is the most important, and predicting agricultural losses and food security. Chapter 12: Has Drought Intensified During 1981 to 2021 Global Warming? Since the mid-eighteenth century, the Earth’s climate has been generally warming up. In the past 60-year, Earth warmed up intensively, leading to never before experienced environmental, economic, and social events. According to numerous publications, environmental observations have showed global changes in snow and ice areas, sea level, natural disasters, biological systems (plants, birds, etc.), and others. One of the biggest climate warming concerns currently is drought intensification, increasing losses in agriculture and deteriorating food security. These are serious problems, considering intensive population growth and a gradual leveling off agricultural production. Unfortunately, global temperature is expected to increase in the near future (IPCC 2018a, b, 2019d, e, f, 2020, 2021). Following continuation of global warming, what should we expect with drought intensification and expansion? How much agricultural losses would increase, deteriorating global food security? This chapter will discuss these problems. Specifically, how much global drought has changed, when global temperature increased to 1.1 °C by 2020 (IPCC 2021). Have drought changes affected the development of agro-industrial complex? What should we expect with changes in crop losses and global/regional food security? Will global temperature intensify droughts and their impacts on agriculture?

1.5 Short Summary From the mid-eighteenth century, the Earth’s climate has been warming up. During 1981–2021, Earth climate warmed up intensively, leading to never before experienced environmental, economic, and social events. The environmental observations have showed global changes in snow and ice, sea level, natural disasters, biological

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systems (plants, birds, etc.), and others. Many publications indicated that climate warming has negatively affected crop yield, especially in undeveloped countries of Africa, Asia, and Latin America. Besides agriculture, very important climate warming concerns presently for these continents, with humid climate, are (a) how the global warming has affected malaria and the number of ill people and (b) what to expect with malaria in the future, considering intensification of climate warming and an intensive population growth in the malaria endemic areas of these continents. Unfortunately, there are only limited number of publications covering malaria response to global warming. Since climate warming is anticipating drought intensification, malaria activities might be reduced in some areas. If a warm climate creates favorable conditions (moderately warm and wet) for mosquitoes’ activities, it might increase the number of malaria-affected people. In Chap. 9, we investigated how much the number of malaria-affected people increase/decrease. Very important that (1) NOAA Operational-Orbiting Satellites (NOAA/POES) have been used with spatial resolution of 1 week and 1 km2, (2) the new Vegetation Health (VH) System has been developed and successfully applied for monitoring land cover and numerous events (drought, crop yield, malaria, greenness, temperature, etc.), and (3) 41-year VH data have been accumulated to study climate and its impacts on Earth.

References BerekelyEarth 2020. Global Temperature Report. http://berkeleyearth.org/2019-­temperatures ClimateBet 2018. Global Warming Challenge. http://www.theclimatebet.com HadCRU 2020. UK’s Met Office Hadley Centre. https://crudata.uea.ac.uk/cru/data/temperature/ IPCC 2021 Climate Change 2021. Physical Science Basis. https://www.ipcc.ch/report/ sixth-­assessment-­report-­working-­group-­i/ IPCC 2020 (revised from 2019b). Special Report on Climate Change and Land. August https:// www.ipcc.ch/srccl/ IGBP 2020. Land System. http://www.igbp.net/globalchange/earthsystemdefinitions.4.d8b4c3c12 bf3be638a80001040.html IPCC 2019a. SR5, Special Report: Ocean, and Cryosphere in a Changing Climate https://www. ipcc.ch/srocc/ IPCC 2019b. Special Report on Climate Change and Land. August https://www.ipcc.ch/srccl/ IPCC 2019c Special Report: Critical Land Resource: Desertification, Land degradation, Sustainable land management, Food security, and Greenhouse gas fluxes in terrestrial ecosystems (Working Group 111). https://www.ipcc.ch/2019/08/08/land-­is-­a-­critical-­resource_srccl/ IPCC 2019d. Global Warming of 1.5°C. https://www.ipcc.ch/site/assets/uploads/sites/2/2019/06/ SR15_Full_Report_High_Res.pdf IPCC 2019e. Impacts of 1.5°C of Global Warming on Natural and Human Systems. Ch3. https:// www.ipcc.ch/site/assets/uploads/sites/2/2019/06/SR15_Full_Report_High_Res.pdf IPCC 2019f Refinement to the 2006 IPCC Guideline for National Greenhous Gas Inventory. https:// www.ipcc.ch/report/2019-­refinement-­to-­the-­2006-­ipcc-­guidelines-­for-­national-­­greenhouse-­ gas-­­inventories/ IPCC 2018a. Chapter 3: Observations: OCEAN. https://www.ipcc.ch/site/assets/uploads/2018/02/ WG1AR5_Chapter03_FINAL.pdf IPCC 2018b. Special Report: Global Warming 1.5°C. October. https://www.ipcc.ch/sr15/

References

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IPCC 2014. Climate Change 2014, Synthesis Report. 5th Assessment, (Eds. R.  K. Pachauri and L.  Meyer), Geneva, Switzerland, pp  151. https://www.ipcc.ch/pdf/assessment-­report/ar5/syr/ SYR_AR5_FINAL_full_wcover.pdf IPCC 2012. Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation. IPCC 2019c Special Report: Critical Land Resource: Desertification, Land degradation, Sustainable land management, Food security, and Greenhouse gas fluxes in terrestrial ecosystems (Working Group 111). https://www.ipcc.ch/2019/08/08/ land-­is-­a-­critical-­resource_srccl/ IPCC 2007. Climate Change 2007: Impacts, Adaptation and Variability. Geneva, Switzerland. pp 104. (Wortking Grouo11, 4th Assessment) https://www.ipcc.ch/site/assets/uploads/2018/03/ ar4_wg2_full_report.pdf Kogan F. 2020. Remote Sensing for Malaria: Monitoring and Prediction Malaria from Operational Satellites. Springer. pp. 255. https://www.springer.com/gp/book/9783030460198 Kogan F., W. Guo & W. Yang 2020. Near 40-year drought trend during 1981-2019 earth warming and food security. 10.1080/19475705.2020.1730452 Kogan F. 2018. Remote Sensing for Food Security. Springer. pp. 255. https://www.springer.com/ gp/book/9783319962559 Kogan F., W. Guo, W. Yang and H. Shannon 2018. Space-based vegetation health for wheat yield modelling and prediction in Australia. J. Appl. Remote Sens. 12(2), 026002, doi: https://doi. org/10.1117/1.JRS.12.026002. NASA/GISS 2020. GISS Surface Temperature Analysis. https://data.giss.nasa.gov/gistemp/stdata/ NOAA/NESDIS/STAR 2020. Vegetation Health indices and products. https://www.star.nesdis. noaa.gov/smcd/emb/vci/VH/index.php NOAA 2020. Climate. Global Temperature. https://www.climate.gov/news-­features/ understanding-­climate/climate-­change-­global-­temperature

Chapter 2

Global Warming Impacts on Earth Systems

2.1 Introduction Over the long Earth history, “climate has never been settled” (Ward 2016), since multiple causes are able to change it and sometimes completely. For example, between 100,000 and 15,000 years ago, the Earth climate has changed from warm to ice age and back nearly 25 times. In the relatively recent time, little ice age during 1340–1700 has switched to warming at the beginning of the seventeenth century (CCS 2020; BerekelyEarth 2020a; NASA/NSIDC 2020; NASA/GISS 2020a; IPCC 2007, 2014, 2018a, b, 2019d, e, f; ClimateBet 2018; Haldon et al. 2018; Gray 2016; UN 2016; Easterbrook 2016; WMO 2014; Diaz 2012; Hansen et al. 2010; Kerr 2005). Following the current temperature time series, global climate is warming slow since 1850. The earth warming intensified from the late 1970s, and farther intensified much more from the 2000s. The climate change is controlled by physical factors, such as solar activity, the earth thermal balance, the distance between the Earth and the Sun, the angle of Earth’s rotation axes relative to the plane of the ecliptic, volcanoes, natural and anthropogenic forcing, and others. The current strong global warming is explained by intensive human activities, which include burning fossil fuels (coal, gas, wood, etc.), cement production, increased transportation, intensive agricultural activities, and other (EPA 2021). These processes stimulate greenhouse gases (GHG) emission, including CO2, CH4, N2O, and SF6. Theoretically, the GHGs, specifically CO2, intercept infrared (IR) radiation emitted by earth, spread it around, warming up earth surface and atmosphere, intensifying climate warming. Specific attention has been currently devoted to CO2 (Berwyn 2016), which is working in the atmosphere as an umbrella, intercepting IR radiation. Therefore, in the past 30–40 years, there has been a strong focus on the need to reduce CO2 emission in order to mitigate climate warming and develop some measures for adaptation. The Kyoto Protocol (UNFCC 2015) and the subsequent Adaptation Fund were the first steps to encourage the international community to © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 F. Kogan, Remote Sensing Land Surface Changes, https://doi.org/10.1007/978-3-030-96810-6_2

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work on these goals. The Kyoto Protocol (UNFCC 2015) was issued in 1997 and in 8 years was ratified by the participating industrial countries, obliging them to cut GHG emission by 5% (compared to 1990 level) by 2008–2012. An intensive global campaign to reduce CO2 has begun from the publication of the book “Inconvenient Truth” (Gore 2006) and issuing a film with the same title. These sources have showed time series of global temperature anomaly (TA) increase and the matching time series of CO2 increase as a proof that global warming is the result of CO2 release in the atmosphere. Some of the conclusions were quite scary: “the world at the edge of climatic catastrophe” … “if not stop emitting CO2, we come to the point of no return” (Gore 2006). Besides, according to IPCC (2014) “CO2 is the largest single contributor to radiative forcing over 1750–2011 and strong temperature upcoming trend since 1970”. Therefore, human activities in releasing CO2 have considered to be the cause of the current global warming (Gore 2006; IPCC 2014). Following the GHG theory, in 2015, the 195 countries agreed to participate in the UN-organized “Paris Agreement”, with the goal to reduce emission of CO2 into the atmosphere (Gray 2016). Following the Agreement, the countries have been obliged to cut emission of CO2 to keep the global TA, which is a deviation of the current global-average, annual-mean temperature (Tan) of each year between 1901 and 2020 from the 1850–1900 (preindustrial time) temperature mean (TM1850–1900), under 1.5  °C in the next 50-year, and if possible, below 2.0  °C by the  end of this century. The following formula is used to estimate the TAan = (Tan − TM1850–1900). Following multiple publications, the early twenty-first century global-average, annual-mean temperature anomaly (TAan) has reached nearly 0.87 °C (BerekelyEarth 2020a; HadCRU 2020; NASA/GISS 2020a; Hegerl et al. 2018; WMO 2014; IPCC 2007, 2014). Such intensive warming has produced many changes in the earth systems (atmosphere, ocean, cryosphere, and land). The strongest environmental changes have started in the early 1980s and intensified considerably in the twentieth and the early twenty-first centuries. The global warming and the following earth changes affected adversely land resources, its environment, socioeconomic activities, and human living (NASA 2018; NASA/GISS 2020a; NOAA 2016; NOAA/ NCEI 2017; IPCC 2014, 2019d, f). Environmental publications have already indicated many warming-related changes in earth systems in the early twenty-first century. The strongest changes included reduction of ice in the Northern Pole, ocean level rise, intensification of large-scale natural disasters (cyclones, floods, hurricanes, etc.), strong increase in the land surface temperature, and others. These large-scale changes in the recent 50-year have stimulated many socioeconomic problems on land. Among them, extremely hot land surface and food shortages have deteriorated the quality of human life, especially in the developing countries, and came out currently to the front priorities of policy and decision makers. In addition, global warming has expanded multiyear disbalance between an intensive world population increase and slower growth in global agricultural production (Kogan 2018). The combined shortand long-term global warming impacts on land would increase world hunger, deteriorating human life. In addition to food shortages, global warming would deteriorate

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population living by intensifying some diseases, especially malaria in a huge tropical ecosystem (Kogan 2020a, b). There are other concerns about changes in the warming-related land conditions, which will intensify insects’ activities, increasing losses in agriculture (Young et al. 2020). Multiple researches have indicated that, in addition to deterioration of land’s livelihood, global warming has produced strong anthropogenic pressures on land, driving a 60% of global decline in biodiversity since 1970 (ClimateBet 2018). The most affected regions were Africa and South America. Around one-quarter of the 5692 mammal species are currently threatened with extinction, following 30–40  years of global warming (IPCC 2019f; Bongaards and O’Neill 2018a, b; Watts 2018; UNFCC 2015). Moreover, pest and diseases have increased annual losses of agricultural production in the recent 20-year (IPCC 2019b; UNESCO 2018; Alexandratos and Bruinsma 2012; Nemani et  al. 2003). Following the observed land deterioration in the most recent four warmest decades, it is hard to expect an improvement in land productivity. The attempts to develop the new adaptation strategies up to the 2030s need additional efforts, bringing more environmental data, especially satellite data, for more precise analysis of climate warming impacts on land (NOAA/NCEI 2020a; Baseto et al. 2020; Kogan et al. 2020; IPCC 2019g; Bongaards and O’Neill 2018a, b; ClimateBet 2018; Seager 2018; Bugatho 2018; Najafi et al. 2018; Shohag and Alm 2018; Kogan 2018; Hegerl et al. 2018; WB 2017; WMO 2017; AG 2017; Easterbrook 2016; Smith and Katz 2013; Parvez 2010; Murph and Timbal 2008; Lucht et al. 2002). One of a very important climate warming concerns presently is how has a very warm earth degraded land environment and deteriorated living of an intensively increasing world population. From global warming consequences, the most troubling for humans are climate-stimulated weather-related food shortages, leading to millions of hungry and even dead people, specifically in the developing countries (Charles et al. 2018; Seager 2018; Najafi et al. 2018; FAO 2017, 2018; NOAA 2016, 2017; WMO 2014, 2016, 2017, 2018)? According to The World Count (WorldCnt 2020), during only first half (January–July) of 2020, 5.3 million people have already died because intensified and expended droughts reduced agricultural production in Africa, causing food shortages, hunger, and hunger-related diseases. Moreover, from the 1990s, 8–10 million hungry people died every year in the developing countries, which is more than from AIDS, malaria, and TB together (WorldCnt 2020). The worst situation is with children in the developing countries, who are dying from hunger every 10 s (WorldCnt 2020). The worst hunger area is Africa, with 20% (30% in East Africa) of population suffering from hunger. In sub-­ Sahara Africa, every third child has stunted growth due to continued lack of food. Around 24% of the world population are living currently with insecure annual food supply and 9% of these people are located in the areas with severe food shortages (WorldCnt 2020). Global policy-decision makers, international organizations, and scientists have undertaken different actions in the nineteenth and twentieth centuries (especially, from the 1980s) to (a) investigate climate warming dynamics (intensity, duration, etc.), (b) assess the warming impacts on Earth systems (ocean, cryosphere,

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atmosphere, land), (c) orient policy-decision makers towards warming consequences for land’s livelihood, (d) predict global temperature increase in the next 5–10  years, and (e) develop adaptation strategies (UNESCO 2018; ClimateBet 2018; NOAA/NCEI 2020a; WMO 2017; WB 2017). Investigation of the earth climate after the nineteenth century has showed that the world is warming, producing strong impacts on earth. The data indicated that northern ice has reduced, ocean level has increased, hurricanes, droughts, floods have intensified and expanded, etc. (WMO 2017; ClimateBet 2018; IPCC 2019b; UNESCO 2018). Some of the disasters have affected human life globally. Climate publications have indicated that drought intensification and expansion have increased agricultural losses, increasing the number of hungry people in the developing countries with almost half of the world’s population (IPCC 2019a, b, c; Shohag and Alm 2018; Kogan 2018, 2020a, b; ClimateBet 2018; UNESCO 2018; WB 2017; WMO 2017; AG 2017; UNFCC 2015). These warming-related problems, specifically in the past 50-year, have stimulated huge governmental, social, and scientific activities to investigate causes of global warming, its intensity, tendency, area and, especially the impacts on the entire earth and land currently and in the future. Among these activities and 1000 climate papers, the two serious world’s actions have been undertaken for numerical analysis of global warming and its impacts on the Earth, and specifically on land. These activities included development of: 1. Multiyear global annual temperature anomaly (TA) records and 2. Climate change Reports by the International Panel on Climate Change (IPCC) The developed 170-year global TA time series and nearly 2 dozen of the IPCC Reports have been used by Governments, policy-decision makers, economists, scientists, and general public, as a well-determined evidence of climate warming and impacts on earth. It is extremely important that the TA have been measured numerically, as a deviation of global average, annual mean temperature (T), derived as combined land and ocean T during the 170-year climate warming), from the preindustrial time (1850–1900) mean annual global (TM1850–1900). The IPCC Reports have been based on thousands of peer-reviewed scientific papers, which explored global warming and its impacts on earth systems. Besides, the Reports have also used measured regional mean weather parameters (precipitation, snow, drought, ice, SST, soil moisture, etc.). Revising the IPCC Reports, we investigated if the global warming-based land changes have been analyzed numerically, accurately, and completely. The indicated two activities, together with the thousands research papers, present currently the main understanding of global warming dynamics, intensity, and impacts on earth. Based on the two activities and the corresponding multiple research papers (BerekelyEarth 2020a; NOAA 2020a, b, c, d; ECMWF 2020; NASA/GISS 2020a; Kogan 2018, 2020a, b; Kogan et al. 2020; Young et al. 2020), the current understanding of global warming dynamics, intensity, and impacts on land and humans can be summarized briefly as:

2.2  Global Temperature and Anomalies for Climate Studies

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1. Global warming has started in 1850 and is continuing through present. 2. The strongest warming has initiated in the late 1970s and intensified in the 1990s and more in 2020s. 3. Global warming of the past 50–60 years has changed the earth environment and its ecosystems at various spatial-temporal scales. 4. The major climate parameters (temperatures, precipitations, ice, snow, etc.) have been changed, affecting strongly land conditions and human life. 5. Extreme climate disasters, such as cyclones, hurricanes, droughts, floods, etc. have intensified, expended, and became more frequent. 6. Agricultural losses increased, compromising economy and livelihood, especially in the developing countries. 7. The number of sufferers from malaria in tropics has increased. 8. Insect’s invasion, damaging crops, and pasture have expanded and intensified. 9. Food security deteriorated, increasing the number of hungry people, especially in the developing countries. 10. Climate warming is expected to intensify in the future, deteriorating land’s environment and human living.

2.2 Global Temperature and Anomalies for Climate Studies Following the developed 170-year TA time series by the indicated climate groups, the world is generally accepting the global warming as an ongoing process (NOAA/ NCEP 2017, 2020, 2016; ECMWF 2020; NASA 2020; IPCC 2019b, c; Lindsey and Scott 2019; UNESCO 2018; IPCC 2007, 2012, 2014, 2019d, e, f; Najafi et al. 2018; Bastasch 2017; Forzieri et al. 2017; NASA/GISS 2020a; Hegerl et al. 2018). As the 170-year (140-year by NOAA) time series showed, in the 18th and the first half of the nineteenth centuries, TA has been increasing slow, but the warming has intensified thereafter, specifically, in the twentieth century, when TA exceeded mean temperature of the preindustrial time (1850–1900) by nearly 0.9 °C (ECMWF 2020; IPCC 2019b, c; WMO 2016; Smith and Katz 2013; Alley et al. 2010). Meanwhile, we found quite a few scientific publications, expressing concerns about a quality of the developed global TA time series (Sherwood et al. 2020; Smith and Katz 2020; WRI 2020; Jayarlj and Rotter 2020; Rotter 2019; Bjorklund 2019; Hegerl et al. 2018; CarbonBrief 2015, 2017; Morice et al. 2012; Vose et al. 2012; Karla 2009; Jones et al. 1999). These publications are indicating that the T measurements over the earth surface are limited and sparsely distributed, over both land and ocean, especially, over the ocean (sea surface temperature (SST) measurements). The T measurements of such land ecosystems as deserts (Sahara, Australia, etc.), forests (tropical, Siberian, etc.), and cryosphere are extremely limited and are not well-presented in the land mean T. More importantly, there are no T observations at the Poles. For example, there are indications that if weather stations and T measurements had been available at the Poles, the global mean T might had been cooler than now.

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2  Global Warming Impacts on Earth Systems

If desert, which occupies 33% of land, had had more weather stations, mean-desert T might had been higher and the global warming might had been more intensive. Opposite situation is with the forest. If more weather stations would had been available in the Siberian forest, the global T might had been cooler (Lambert et al. 2011). Ocean has much less locations, measuring temperature than land. This might reduce global warming intensity, since ocean is cooler than land and occupies 70.8% of earth surface (Rotter 2019; Bjorklund 2019; NOAA 2020c; Merzdorf 2019; CarbonBrief 2015; Vose et al. 2012; Jones et al. 1999).

2.2.1 Development and Accuracy of the Global TA Time Series and UN-Based IPCC Activities The world community is currently accepting the 170-year annual world mean T and TA (deviation of T from the temperature of the preindustrial time (1850–1900)), developed by the five climate groups: BerekelyEarth (2020a, 2015), HadCRU (2020), NOAA (2020), NASA/GISS (2020a), Cowtan and Way (2014), and Hegerl et al. (2018). Following the selected climate groups, the records of world-average, annual-mean temperature anomaly (TA) covered the period from 1850 (NOAA from 1880) through 2019/2020, containing 170-year (140-year NOAA) global annual TA time series. There are other groups and even individual scientists developing TA records, such as the Japan’s Meteorological Services, University of Columbia (USA), and others (JMS 2020; Spencer 2021; SceptS 2020). However, the world is using the time series, developed by the indicated five climate groups (TATS 2020). In order to estimate the accuracy of the developed TA records, it is needed to understand clearly how the TA has been calculated through multiple processing stages (collecting temperature measurements from land and ocean, their aggregation to annual and global levels, statistical processing of the data to fill the gaps, climatology calculation, etc.). Following these multiple stages of data processing, the developed time series might have errors from the initial up to the final stage of the 170-year time series. In order to have a right impression on how complex and complicated the process of time series development due to errors the Table 2.1 indicate these sources, which must be corrected before being included in the developed 170-year TA time series. If only at the initial stage of processing raw T and SST data are not collected, aggregated, and statistically processed correctly, the estimated global annual TA trend and global warming might be inaccurate. In the following discussion we will investigate the development of 170-year TA records, specifically, raw land temperatures, methods of data processing, corrections of errors, aggregation of T data to land mean and SST data to ocean-mean, aggregation of land and ocean data into the earth surface-mean, and finally, calculation of global annual multiyear TA time series. Our main goals were to assess (a) How the developer of TA time series have been avoiding errors? (b) What earth

2.2  Global Temperature and Anomalies for Climate Studies

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Table 2.1  Errors in raw temperature measurements, used for the development of multiyear global annual temperature anomaly (Sherwood et al. 2020; Smith and Katz 2020; WRI 2020; Jayarlj and Rotter 2020; Rotter 2019; Bjorklund 2019; Merzdorf 2019; Hegerl et al. 2018; CarbonBrief 2015, 2017; Morice et al. 2012; Vose et al. 2012; Karla 2009; Jones et al. 1999) Earth surface Land

Ocean

Errors due to Incorrect T measurements in Africa, South America, Russia’s Siberia (around 50% errors) General lack of locations, measuring T and SST around the world Very sparce distribution of weather stations No T measurements in the two Poles (very cold area) Lack of T measurement in the mountains, forests, and deserts (occupy 87% of land) Much fewer weather stations measuring T during preindustrial time Urbanization impacts on T data Ecosystem changes near a weather station Much less raw T records in Southern hemisphere Changes in methodology for measuring and processing T Small average area (7100 km2), covered currently by one weather station Shortage of weather stations with T data in Africa (one station for 25,000 km2) Changes in instruments, measuring T Changes in the technique T measuring and aggregation Changes in the location of weather station, measuring T Changes in the time of T measurements Changes in the methods of calculation of monthly and annual mean T Very small average area (91,000 km2), covered currently by one buy and ship Much less location with SST measurement in preindustrial time Much less SST data, measured by buys, in Southern hemisphere Large daily temperature variations not related to climate/weather Incorrect SST measurement in shallow water Very small number of buys ( TC, the estimated year is warmer than TC and cooler if T