Modern Science of Climate Changes [1 ed.] 9781617616358, 9781617612732

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Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved. Modern Science of Climate Changes, Nova Science Publishers, Incorporated, 2010. ProQuest Ebook Central,

Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved. Modern Science of Climate Changes, Nova Science Publishers, Incorporated, 2010. ProQuest Ebook Central,

CLIMATE CHANGE AND ITS CAUSES, EFFECTS AND PREDICTION

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MODERN SCIENCE OF CLIMATE CHANGES

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CLIMATE CHANGE AND ITS CAUSES, EFFECTS AND PREDICTION

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MODERN SCIENCE OF CLIMATE CHANGES

ERNEST C. NJAU

Nova Science Publishers, Inc. New York

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Copyright © 2011 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers‟ use of, or reliance upon, this material.

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Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book.

LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA Njau, Ernest C. Modern science of climate changes / Ernest C. Njau. p. cm. Includes index. ISBN:  (eBook) 1. Climatology. 2. Climatic changes. I. Title. QC981.N53 2010 551.6--dc22 2010029781

Published by Nova Science Publishers, Inc. † New York

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CONTENTS Preface

vii

Acknowledgments

ix

Abbreviations

xi

Chapter 1

Introduction

Chapter 2

Basic Science on which the Climate System Operates

19

Chapter 3

Solar Activity

35

Chapter 4

Historical Development of the Science of Climate Changes up to 1990s

47

Modern Science of Natural Climate Changes

57

5.7 Prediction Of Future Global Temperature Variations Using Equation (5.18)

88

5.8 Actual Shapes Of Terrestrial Temperature Variation Patterns Associated With Cyclic Variations In Incident Solar Energy

90

5.9 The Ozone Hole And Solar Activity

92

Chapter 5

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1

vi

Chapter 6 Chapter 7

Contents

Modern Science of Human-induced Climate Changes

95

Modern Science of Natural and Human-induced Changes in Earthquakes, Volcanic Activity and Related Climate

105

Chapter 8

A Modern Method for Predicting Climate Changes

129

Appendix

Mathematical Derivation of the Meridional General Circulation Model in Figure 5.11

149 159

Index

167

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References

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PREFACE Series of recent scientific (journal) publications have indicated that the crucial science governing climate changes has not yet been understood well and published in book form up to the late part of the 2000 – 2010 period. Consequently not only that some scientifically erroneous reports on climate changes have been published, but also disagreements on the issue of climate changes have continued to prevail. For example, the much publicised global warming trend has not taken place since 2000. Also some publications have opposed each other on the issue of climate change. Not only that. Annual U.N. climate meetings have (by 2010) failed to achieve any major breakthrough since signing the Kyoto Protocol in 1997. As an inevitable result, important documents (including the four Intergovernmental Panel on Climate Change (IPCC) reports issued so far) and decisions concerning climate changes have been based on incomplete or partly incorrect science. Bearing in mind the importance and influences of climate changes on people‟s lives all over the world, I have recently spent time in collecting and analysing newly published papers on climate changes as well as published works that criticise and correct the currently used science of climate changes. The collections I have accumulated clearly indicate an urgent need for a new (and hopefully widely circulated) book that would report on the most correct, unchallengeable and complete science of climate changes. Such a modern book will hopefully be one of the scientifically most appropriate documents for guiding global and regional decisions as well as studies on climate changes. It is on the basis of the brief account given above that this book has been written. The book first describes the structure of the climate system as well as the processes upon which the system runs, changes and operates. Then a historical development of the science of climate changes is presented from ancient times

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viii

Preface

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up to the late 1990s. Following this is a detailed description of important discoveries made since the late 1990s which have led to creation of modern science of natural climate changes and human-induced climate changes. A unique feature of the book is that it contains a presentation of recently reported new theory and causes of natural variations of earthquakes as well as humaninduced variations of earthquakes. Furthermore the book also presents a new theory and causes of natural and human-induced variations in volcanic activity together with associated climate changes. Finally the book presents scientifically predicted short-term and long-term (future) changes in climate, earthquake activity and volcanic activity. It is expected that these predictions will be used by national, regional and international communities to properly institute adaptation strategies, plan and prepare for the future. The contents of the book make it an essential and unique book for students in tertiary institutions studying meteorology, climatology, environmental sciences, agriculture, geography, geophysics and geology. It is also a very useful document to practising climatologists, meteorologists, environmentalists, geographers, agriculturists, geologists and geophysicists. Finally I am extremely grateful for invaluable co-operation and guidance from Nadya S. Gotsiridze – Columbus of the Nova Science Publishers, Inc.

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ACKNOWLEDGMENTS I was consulting scientist to the U.S.A. Space and Science Research Centre (under the directorship of John L. Casey) when plans to write this book were shaping up. For this reason, I am grateful to John L. Casey for his cooperation during my consulting scientist position. Several eminent scientists have had chances of reading through some of my (now already) published works and making comments that were extremely useful to me. Some of the works are part of this book. Among these eminent scientists, I would like to particularly and representatively mention and thank the following: Prof. Saffa B. Riffat (of the University of Nottingham, United Kingdom), Prof. Dr. Hartmut Grassl (of the Max Planck Institute for Meteorology, Germany) and Prof. Kirill Kondratyev (of the Russian Academy of Sciences, Moscow). The author is also grateful to the following publishers for kind permission to reprint and include herein some copyright figures from their journals and books: Academic Press, Allen and Unwin, American Association for Advancement of Science, American Geophysical Union, American Meteorological Society, Arnold, Black Swan, Cambridge University Press, Collins, Elsevier Science Publishers, D. Reidel Publishing Company, Houghton Mifflin Company, Macmillan Publishing Company, McGraw-Hill Book Company, Methuen, Pergamon Press, Royal Swedish Academy of Sciences, Seismological Society of America, The American Physical Society, The English Universities Press, Tiempo Editorial, and World Meteorological Organisation.

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ABBREVIATIONS ARF CAS CP DRF EAS ENSO ETM GCM GHG GHW IPCC ISRC ITCZ KLR LFP MA MTGC NAO NOAA NAOI NHZI SAS SCS SEM SO SOI

Amplified radiative forcing Crust – atmosphere system Central peak Direct radiative forcing Earth – atmosphere system El Nino – Southern oscillation Envelope – tracing method General circulation model Greenhouse gases Global heat/temperature waves Intergovernmental Panel on Climate Change Incident solar radiation changing Intertropical convergence zone Kirchhoff‟s law of radiation Lower frequency peak Mechanical advantage Meridional Tropospheric General Circulation Node–antinode oscillation National Oceanic and Atmospheric Administration North Atlantic Oscillation Index Northern hemisphere zonal index Surface – atmosphere system Surface – to – magnetosphere circulation systems Science – extension model Sinusoidal oscillation Southern oscillation index

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Ernest C. Njau Upper frequency peak United Nations Framework Convention on Climate Change Ultra-violet Velocity ratio

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UFP UNFCCC UV VR

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Chapter 1

INTRODUCTION

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1.1. THE EARTH’S ATMOSPHERE The definitions of weather and climate given in sections 1.2 and 1.4 involve the earth‟s atmosphere. Therefore, it is proper that we introduce ourselves to the earth‟s atmosphere before looking at those definitions. What is called earth‟s atmosphere (or simply atmosphere) is the blanket of air and airborne particles surrounding the earth. The atmosphere extends from the earth‟s surface up to an altitude of about 10 earth radii. Note that one earth radius is 6371 kilometres. Atmospheric density and pressure decrease exponentially as altitude increases. The atmosphere is divided into (horizontally stratified) layers using certain specific criteria. If we take degree of ionisation as the only criterion, then the atmosphere is divided into three layers. The first layer, which is relatively non-ionised, extends from the earth‟s surface up to an altitude of about 60 kilometres. The second layer (called ionosphere) extends from an altitude of about 60 kilometres up to an altitude of about 1,000 kilometres. This layer has the highest electron density. If you go into further details, you will find that the ionosphere is itself divided into D, E, F1 and F2 layers. Above the ionosphere is a third layer called magnetosphere. Motions of ionised particles in this layer are controlled by the earth‟s magnetic field. The magnetosphere is bounded at its upper most part by a relatively thinner layer called magnetopause. Solar wind (see chapter 3 for its definition) constantly lands and pushes on the latter layer.

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We can also divide the atmosphere into layers on the basis of temperature variations. Such temperature-based division leads to the layers given in Table 1.1. Both pressure and density in the atmosphere decrease rather exponentially with altitude. Suppose Ph and Dh represent atmospheric pressure and density at height h above sea level, respectively. If the pressure is Po at sea level and also the density is Do at sea level, then the symbols given above are related mathematically as follows: Table 1.1. Atmospheric layers based on temperature variations Name of layer Troposphere

Tropopause

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Stratosphere

Stratopause Mesosphere

Mesopause Thermosphere

Altitude range 0 → 10 to 17 km. in the tropics and 0 → 7 to 10 km. in polar regions.

Main characteristics Temperature decreases as altitude increases. The rate of decrease is about 10oC per km. This rate of temperature decrease with height is called lapse rate. Thin layer above the Temperature stops decreasing troposphere. with altitude. From the tropopause up Temperature increases as altitude to an altitude of ~55 km. increases. This is because the (in the tropics) and ~ 50 ozone layer in the stratosphere km. (at the polar (which peaks at altitudes 20 to 26 regions). km) absorbs UV solar radiations at wavelengths below 0.3 µm. Thin layer above the Temperature stops increasing with stratosphere. altitude. From the stratopause to Temperature decreases as altitude an altitude of ~ 85 km. in increases. the tropics and ~ 80 km. in polar regions. Thin layer above the Temperature stops decreasing mesosphere. with altitude. From the mesopause Temperature increases as altitude upwards. increases.

(1.1)

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(1.2)

where k is a constant. If h is given in metres, then

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given in km, then

3

. But if h is

. Equation (1.2) shows that as one climbs a

high mountain, the air density and hence also oxygen supply decrease. This makes the climbing process strenuous unless extra oxygen supply is available. It is for this reason that the peak of the world‟s highest mountain (ie. Mount Everest) was reached in 1953 after availability of portable oxygen containers. Since both pressure and density decrease as altitude increases in the atmosphere, about 99.9% of the atmospheric mass is in the troposphere and stratosphere. The troposphere alone houses about 90% of the atmospheric mass in the tropics as well as about 75% in middle latitudes and virtually all the clouds, water vapour and precipitation. Specifically about 99% of the atmospheric mass and virtually all the clouds, water vapour and precipitation are contained in the lower atmosphere below an altitude of 30 kilometres. On this basis, the field of meteorology is mostly concerned with studies in this particular lower atmosphere. In some meteorology and related books, the word “atmosphere” is used implicitly to represent the “lower atmosphere” just mentioned above. We should note that the real atmosphere has complicated horizontal and vertical variations. For the sake of simplicity and usefulness, let us think of an ideal atmosphere in which all the horizontal and time-dependent variations are averaged. In such an ideal atmosphere the structure is a function of height or altitude only. This ideal atmosphere is called “standard atmosphere”, and is the one represented by equations (1.1) and (1.2). Observations have shown that as far as variations below an altitude of 100 km. are concerned, the standard atmosphere does not differ with the actual atmosphere by more than 30%.

1.2. WEATHER Among the words which are most popularly mentioned or spoken in dayto-day talks worldwide are weather and climate. By definition, weather is the short-term condition of the atmosphere created by the following parameters: temperature, wind, precipitation, humidity, pressure, cloudiness, visibility and sunshine. These eight parameters are specifically referred to as weather

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Ernest C. Njau

parameters or weather elements. On the basis of the definition given above, reports of global or regional or local weather are given over short periods such as on hourly basis, 3 hourly basis, 12 hourly basis and daily basis. High resolution assessment of weather is obtained from a combination of surface observations (or measurements), upper-air (ie. upper-level) observations (or measurements), weather radar data and satellite data. For the surface measurements temperature, pressure, humidity and wind velocity are measured by thermometers, barometers, hygrometers and anemometers, respectively. Also sunshine duration, precipitation, visibility and cloudiness are measured by sunshine recorders, rain gauges, visibility meters (or hazemeters or range meters or transmissometers) and cloud-photography devices, respectively. Where measurements of solar radiation are needed, these are made by pyranometers and pyrheliometers. Upper-air (or upper-level) measurements are measurements of weather elements made at one or more of the atmospheric levels whose pressures are 100 mb, 200 mb, 300 mb, 400 mb, 500 mb, 700 mb and 850 mb. Here mb is a short form of millibar. Note that 1 mb is a pressure equal to 100 N/m2. Upperlevel temperature, pressure and humidity are measured by radiosonde (which is fitted with a thermometer, a barometer and a hygrometer) and balloon ascents. A radiosonde is a system of instruments which is lifted up into the air and made to send weather conditions to a ground receiving station using radio waves. Radiosonde systems can rise up to altitudes of about 40 kilometres. Wind velocity measurements at upper-air levels are measured by rawinsonde (which is a radiosonde made specifically for measuring wind velocities). For additional betterment, the surface and upper-air measurements are supplemented by satellite and radar data. This data contains useful information on mean cloud cover, winds flowing inside clouds, albedo, sea-surface temperature, et cetera.

1.3. WEATHER FORECASTING Information on the weather is useful not only for the general public but also for the agricultural sector, industry (notably the aviation industry) and the surface transport sector. Before an aircraft (or aeroplane) pilot starts a flight, he/she is supplied with information on weather conditions along the planned flight path. That information enables the pilot to avoid or take precautions against any of the following weather conditions along or near the path: air turbulences, extreme fog and wind shear, pressure and temperature extremes,

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lightning, dust haze, downbursts, etc. Remember that all flights for helicopters, jet and propeller aircrafts and supersonic aircrafts take place below an altitude of 30 kilometres. Aside from knowing the instantaneous weather, ordinary people and farmers would like to know how the weather will be some hours to come. Such advance knowledge would enable one to decide on whether taking an umbrella is necessary or on the type of clothes to put on. The advance weather information can also tell whether a football match should be held or should be postponed. As for the farmer, the advance knowledge will guide him/her in making accurate short-term decisions concerning his/her farming activities. Weather is in fact the variable that most dominantly affects crop yields and crop losses worldwide. Now the process of generating expected weather conditions in advance is called “weather forecasting” or ”weather prediction”. Some years back weather forecasting used to be made through a mostly manual conventional method. Nowadays, however, it is the computer-based numerical model method that is mostly used in making weather forecasts.

Figure 1.1. Variations of global mean temperature during the last 11,000 years. Reproduced with kind permission from Lowrie W. (1997): Fundamentals of Geophysics, Cambridge University Press.

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Temperature change (oC)

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Making a weather forecast using the conventional method follows the following steps. First surface measurements and upper-air measurements are used to prepare surface weather maps (or charts) and upper-air weather maps (or charts), respectively. Each map contains plotted values of the weather elements such that each element is represented by a unique symbol. On the basis of continuity considerations each weather map is carefully extrapolated forward (in time and space) to form a weather forecast. Weather forecasts can also be made using weather/climate models. In simplified language, a weather/climate model is a small imagined and closed world created inside a computer. Such a model calculates how the weather/climate may vary in the imaginary world they represent over periods of time, subject to some initial assumptions. A range of weather/climate models has been developed in different countries over the last 30 years. Currently the most advanced of such models (the so-called general circulation models) are found in the U.S.A. and United Kingdom. A weather forecast based on numerical model method is made through the following steps. Outputs from runs of weather/climate computer models conducted in regional/global weather modelling centres (in the U.S.A., Europe, Canada, Japan, … etc) are received by the forecaster directly or through the internet. Then the forecast fields contained in the received outputs are translated and improved by the forecaster to form a regional or local weather forecast.

Little ice age Medieval warm period

1000 AD

1500 AD

1900 AD

YEAR Figure 1.2. Variations of global mean temperature since 800 A.D. (see solid lines). Reproduced with kind permission from Jain P. C. (1993): „Greenhouse effect and climate change: Scientific basis and overview‟, Renewable Energy, vol.3, pp. 403 420. We have used curve-fitting methods to plot out the most dominant oscillation formed by the solid-line variations (see dotted curve).

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1.4. CLIMATE AND CLIMATE CHANGE When weather is observed and averaged over a sufficiently long period, what results is climate. Since climate looks at long-period averages of weather, it is generally influenced by the atmosphere, cryosphere (ie. snow accumulation and ice masses), hydrosphere (ie. water along the earth‟s surface), lithosphere (ie. land masses along the earth‟s surface) and biosphere (ie. biological organisms in the atmosphere, land and oceans). On this basis, the so-called climatic system (which is mostly powered energy-wise by the Sun) is made up of the atmosphere, hydrosphere, lithosphere, cryosphere and biosphere. Thus we can alternatively define climate as the long-term conditions created by averages of the parameters which dominantly influence the dynamics and structures of the atmosphere, cryosphere and hydrosphere. This book is strongly biased towards modern climatology (which deals with the actual causes of climate and climate changes) rather than on classical climatology (which deals with averages and extremes of climatological parameters). Let us now look briefly at the issue of climate change. On the basis of the definition of climate given above, it is obvious that climate change is generally defined as any significant shift of climate. As long as the shift occurs, we say that climate change has taken place irrespective of the causes of the change. If further details on a climate change are needed, then one may subdivide it into a natural component and an anthropogenic component. Each of these two components may be subdivided into subcomponents, depending on the interest at hand. The definition of climate change given above is generally agreeable with that used by the Intergovernmental Panel on Climate Change (IPCC). According to the IPCC, climate change is “any change in climate over time, whether due to natural variability or as a result of human activity” (see Tiempo, Issue 40/41 dated September 2001, page 28). But the 1992 United Nations Framework Convention on Climate Change (UNFCCC) uses a slightly different definition of climate change. The UNFCCC defines climate change as “a change of climate that is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and that is in addition to natural climate variability observed over comparable time periods” (see Tiempo, Issue 40/41 dated September 2001, page 28). In this book we shall hereinafter adopt the definition of climate change given by the IPCC, which is in agreement with the general definition given earlier in this Section.

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Ernest C. Njau Scale of deviations from the mean ratio of the abundance of the two oxygen isotopes O18/O16 in parts per thousand

8 -1.4

-123

-330

-199 -102

-2.8

-81

-6

-111

-342

-270

-21

-4.2 -400

-300

-200

-100

0

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Scale in thousands of years before (-) present

Figure 1.3. Long term variations of climate (effectively of world temperature) over the past 400,000 years based on the orbital variables. Crosses show how far the part of the curve relating to the past agrees with oxygen isotope measurements from deep ocean bed cores. The numbers give the dates in thousands of years before the present time of key points on the curve. Reproduced by kind permission from Professor Berger‟s article in Vistas in Astronomy, vol. 24, pp. 103 -122 (1980)). We have used dashed lines to sketch out the variation envelopes formed by the exponential pulse waveforms formed by the solid-line variations.

1.5. GLOBAL WARMING Global warming is simply the rising of global temperatures. Past records show that natural global warming trends have occurred quasi-periodically over thousands and millions of years. The last global warming trend, which is the one worrying us most, started naturally around 1625 before the industrial revolution. Variations of global mean temperature during the last 11,000 years are shown in Figure 1.1.

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Introduction

9

These variations are continuously dominated by a natural oscillation at a period of the 2300 – 2700 years solar cycle described in chapter 3. In fact a very significant positive correlation exists [1] between the latter solar cycle and the 2300 – 2700 years global temperature oscillation in Figure 1.1. The last part of Figure 1.1. is illustrated in more detail in Figure 1.2. The latter Figure is dominated by an oscillation formed by two portions, one related to the 400 – 550 years solar cycle and the other related to the 1000 – 1250 years solar cycle. The former portion exists from 1625 onwards (see later parts of this chapter). It is obvious from Figure 1.1 that the 2300 – 2700 years natural oscillation in dominating this Figure started its ongoing rising phase at around 1625 and is expected to reach its next peak in 2825 – 2925. Also the natural oscillation dominating Figure 1.2 started its ongoing rising phase at around 1625 and is expected to reach its next peak at around 2060. Consequently global warming has been taking place since around 1625. Now the key question to ask here is: Isn‟t this global warming mostly natural? A detailed answer to the last question is given in chapters 5 and 6. However, some clues to this answer may be guessed from simple analysis of Figures 1.1 and 1.2. Firstly we note that continuation of the dominant natural oscillations in Figures 1.1 and 1.2 beyond 1625 (which has actually happened) must give rise to global warming. Secondly if human activities have significantly contributed towards global warming, these contributions must have started with the industrial revolution (1750 – 1850). As a result one would expect that the post-1750 rising phases in Figures 1.1 and 1.2 would be human-enhanced and hence have relatively great gradients. On the contrary the gradient of the post-1750 rising phase is not greater that any of the gradients of three out of the last four pre-1750 rising phases in Figure 1.1. Details given in chapters 5 and 8 show that since the last Little Ice Age, global mean temperature variations have been modulated at a period equal to that of the 80 – 120 years solar cycle see chapter 3 for information about this cycle). It is this modulation that has virtually stopped global warming since 1999 as already verified by observations [2]. Although global warming will expectedly resume later on, it will be expectedly stopped and reversed by the oscillation in Figure 1.2 at around year 2060 as detailed in subsequent chapters.

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+2.5 2 0 -1 -2 -3 -4

Temperature change (°C)

10

-5 160

120

80

40

0

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Thousands of Years Before Present

Figure 1.4. Variations of global mean temperature during the last 160,000 years (see solid lines). Reproduced with kind permission from McBean G. (1992): „The Earth‟s climate system‟, WMO Bulletin, vol.41, pp. 393 - 401. The arrow points at a rapid rising phase of the exponential pulse waveforms involved. Dashed lines have been used to plot out the most dominant envelopes formed by the solid-line variations.

Figure 1.5. Same as Figure 1.1 but now dashed lines have been used to sketch out the apparently exponential pulse waveforms formed by the dotted lines.

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1.6. GLOBAL WARMING AND ATMOSPHERIC CARBON DIOXIDE Let us briefly look at global average temperature over the past hundred thousands of years before relating global warming to atmospheric carbon dioxide (CO2). Figure 1.3 shows variations of global average temperature during the last 400,000. These variations are in form of approximately exponential pulse waveforms with periods similar to those of corresponding changes in the parameters of the earth‟s orbital geometry (see chapter 2). By their natural characteristics, exponential pulse waveforms have rapid rising phases and relatively slower falling phases. This basic feature will be also noted in connection with the next two Figures. Berger [3] has proved convincingly that the variations in Figure 1.3 have been caused by variations of the earth‟s orbital geometry parameters, notably the ~100,000 years Milankovitch cycle. A more detailed display of the last 160,000 years of Figure 1.3 is shown in Figure 1.4. Since Figures 1.3 and 1.4 are dominated by approximately exponential pulse waveforms with a mean period of ~ 116,000 years, the variation patterns in these Figures are expected to gradually drop down to the next major ice age some 98,000 years from the present. Note that exponential pulse waveforms are familiar features in variations of climatic parameters. To illustrate this point, it can be shown that the temperature variations in Figure 1.1 are apparently shaped into exponential pulse waveforms (see Figure 1.5). In addition, variations of mean surface air temperature in the U.S.A. have been characterised by exponential pulse waveforms (see the thick solid line in Figure 1.6). These waveforms have a variation period equal to that of the second harmonic of the 80 – 120 years solar cycle (see chapter 3). On this basis Figure 1.6 implies existence of a cooling trend in the U.S.A. starting around year 2010. Let us now look at both temperature variations and atmospheric CO2 variations. The temperature variations in Figure 1.4 have been placed side by side with corresponding variation of atmospheric CO2 concentration in Figure 1.7. Surely a very high positive correlation exists between the temperature variations and CO2 variations in Figure 1.7. But we are already sure that the temperature variations have been caused by corresponding variations in the earth‟s orbital geometry parameters [3]. It is, therefore, the climatic variations associated with the latter variations that caused the CO2 variations in Figure 1.7, and not the other way round.

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54.0

12.0 Degrees C

Degrees F

56.0

52.0

50.0

10.0 1900

1920

1940

1960

1980

2000

YEAR

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Figure 1.6. Mean surface temperature in the U.S.A. from 1895 to 2006 (see thick solid lines). This thick line has been fitted through the annual variations (see thin solid lines) in order to reflect variations at periods greater than 30 years. Data for the thin solid lines has been gratefully sourced from NOAA, National Climate Data Center.

Available records [4-6] show that the total atmospheric CO2 in 1968, 1981 and 1986 was 2.3 x 1012 tonnes, 2.4 x 1012 tonnes and 2.7 x 1012 tonnes, respectively. In 1998 human activities were emitting CO2 at an annual rate of about 6 x 109 tonnes. The oceans (which cover ~ 71% of the earth‟s surface) contain about 60 times more CO2 than the atmosphere. Anthropogenic activities can generate 16 to 23 x 109 tonnes of CO2 annually and deplete ~ 2 x 109 tonnes of CO2 annually. On the other hand, the oceans alone can release up to 100 x 109 tonnes of CO2 annually and absorb up to 100 x 109 tonnes of CO2 annually.

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13

280 CO2

240 2.5 220 0

200 o

C

-2.5

180

-5.0 -7.5

Change in atmospheric temperature oC

Carbon dioxide ppm

260

-10.0

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160

120

80

40

Thousands of years ago

0 Present

Figure 1.7. Variations of global mean temperature and atmospheric carbon dioxide concentration during the last 160,000 years. Reproduced with kind permission from Gribbin J. (1990): „Hothouse Earth, Black Swan, London.

Let us see the conditions under which the oceans absorb and release CO2. These conditions can shed light onto whether or not oceans can nullify or suppress anthropogenically released CO2. According to Ryabchikov [4], the intensity with which CO2 dissolves from the atmosphere into the oceans decreases as (ocean) temperature increases, but is proportional to the square of wind speed and the difference between CO2 partial pressures in the atmosphere and oceans. The mean CO2 concentration is about 0.01% by weight in the oceans and about 0.04% by weight in the atmosphere. Suppose that human activities pump significant CO2 into the atmosphere. Suppose further that the pumped CO2 increases the difference between CO2 partial pressures in the atmosphere and oceans over a period in which the oceans have

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not significantly warmed up (due to their relatively slow tendency to heat up). In this case the oceans may absorb atmospheric CO2 that is equal or comparable to that released by the human activities. This inference is supported by the fact that the oceans are capable of absorbing at least 80% of the CO2 generated by fossil fuel combustion [7]. In addition the rate of CO2 build-up in the atmosphere decreased during the mid-1960‟s although the rate of industrial CO2 emission correspondingly increased [8]. ans have not significantly warmed up (due to their relatively slow tendency to heat up). In this case the oceans may absorb atmospheric CO2 that is equal or comparable to that released by the human activities. This inference is supported by the fact that the oceans are capable of absorbing at least 80% of the CO2 generated by fossil fuel combustion [7]. In addition the rate of CO2 build-up in the atmosphere decreased during the mid-1960‟s although the rate of industrial CO2 emission correspondingly increased [8]. This CO2 decrease is apparently due to the maximisation in the 1960s of frequencies of Atlantic hurricanes, meridional hemispheric (wind) circulations and other wind patterns. The frequencies have been noted to vary at a period equal to that of the second harmonic of the 80 – 120 years solar cycle. These frequencies reached minima in 2000 – 2010 and are expected to proceed thereafter to the next maxima. These maxima are expected to occur in the 2030s. Analysis of records from Milton [125] shows that both cumulative deviations and frequencies of cyclones for south-west Indian Ocean, northwestern Australia, north-east Australia, bay of Bengal and north Atlantic apparently vary at a dominant period equal to that of the 80 – 120 years solar cycle. The last maxima of these cumulative deviations and frequencies occurred in the 1960s and early 1970s. When combined with the expected global cooling trend discussed in chapter 8, the observation just given above tells us the following. Absorption of atmospheric CO2 by the oceans will gradually increase with time from 2010 onwards. Note that variations in meridional hemispheric circulation, Atlantic hurricanes and some other wind patterns are related to the ISRC waves. Indeed the apparent ability of the oceans to partially or totally suppress anthropogenic CO2 build-up in the atmosphere is reflected in the oceans‟ huge capacity to vary CO2 releases and absorptions at amplitudes that exceed those of human activities. It is on this basis that all CO2 scenarios for general circulation or other climate models should be accompanied by estimates of corresponding releases and/or absorptions of CO2 by the oceans. The amount of CO2 in the atmosphere is regulated by the carbon cycle. This cycle involves temperature variations, precipitation variations, wind

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Introduction

15

speed patterns, oceanic circulations and volcanic activity, all of which are largely influenced by the ISRC oscillations (that include solar cycles). Thus as climate changes related to the ISRC waves take place, associated atmospheric CO2 changes also take place (eg. see Figure 1.7). But whereas natural temperature changes can cause changes in atmospheric CO2, human-generated atmospheric CO2 changes are limited by Kirchhoff‟s law of radiation and global radiative equilibrium conditions in causing global temperature changes. Specifically the increase in global average temperature by 0.6°C over the past 100 years can hardly be attributed to human-generated greenhouse gases (mostly CO2) for the following reasons. First, the temperature variations have patterns that are strongly related to the 400 – 550 years solar cycle, the 1000 1250 years solar cycle and the 80 – 120 years solar cycle (see Figures 1.2 and 8.4). Second, global mean temperature has not increased since 1999 although atmospheric CO2 has correspondingly been increasing by more than 0.5% per year. Third, half of the 0.6°C global temperature increase mentioned above took place from 1900 to 1940 when the rate of increase of atmospheric CO2 was only 0.1% per year. Fourth, the sharp rise in global mean temperature from 1970 to 1999 has not been accompanied by sharp rise in high latitude temperatures as predicted by GCMs. Figure 8.3(b) shows that greatest greenhouse warming between 1970 and 1999 did not take place in the Arctic as predicted earlier by GCMs. Even the whole post-1800 global warming trend can hardly be attributed to human-generated greenhouse gases to a large extent. The reason is that this global warming trend appears clearly to be part of long existing natural temperature oscillations which are strongly related to solar activity as illustrated in Figures 1.1, 1.2, 5.6, 5.12, 5.13 and 5.15. It is on this basis that all long-period global ISRC oscillations have been accompanied (in in-phase mode) by corresponding CO2 variations (eg. see Figure 1.7). These CO2 variations essentially adopt periodicities of the corresponding ISRC oscillations, but their waveforms are often exponential pulse waveforms. The ~874 years temperature oscillation in Figure 1.2 is made up of a falling phase of a 1000 – 1250 years oscillation and a rising phase of a 400 - 550 years oscillation. This approximately one-cycle ~874 years oscillation has been matched or accompanied by a corresponding CO2 oscillation. The latter CO2 oscillation exists as NAO waveforms (whose mean values are nearly constant) during the falling phase of the 1000 - 1250 years temperature oscillation (see Figure 1.8) and as SO waveforms during the rising phase of the 400 – 550 years temperature oscillation. The last falling phase of the 1000 - 1250 years temperature oscillation lasted from 1100 – 1200 up to 1625. This temperature phase has been accompanied by NAO waveforms of

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CO2 variations whose one hundred year running mean value should expectedly be nearly constant [2,83-86] as implied by Figure 1.8. Now the ongoing rising phase of the 400 - 550 years temperature oscillation started around 1625. This phase has been accompanied (from 1725 onwards) by SO waveforms of CO2 variations whose one hundred year running mean value has expectedly been increasing with time [2,83-86]. These carbon dioxide SO waveforms are expected to reach a maximum around 2060 and thereafter give way to NAO waveforms that will effectively halt the natural CO2 increasing trend. Note that humans started injecting CO2 into the atmosphere around 1870, some 145 years after nature had started the ongoing rising phase of CO2 variations in SO waveform. So we now realise that between about 1100 and about 1625, atmospheric CO2 was varying significantly in NAO mode as part of a 1000 1250 years period waveform. If one hundred year running mean is calculated over the NAO waveform, what would obviously result is a nearly constant curve as shown in the literature. But such a nearly constant curve should not be interpreted as absence of sizable variations of atmospheric CO2 over the period involved. Apparently there are two main factors that have misled several authors into believing that humans are mostly responsible for the post – 1700 increase in atmospheric CO2. The first factor is unawareness of existence of the NAO waveforms in CO2 variations that existed before about 1725. The second factor is the near coincidence of the effective end of these NAO waveforms with the start of the Industrial Revolution. It is after this particular end that natural atmospheric CO2 variations started on a rising phase of an SO waveform. All the CO2 increases with time since 1725 popularly reported in the literature are actually part of the (rapid) rising phase of an approximately 400 - 550 years period exponential pulse waveform as already detailed earlier. This rapid rising phase has been contributed by both natural processes and anthropogenic activities since 1870, nothing that the mainstream waveform involved exists naturally before and after 1870. So human activities have been “assisting” nature in accelerating the above-mentioned rapid rising phase of atmospheric CO2, a phase which is expected to end at around 2060. There is no argument at all against the fact that human activities have been increasingly injecting CO2 into the atmosphere since 1870. Over the last 40 years, concentration of atmospheric CO2 varied from about 315 to about 360 ppm by volume. In comparison, concentration of atmospheric CO2 over the earlier 200,000 years varied from 200 to about 300 ppm by volume. It happens that the post – 1870 anthropogenic injections of CO2 into the atmosphere (which have gradually increased with time) have formed a rising phase which

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Introduction

17

has combined additively with the post – 1725 natural (rapid) rising phase of the 400 - 550 years cycle of atmospheric CO2 concentration. Thus the former anthropogenic rising phase has been effectively amplifying the latter natural rising phase. The amplified version of the latter rising phase will reach an abnormally high maximum by the time it reaches its end at the next maximum of the 400 - 550 years oscillation in atmospheric CO2 which is expected to occur around 2060. Thereafter the rising phase will give way to NAO waveforms in atmospheric CO2. As implied earlier, the variation patterns associated with the 400 - 550 years oscillation in atmospheric CO2 oscillation will then take the form of lowered NAO waveforms (comparable with those illustrated in Figure 1.8) for about 270 years after 2060. These NAO waveforms will inevitably give rise to the following two occurrences during their existence. First, global temperature will correspondingly decrease after 2060 since the CO2 NAO waveforms will coincide with the falling phase of the 400 - 550 years temperature oscillation. Second, the post – 2060 NAO waveforms in atmospheric CO2 will take the form of a mean CO2 level (much lower than the 2060 CO2 peak) about which relatively short-period CO2 variations oscillate. This means that atmospheric CO2 generated by humans over the 270 years period after 2060 will not significantly increase the mean CO2 level in the atmosphere. Instead it will increase the amplitudes of the natural CO2 oscillations about this particular CO2 mean level. By comparison the human-generated atmospheric CO2 from 1870 to about 2060 expectedly has had the effect of increasing the amplitude of the rising phase of the natural 400 - 550 years oscillation in atmospheric CO2. What is generally realised and concluded in this case is as follows. Human-generated atmospheric CO2 generally amplify (and sometimes distort) existing natural oscillations of atmospheric CO2. A similar conclusion is reached in chapter 6 concerning the influence of any human-generated greenhouse warming on corresponding natural temperature oscillations. However, human-generated greenhouse warming is suppressed by Kirchhoff‟s law of radiation as explained in chapter 2.

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Figure 1.8: An idealised fitting of the NAO in CO2 variations discussed in the text (see the vertical oscillations) onto graphical plots of atmospheric CO2 reported in Houghton et al.[85]. Except for the idealised NAO, the rest of the diagram has been gratefully reproduced with permission from Houghton et al.[85].

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Chapter 2

BASIC SCIENCE ON WHICH THE CLIMATE SYSTEM OPERATES

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2.1. STRUCTURE AND MOTIONS OF THE CLIMATE SYSTEM The climate system has been defined in Section 1.4. According to this definition, the climate system is simply made up of the earth‟s atmosphere and the topmost layer of the solid earth. If we look at all the established layers of the solid earth we will find that the topmost layer is called crust. This particular layer (which extends from the earth‟s surface down to a depth of about 30 kilometres) supports and contains all the climatically important water bodies, ice masses, snow accumulations and land masses along the earth‟s surface. It is, therefore, fitting and proper to refer to the climate system as crust-atmosphere system or in short form CAS. The CAS continuously rotates (infront of the Sun) about the Earth‟s geographical axis at a period of 23.93 hours. This rotation creates day-andnight sequences. Together with the Earth, the rotating CAS also orbits or revolves about the Sun at a period of 365.256 days. This revolution (or orbit) traces a slightly elliptical path with mean distance from the Sun of about 1.496 x 108 km. Due to its ellipticity, the CAS‟s orbit around the Sun has an eccentricity (ie. a measure of how an orbiting path deviates from a circle) ranging from 0.0005 to 0.0607. Its present value is 0.0167. The eccentricity varies rather sinusoidally at a period of about 100,000 years as a result of gravitational forces within the solar system. Over the entire ~100,000 years eccentricity cycle, the solar radiation incident onto the CAS varies by no more that 0.1%. Over the same cycle the seasonal variation of the latter solar

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radiation changes by up to ~30%. Currently it is changing by about 7% (ie. by ±3.5% about a mean value). Another motion of the CAS is connected with the angle between the Earth‟s axis and the normal to the plane of the Earth‟s orbit. This angle (which is called obliquity of the ecliptic) is not zero, that is, the Earth‟s axis is tilted. This tilting gives rise to the seasons and changes in the length of daylight within a year. Due to gravitational forces in the solar system, the obliquity of the ecliptic varies cyclically between 21.5o and 24.5o at a period of 41,000 years. At present the angle is 23.5o. Variations in the obliquity of the ecliptic do not change the amount of solar radiation incident onto the CAS. Instead these variations give rise to changes in the latitudes of the polar circles and the tropics. They also introduce some temperature differences between the northern and southern hemispheres. In introducing the last motion of the CAS, we note that the Earth is pearshaped. This pear-like shape makes the rotating Earth appear like some form of “gyroscope”. The Moon‟s torque that is continuously exerted on this “gyroscope” makes the axis of the Earth twist around, causing the so-called precession. This precession is defined as the process by which the Earth‟s axis traces cone-shaped paths when viewed from above the north pole. Precession (which is also known as “precession of the equinoxes”) takes place at a period of 25,800 years. It does not change the amount of solar radiation incident onto the CAS. However, it changes the season in which the CAS is closest to the Sun. We note generally that the CAS‟s motions are tied onto the Earth‟s rotation and variations of the Earth‟s orbital parameters (ie. parameters of the Earth‟s rotational geometry). These parameters are: period of a complete orbit, eccentricity of the orbit, obliquity of the ecliptic and precession of the equinoxes.

2.2. ENERGY INPUT AND DISTRIBUTION IN THE CRUST-ATMOSPHERE SYSTEM About 99.98% of the thermal energy continuously incident onto the CAS comes from solar radiation. The remaining percentage comes from inside the Earth. Solar radiation (ie. shortwave radiation) at wavelengths 0.1 µm to 3.5 µm is continuously incident onto the (dayside) atmosphere. In this case the Sun emits out radiation as if it were a black body at a temperature of about

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5900 K. We use the phrase “solar constant” to denote the amount of solar radiation incident per unit time on unit area perpendicular to the radiation and placed at the centre of the Sun-Earth distance. The solar constant Sc ≈ 1360 Wm-2. Let us get an expression for the daily solar radiation Rd incident on horizontal unit area on top of the atmosphere at latitude . If δ is solar declination, zo is mean Sun-Earth distance, z is actual Sun-Earth distance and then

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(2.1) where Sc and Rd are in Wm-2. Derivation of equation (2.1) is given in standard books on climate such as Sellers [9], Peixoto and Oort [10], …etc. This equation (2.1) shows that Rd varies significantly with latitude. This latitudedependent variation of solar radiation incident onto the CAS is further illustrated in Figure 2.1. Some of the solar radiation incident onto the CAS is reflected back to space, depending on the reflection coefficient (ie. albedo). For the CAS as a whole, albedo ≈ 0.34. And for the earth‟s surface as a whole, albedo ≈ 0.11. Knowledge of the overall CAS albedo enables us to estimate the fraction of solar radiation absorbed into the CAS. About 70% of the solar radiation incident onto the CAS is absorbed while the remaining ~30% is reflected into space. About 69% of the solar energy absorbed into the CAS enters onto the Earth‟s surface. It is this particular energy which: (i) Differentially heats up the surface and atmosphere, thus setting up atmospheric and oceanic motions under the influence of the Earth‟s rotation; and (ii) Gives rise to physical evaporation, transpiration and photosynthesis. The remaining part of the CASabsorbed solar energy is absorbed into the atmosphere by clouds, water vapour, ozone and dust particles. Most of the solar radiation is, therefore, absorbed at the Earth‟s surface, in the ozone layer and in the thermosphere. In reality the CAS albedo varies with latitude as illustrated in Figure 2.2. If you want to get the pattern of solar radiation absorbed daily at each latitude, this is what you should do. Take from Figure 2.2 a pattern of latitudinal distribution of “1 – albedo” and multiply that pattern with the incoming energy pattern shown in Figure 2.1. At the end of this exercise you will realise that there is generally a latitudinal gradient in the solar radiation absorbed into the surface –

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atmosphere system (SAS). In this absorbed energy gradient (which also creates a temperature gradient), a maximum occurs in the tropics while two minima occur at the poles. Heat is transferred from regions with abundant heat to regions with relative heat deficit through winds and ocean currents.

Figure 2.1. Total solar radiation (in 106 Jm-2) incident daily on horizontal unit surface area at different latitudes. Areas that are not illuminated by the sun are shaded. Reproduced by kind permission from Wallace J. M. and Hobbs P. V. (1977): Atmospheric Science: An Introductory Survey, Academic Press, New York.

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60

40

20

Average 90 60

30 S

0

30

60 90 N

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Figure 2.2. Variation of global albedo (%) with latitude. Reproduced by kind permission from Vonder Haar T. H. and Suomi V. (1971); Journal of Atmospheric Science, vol. 28, pp. 305 – 314.

As it is receiving energy from the Sun, the SAS also emits terrestrial (or longwave) radiation at wavelengths from 4 µm to 80 µm. This radiation is given out in accordance with Stefan-Boltzmann law. This law states that a body at absolute temperature T radiates out heat at a rate HR given as (2.2) where A is the surface area of the body, ε is the emissivity of the body, and . The outgoing terrestrial (or longwave) radiation is partly absorbed by atmospheric water vapour, carbon dioxide, aerosols, methane and others. This absorption gives rise to the so-called greenhouse effect. By definition, greenhouse effect is the phenomenon by which outgoing longwave radiation is trapped. On yearly or longer averages the CAS is approximately in radiative equilibrium. This means that:

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(2.3)

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Ernest C. Njau

It is no wander, therefore, that the mean surface temperature of the Earth has remained at 286 to 288 K for a long time. It is important, notably for climate modellers using general circulation models, to realise that the surface-atmosphere system (SAS) below an altitude of 60 – 70 km. obeys Kirchhoff‟s law of radiation [11,12]. This law for the SAS part just mentioned above is represented by the following equation:

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(2.4) A simple interpretation of equation (2.4) is as follows. Suppose humangenerated greenhouse gases enter the atmosphere and trap outgoing longwave radiation. This trapping process effectively decreases the emissitivity with respect to longwave radiation. According to equation (2.4) the albedo should consequently be increased so as to reduce absorptivity with respect to shortwave radiation. In other words, trapping of outgoing longwave radiation is matched by blocking entry into the CAS of an equal amount of incident solar radiation. Equations (2.3) and 2.4 are obeyed, and yet global air temperature and sea-surface temperature change significantly. Why? While residing into the CAS before being sent into space as longwave radiation, some of the solar energy absorbed into the CAS is made to oscillate at frequencies related to solar activity, the seasonal cycle and the ~100,000 years cycle mentioned in Section 2.1 (see also chapter 5). These energy oscillations have spatial wavelength structures that are consistent with the resonant modes of the CAS. It is positionings of the energy structures (notably their maxima and minima) that mainly determine the corresponding global air or sea-surface temperatures. These positionings and the associated oscillation frequencies are determined solely by natural processes. Human activities have no hand in this (as elaborated in chapter 5) although they influence amplitudes of the oscillations.

2.3. GENERAL CIRCULATIONS OF THE ATMOSPHERE AND OCEANS Both atmospheric and oceanic general circulations, which form the key physical basis of climate, are driven by differential heating of the earthatmosphere system by absorbed solar energy. Atmospheric winds and oceanic currents are, therefore, forced to flow as a result of attempts by the earth-

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atmosphere system to reach equilibrium conditions. As noted in the previous Section, the Sun heats up the equatorial belt more than the other regions of the globe. As a result, a generally warmest zone called intertropical convergence zone (ITCZ) continuously exists in the equatorial belt. Notably along oceans, the ITCZ has highest temperatures and shifts with the zenithal position of the Sun. Thus the seasonal shifts of the Sun‟s zenithal position make the ITCZ move seasonally between latitude 5o S (in January) and latitude 20o N (in July) as illustrated in Figure 2.3. Note that the annual march of the ITCZ lags behind the Sun‟s zenithal position march by two months. Of course even the global wind belts, pressure systems and ocean currents discussed later on in this Section also shift seasonally with the Sun‟s zenithal position march. Climate and weather in tropical regions are significantly affected by the ITCZ‟s seasonal shifts. It is these shifts that greatly give rise to the monsoon winds in tropical regions. Remember that monsoons are the lower branches of convection air currents set up between major continents and adjacent oceans. They flow towards the continents in summer and towards the oceans in winter. Specifically the summer rainfalls in India, Central America, Southeast Asia and North Africa are caused by the ITCZ‟s northward shifts. Earlier in this Section we mentioned general factors that give rise to winds and ocean currents. Here we will go further by looking in details at the physical laws and processes involved. Both air in the atmosphere and water in the oceans obey the following:180° 40° N 20° N EQ 20° S

180°

0° July

40° N 20° N

July EQ

January January

40° S

20° S 40° S

Figure 2.3. Seasonal variations of the intertropical convergence zone (ITCZ). Reproduced with kind permission from page 248 of Moran J. M. and Morgan M. D. (1989): Meteorology, Macmillan Publishing Company, New York.

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Ernest C. Njau Archimede‟s principle in the sense that warm air (or water) is lighter than adjoining air (or water) and hence it rises up. ii. Continuity equation in the sense that a stream of air or water includes no discontinuities. i.

It is on the basis of Archimede‟s principle that the air along the ITCZ is always rising up and hence creating a low pressure zone. Also the cold air at the poles is always sinking down thus creating high pressure areas. A number of thermally driven convection currents with rising and falling arms also exist in the oceans. Due to the continuity equation, the falling air at the poles is part of falling phases of two circulation cells near each pole. Also the rising air at the ITCZ is part of two circulation cells (one in each hemisphere) as will be illustrated later on. Due to the Coriolis force mentioned in (ii) below, the upper poleward arm of each of these two circulation cells cannot flow straight to the pole. It will have to fall down somewhere before reaching the pole. The fall takes place at a high pressure belt. You can see now that at least one circulation cell should exist in each hemisphere between the cell near the ITCZ and the cell near the pole. So there are three circulation cells in each hemisphere. Air in the atmosphere is forced to move by the following forces.

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i.

Pressure-gradient force. The pressure-gradient force Fp acts on air along a direction perpendicular to the isobars towards low pressure. If ρ represents air density, P represents air pressure and Δn is the distance between two isobars, then Fp is given vectorially as: (2.5)

Air flows clockwise around a high-pressure centre in the northern hemisphere and anti-clockwise around the same centre in the southern hemisphere. Also air flows anti-clockwise around a low-pressure centre in the northern hemisphere and clockwise around the same centre in the southern hemisphere. ii. The Coriolis force. The Earth‟s rotation makes an air parcel moving in the atmosphere (say, at velocity v) to appear as being acted upon by a force called Coriolis force Fco. If Ωe represents the Earth‟s angular velocity (which is directed parallel to the Earth‟s axis outward from the north pole), then

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and

(2.7)

You are likely to come across “Coriolis parameter” in some books. This parameter is simply 2Ωesin . Note also that air

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moving under the condition that the Coriolis force balances the pressure-gradient force is called geostrophic wind. iii. Forces that form thermal wind. Generally warm regions display lower atmospheric pressure than relatively cold regions. Therefore a horizontal temperature gradient is often accompanied by a horizontal pressure gradient. It follows that existence of horizontal temperature gradient gives rise to pressure gradient at higher levels. This pressure gradient varies with height, leading to corresponding variation of the velocity of the geostrophic wind with height. The latter variation gives rise to another type of wind called “thermal wind” whose primary cause is the horizontal temperature gradient. The speed VT of the thermal wind is given as

(2.8) where T is mean temperature, x is horizontal distance and fc is the Coriolis parameter. Thermal wind (or vertical wind shear) flows along isotherms with cold air to its left in the northern hemisphere and warm air to its right in the southern hemisphere. iv. Centripetal forces. A body moving in a circle is enabled to do so by a force that is directed towards the centre of the circle. The force is called centripetal force, and it gives the circling body some centripetal acceleration. v. Frictional forces. Air moving horizontally below an altitude of about 1.5 km. experiences frictional forces that change its speed and direction. These forces are due to friction between the air and the Earth‟s surface or topography.

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Now let us apply all the forces and processes given so far in this Section to the earth-atmosphere system discussed in Section 2.2. If we do this, what will result are the following. High 60° Stormy

Low Westerlies

Calm

30° Subtropical high Trade winds

Doldrums

Low

0°

Trade winds

Calm

Subtropical high

30°

Westerlies

Stormy

Low

60°

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High Figure 2.4. Observed zonal wind systems near the Earth‟s surface. Reproduced by kind permission from page 177 of Petterssen S. (1969): Introduction to Meteorology, McGraw-Hill Book Company, New York.

i.

The pressure belts, surface winds and meridional general circulation in the troposphere illustrated in Figures 2.4 and 2.5. Low pressure belts are centred at latitudes 0° and 60° N and S. Also high pressure belts are centred at latitudes 30° and 90° N and S. In Figure 2.5 the circulation cell closest to the equator in each hemisphere is called Hadley cell. Also the circulation cell closest to the pole is called polar cell. That circulation cell sandwitched between the Hadley and a polar cell is called Ferrel cell. The surface winds shown in Figure 2.4 are the lower arms of the Hadley cells, Ferrel cells and polar cells shown in Figure 2.5. For example, the winds along the lower arms of the Hadley cell, Ferrel cell and polar cell in the northern hemisphere are called N.E. trade winds, south westerlies and north easterlies, respectively. And those in the southern hemisphere are called S.E.

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trade winds, north westerlies and south easterlies, respectively. It is established in chapter 5 that the meridional tropospheric general circulation in Figure 2.5 is only part of a bigger and more complex system. This system is made up of three types of general circulation placed one on top of the other and extending from the Earth‟s surface up to the magnetosphere. A clearer connection between Figures 2.4 and 2.5 may be obtained as follows. Look at the six meridional circulation cells represented in Figure 2.5. The causes of these cells have been given and explained earlier in this section. Now with these cells in existence, consider that the Earth is rotating from west to east. If we apply coriolis forces to the motions in the cells, the results will obviously be as follows. All the cells in the northern hemisphere will each rotate slightly about a vertical axis in a clockwise direction (as viewed from above). Also each cell in the southern hemisphere will rotate slightly in an anticlockwise direction. After all these slight rotations, the lower arms of the cells will form the surface winds illustrated in Figure 2.4. ii. The major (surface) oceanic currents in Figure 2.6. These currents are horizontal and are approximately located between the equatorial belt and a polar region. Since the area covered by the oceans in the northern hemisphere is different from that in the southern hemisphere, the ocean currents in Figure 2.6 are not symmetrical about the equatorial belt. Note that those ocean currents bordering the equatorial belt in the northern hemisphere are mostly clockwise (as viewed from above) while those in the southern hemisphere are mostly anti-clockwise. This is mostly due to coriolis forces acting on poleward water flows from the equator. Of course those ocean currents that border the equatorial belt rotate in a direction opposite to that of the latter currents. iii. Atmospheric jet streams. By definition an atmospheric jet stream is a relatively small core of strong wind which normally circles the Earth. There are two conditions which form a jet stream, namely: sufficiently large meridional temperature gradient and rotation (with the Earth) of underlying surface. These two conditions exist in some parts of the surface-atmosphere system and have been forming two types of jet streams. In the first type are two mesospheric jet streams at altitudes of about 60 km. near latitudes 30° N and 30° S. These jet streams reverse directions

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Ernest C. Njau from summer to winter. In the second type of jet streams are four west-to-east moving jet streams located at the top of the troposphere. Two of these jet streams (called polar front jet streams) are located around latitudes 45° N and 45° S. The remaining two (called subtropical jet streams) are located between latitudes 25° and 35° north and south of the equator. iv. Existence of maximum rainfall along latitude 7° N due to the ITCZ and a specific pattern of rainfall around the globe. v. Long waves in the upper westerlies (called Rossby waves). vi. Annual rainfall minima at the poles and at latitudes 30°N and S. Also annual rainfall maxima at latitude 7°N and latitudes 45°N and S. While the rainfall maxima coincide with generally rising air, the rainfall minima coincide with generally descending air. vii. Evaporation minima at 7° N and at the poles. Also evaporation maxima at 30° N and S. viii. Annual cloud cover maxima at latitudes 0°, 60° S and 55 – 90° N. Also annual cloud cover minima at latitudes ~ 22° N and S as well as at the south pole. ix. Stratospheric warmings. By definition stratospheric warming is the phenomenon by which abnormally large warming takes place in the polar stratosphere during certain groups of days in winter. It is apparently associated with passages of peaks of the GHW (see chapter 5) along the winter-experiencing stratosphere.

2.4. ANTHROPOGENIC DISTURBANCES ON THE CLIMATE SYSTEM So far this chapter has considered only natural scientific aspects associated with the climate system. But we all know that human activities that modify certain parameters or characteristics of the climate system have been increasing since the start of the industrial revolution. Already there is global concern that humans are creating unwanted changes in climate, stratospheric ozone and atmospheric composition.

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Basic Science on which the Climate System Operates

31

Polar Easterlies POLAR FRONT ZONE Westerlies HORSE LATITUDES

Trade Winds

EQUATORIAL CONVERGENCE ZONE

Trade Winds

HORSE LATITUDES Westerlies POLAR FRONT ZONE

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Polar Easterlies

Figure 2.5. Schematic representation of the atmospheric general circulation. Reproduced by kind permission from page 219 of Byers H. R. (1974): General Meteorology, McGraw-Hill Book Company, New York.

To some extent this concern has been addressed through the 1985 Vienna Convention, the 1987/90 Montreal Protocol, the 1988 UNGA Resolutions, the 1992 United Nations Framework Convention on Climate Change, the 1994 United Nations Climate Change Convention, the 1995 Berlin Mandate, the 1997 Kyoto Protocol and its post-2012 replacement, the 1998 Buenos Aires Action Plan, the 2003 Moscow World Climate Change Conference Resolution and the 7 – 18 December 2009 Copenhagen Conference. Clearly a lot of efforts have been used to try to minimise human (undesirable) influences on climate and atmospheric composition. But in the case of climate, have we unquestionably mastered the science of climate change? And further more, have we fully understood the science on which human influence on climate is based?

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East Greenland

Murmansk

Irminger

ARCTIC CYCLE North Atlantic drift

West Greenland

60°N Alaska

Oyeshio

Norway

Labrador 45°

North Pacific

Gulf Stream California

Kuroshio

Florida

15°

Canaries S. Eq. C.

North Equatorial Equatorial Countercurrent

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0°

Guinea

Somali

C.C.

EQUATOR

S. Eq. C.

South Equatorial S. Eq. C.

15°

30°

Eq. C. C

Brazil

East Australia

S. Eq. C.

Benguela

Peru or Humboldt

Agulhas

West Australian

45° Falkland

60°S 120°E

West wind drift or Antarctic Circumpolar

West wind drift or Antarctic Circumpolar 180°

Key warm currents cool currents

120°W

60°W

0°

60°E

120°E

Figure 2.6 A map of the major surface currents in the world oceans during northern winter. Reproduced by kind permission from Tolmazin D. (1985): Elements of Dynamic Oceanography, Allen and Unwin, Winchester, MA.

Figure 2.6. A map of the major surface currents in the world oceans during northern winter. Reproduced by kind permission from Tolmazin D. (1985): Elements of Dynamic Oceanography, Allen and Unwin, Winchester, MA.

Basic Science on which the Climate System Operates

33

During the First Meeting of the Parties to the Kyoto Protocol (28/11/2005 – 10/12/2005, Montreal Canada), serious concerns were expressed on attempts by nations and voices to dismiss the reported science of climate change [13]. The view that the science of climate change has not been well understood continued to be echoed even some years thereafter [14]. Urgent efforts should, therefore, be used to adequately dig up the correct science of climate change that sufficiently takes into account human activities. In general, humans do influence climate changes through the following activities.

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i.

Emission of (waste) heat. The Sun-derived thermal energy which naturally runs the climate system is accumulated in the lower CAS. If human activities add some thermal energy in the lower CAS, this energy will combine with the corresponding energy from the Sun and be used by the climate system accordingly. Thus the human-generated thermal energy effectively amplifies the thermal energy available for use in running the climate system and climate changes [15]. This is the case because the climate system does not differentiate between thermal energy from the sun from thermal energy produced by humans. Besides the latter thermal energy takes part in all processes undertaken in the CAS by the former thermal energy except photosynthesis processes. More details on this aspect are given in Section 6.2 of chapter 6. ii. Emission of gases and airborne particles. Various activities done by humans release greenhouse and other gases as well as airborne particles (eg. from industrial and combustion processes). Greenhouse gases are those gases (such as CO2) that have ability to trap outgoing longwave (or infrared) radiation. The greenhouse gases decrease the emissivity for longwave radiation. As regards the airborne particles, these particles can change either the latter emissivity or the albedo for shortwave radiation. The climate system reacts or responds to the influences of human-generated gases and airborne particles according to relevant laws such as Kirchhoff‟s law of radiation as well as radiative equilibrium considerations. The climate system must not be assumed to be passive with respect to anthropogenic disturbances. Section 6.3 of chapter 6 gives more details on this issue. iii. Generation of electric, magnetic and electromagnetic fields. It is shown in chapter 7 that solar activity influences variations of earthquakes and volcanic activity through certain subtle

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Ernest C. Njau processes. These processes involve naturally generated electric and magnetic fields. Some of our energy and communication technologies involve generation of electric fields, magnetic fields and electromagnetic fields. In some cases human-generated electric fields and magnetic fields are comparable to and coincide with electric and magnetic fields used to naturally influence earthquakes and volcanic activity. In this way some human activities influence occurrences of earthquakes and volcanic activity, a realisation that has been known only recently [2]. Correspondingly the activities also influence climatic variations associated with volcanic activity. More details on this subject matter are given in chapter 7.

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So far global attention has been focused only on (i) above. It is urgently essential that global attention should be focused on (ii) and (iii) as well.

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Chapter 3

SOLAR ACTIVITY

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3.1. INTRODUCTION Solar activity is the periodicity of changes occurring on the Sun‟s surface (whose temperature is about 5900 K). This activity has already been associated with variations in the atmosphere and biosphere [16] as well as climate changes [17,18]. From chapter 5 onwards it is established theoretically and through records-analysis that most dominant players in climate changes are solar activity and variations in the Earth‟s orbital parameters. The latter parameters are dealt with in Section 2.1 of chapter 2. Before proceeding to the subsequent chapters (which involve solar activity), it would be useful to go through a brief account of the latter activity for simplicity purposes. This chapter, therefore, presents the brief account just mentioned above.

3.2. HOW SOLAR ACTIVITY IS MEASURED There are a number of indices for measuring solar activity. All these indices represent changes along (or associated) with the Sun‟s surface. The outermost layer of the Sun (called corona) emits radiation that varies with solar activity. Therefore coronal radiation is one of the possible measures for solar activity. Solar activity can also be measured by solar flares (ie. large bursts of energetic particles and radiation), solar radio emissions and faculae (ie. bright spots on the Sun‟s disc). Of all the available indices for measuring solar activity, the most popularly used is the number of sunspots (ie. dark spots

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Ernest C. Njau

on the Sun‟s disc). The number increases and decreases with solar activity. Sunspot number as a measure of solar activity was introduced by R. Wolf in 1847. Records of sunspot number exist in the form of: daily data from 1818 onwards, monthly means from 1749 onwards and yearly means from 1700 onwards. This long record of sunspot number has been extensively used in studies which attempt to relate climate changes to solar activity. Studies based on the sunspot number records mentioned above cannot extend earlier than 1700. This condition limits climatic periodicities or variabilities that can be related to corresponding solar activity. Fortunately some techniques are available through which sunspot numbers may be estimated in absence of actual records of such numbers. One of these techniques uses data on deviations of carbon – 14 to estimate corresponding numbers of sunspots [19]. On the basis of this particular technique, estimates of sunspot numbers are available dating as far back as 5400 BC.

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3.3. THE SOLAR WIND The Sun is slowly losing mass. It loses mass by continuously sending out in all directions a stream of very hot protons, electrons and other atomic particles as well as magnetic fields altogether called solar wind. But why does the Sun (whose 92.1% of mass is made of hydrogen) lose mass? It is because it continuously produces nuclear energy through the following reaction: Hydrogen → Helium + Energy + Loss of mass. It is this nuclear reaction which produces the energy given out by the Sun. The reaction also makes the Sun lose 4000 million kilogrammes of mass every second. Of course this rate of mass loss is not worrying because the Sun has total mass of 1.99 x 1030 kg. This lost mass fastly flows out as solar wind. The solar wind velocity increases as distance from the Sun increases. When it is flowing past the Earth, the solar wind has velocities of 400 to 1000 km. per second and a temperature of about 200,000 K. It takes the solar wind about 4.5 days to flow from the Sun to the Earth.

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37

20 DEC. 0300

1 DEC. 0300

SUN 4 DEC. 2100

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12 DEC. 1200

Figure 3.1. Magnetic sectors (four in number) whose magnetic field either points towards the Sun (see the negative signs) or points away from the Sun (see the positive signs) as reported in late 1963. Adapted by permission from Wilcox J. M. (1968): “The interplanetary magnetic field, solar origin and terrestrial effects”, Space Sci. Rev.8, p. 258. ©Reidel Publishing Co.

As it continuously flows onto and past the Earth, solar wind pushes onto the Earth‟s magnetopause. During the day some solar wind streams manage to penetrate the magnetopause and enter into the magnetosphere. There are two further points worth noting in connection with the solar wind. First, the velocity, density and momentum of solar wind change with the sunspot number. Second, solar wind velocity is directly proportional to terrestrial magnetic disturbances. The Sun (which generates its energy through thermonuclear reactions) rotates along a direction similar to the Earth‟s rotational direction. Note here that the Sun rotates not as a solid body but as a fluid. Its rotational period varies from about 35 days for the polar region to about 27 days for the equatorial region.

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Ernest C. Njau

SUNSPOT NUMBER

240

160

80

0 1610

1650

1690

1730

1770

1810

1850

1890

1930

1970

TIME IN YEARS

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Figure 3.2. The 11-years solar cycle (see solid-line curves) and the 80 – 120 years solar cycle (see thick dashed curves) from 1610 A.D. onwards. The solid-line variations have been reproduced by kind permission from Eddy J. A. (1980): The Ancient Sun, Pergamon Press, New York.

The Sun has a magnetic field whose field lines are stretched out by the solar wind to form the interplanetary magnetic field. Look at Figure 3.1 and note the Sun‟s direction of rotation. Since the Sun has north and south magnetic poles, the magnetic field lines stretched out of it must point either towards the Sun or away from the Sun. The stretched out magnetic field lines form spiral patterns as the Sun rotates. These spiral patterns are frozen into the radially out-flowing solar wind. Those magnetic field lines associated with the spiral patterns mentioned above alternate their directions between towards-thesun direction and away-from-the-sun direction. The alternating period is about 27 days. Due to this alternation process, the solar wind stream is always divided into regions each having a single magnetic field direction. These regions are called “magnetic sectors” and are separated by sector boundaries (Figure 3.1). Each magnetic sector has its own physical characteristics.

3.4. SOLAR CYCLES A cyclic variation at the surface of the Sun is called a solar cycle. Such a cyclic variation is also called “sunspot cycle” if it is measured using variation of sunspot number. A look at records of sunspot number variations shows that these variations have a number of periods, each corresponding to a solar (or sunspot) cycle. For example, the oscillations plotted in Figure 3.2 using solid

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39

lines represent the 11-year solar cycle. The cycle has a period of about 11 years. Each complete 11-years cycle is bounded by two adjacent minima and is given a specific number. For example, the cycle extending from the 1976 minimum to the 1986 minimum is called “solar cycle 21”. And the subsequent cycles are called solar cycle 22, solar cycle 23, solar cycle 24, … and so on. Specifically the current cycle, which started in 2008 and is expected to end in 2019, is called solar cycle 24. Now the amplitudes of the 11-year cycle are varied at a period of 80 to 120 years. This implies existence of an 80 – 120 years solar cycle (see Figure 3.2). A 22 – years solar cycle (also called double sunspot cycle) exists based on two processes. The first process is reversal of the Sun‟s magnetic field polarity at the start of each 11-years solar cycle. And the second process is amplitude-modulation of the 11-years solar cycle at a period of 22 years (eg. see Figure 3.2 from 1848 to 1937). Other solar cycles that have been identified in sunspot number records have the following periods: 7 days, 23.4 days, 27 days, 51.4 days, 13 months, 17 months, 170 – 250 years and 400 – 550 years. The 170 – 250 years solar cycle is plotted in Figure 7.7 of chapter 7. Past records of carbon-14 variations have enabled estimations of solar activity as far back as 5400 B.C. (see Figure 3.3). The areas having vertical line shadings represent a series of 11-years solar cycles. Analysis of the variations in Figure 3.3, has led to establishment of other solar cycles at the following periods: 874 years, 1000 – 1250 years, 2300 – 2700 years, about 5000 and about 10,000 years. Little Ice Ages coincide with minima of the solar cycle with a period of 2300 – 2700 years. The solar cycle with the latter period is plotted in Figure 3.3. Spectral analysis shows that from 1100 onwards, the sunspot number variations in Figure 3.3 display major oscillations at periods 843 – 874 years and about 350 years. Apparently the 843 – 874 years period is equal to that of the third harmonic of the 2300 – 2700 years solar cycle. Also the ~350 years period is equal to that of the third harmonic of the 1000 – 1250 years solar cycle. All solar cycles, the annual cycle and the 100,000 years cycle in the eccentricity of the Earth‟s orbit discussed in chapter 2 give rise to small variations in the solar radiation incident onto the Earth‟s atmosphere. These cycles will hereinafter be referred to as incident solar radiation changing cycles (or ISRC cycles). The percentage changes in the solar radiation incident onto the atmosphere associated with the annual cycle and the 100,000 years cycle are (currently) 7% and ~ 0.1%, respectively. Percentages associated with the solar cycles range from 0.04% to 0.6%. These percentages are really small,

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but it is proved in chapter 5 that these cycles significantly influence climate changes through a natural “amplification process”. It is unawareness of this amplification process which made all the 1990, 1995, 2001 and 2007 IPCC reports incorrectly present solar activity as an insignificant driver of climate changes. This point of view has been presented and elaborated in details recently [2,15]. If we were to consider climatic periodicities longer than one million years, then we would have to take into account influences of the Sun‟s evolution and galactic dust. The solar system circles the Milky Way galaxy at a period of 250 million years. During this circling motion, the sun passes through galactic dust which may change the solar radiation reaching the Earth‟s atmosphere.

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3.5. MATHEMATICAL REPRESENTATION OF SOLAR ACTIVITY Consider again the following string of solar cycle periods already given in the previous Section: 11 years, 22 – 23 years, ~ 50 years, 80 – 120 years, 170 – 250 years, 400 – 550 years, 1000 – 1250 years, 2300 – 2700 years and ~ 5000 years. Approximate and mean values of these periods can be represented by Ps(n) in years such that (3.1)

Figure 3.3. A plot of long-term envelope of possible sunspot cycle since 5400 B. C. (see series of vertical lines) as deduced from data on deviations in carbon-14. The dashed curve represents the 2300 – 2700 years solar cycle. The solid curve represents the average of the 2300 – 2700 years oscillations. The patterns of vertical lines have been reproduced by kind permission from Eddy J. A. (1977): “Climate and the changing Sun”, Climatic Change 1, 173 – 190.

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where cs ≈ 0.18 and n = 0, 1, 2, 3,….. . To verify equation (3.1), let us substitute 0 to 8 for n in this equation. Thus if n = 0 to 8, Ps(n) = 11 years, 22 years, 47 years, 101 years, 222 years, 496 years, 1119 years, 2540 years and 5765 years. Each of these periods is approximately equal to an observed solar cycle periodicity or a mean period of an observed frequency band of solar activity. On the basis of Waldmeier‟s empirical formulae for solar activity, the period T11(t) and peak-to-peak amplitude A11(t) of the 11-years solar cycle are approximately related as

(3.2) Equation (3.2) shows that T11(t) decreases as A11(t) increases. Figures 3.2 and 3.3 show that oscillations at the periods (>11 years) represented by equation (3.1) somehow amplitude-modulate the 11-years solar cycle. That is, they modulate A10 (see equation 3.4). According to equation (3.2), these same oscillations also frequency-modulate the 11-years solar cycle. That is, they modulate the frequency

of the latter

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cycle, where T10(t) is T11(t) in which A11(t) is replaced by A10(≈100). Let Also let function S11(t) be expressed mathematically as follows:

(3.3) where en,

, gn and cn are parameters that vary with n, Aoo (≈ 0) is a constant

and βs is a phase term. Reasons for choosing the form of S11(t) shown in equation (3.3) are given at the end of the chapter.

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The 11-years solar cycle and its variability can, therefore, be represented by Se(t) such that

(3.4) Since equation (3.3) represents nonlinear harmonic oscillator processes, there are processes inside the Sun represented by Si(t) in equivalent units other than sunspot number such that

(3.5)

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where

is a parameter that depends on conditions inside the sun. The

situation represented by equations (3.4) and (3.5) may be somehow compared with a fish oscillating nonlinearly about the ocean surface along the vertical direction. Those observers at and above the ocean surface will see only the fish‟s oscillations in the air. The other oscillations will form inside the ocean water and be seen by observers below the ocean surface. Note that variations Se(t) and Si(t) are out of phase with each other. So when there are no sunspots (ie. when Se(t) = 0) the Sun is not actually “quiet” as reported in several textbooks because Si(t) is maximum at that time. Unfortunately Si(t) cannot be measured by sunspot number as in the case of Se(t). Equation (3.4) is a realistic mathematical representation of the 11-years solar cycle for the following three reasons. First, for all possible values of n, Sn(t) has variation periods ranging from 7.3 years to 17.1 years. This period range is obtained from equation (3.2) after replacing A11(t) with The period range so obtained is approximately equal to the observed range of periods for the 11-year solar cycle. Second, when n = 1, WL(1) = 0.14 radians per year. And as n → large values, WL(n) → 0. This implies that solar activity as represented by equation (3.4) is limited in effective periodicity to no more than about 13,097 years when n = 9. This inference is in line with the report in Lamb [82] which says that the Sun‟s activity varies up to a period of about 10,000 years. The third reason is that equation (3.4) indicates existence of mutual dependence (ie.

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significant correlation) between the instantaneous amplitude and frequency of Se(t). This implies that the 11-years solar cycle is generated by a driven nonlinear harmonic oscillator mechanism as suggested by models. The brief account given above does not involve those sunspot variations at the following periods: 7 days, ~ 27 days, 51.4 days, 13 months and 5.5 years. Influences due to all these periodic variations obviously interact with corresponding influences due to the solar activity represented by equation (3.4). The interaction may involve NAO modes or SO modes whose mathematical representations can be easily formulated. In ending the chapter, we recall that equation (3.3) was given without reasons and a physical basis. What follows, therefore, is an explanation of why the mathematical form of S11(t) in equation (3.3) has been specifically chosen. On the basis of standard books on Amplitude Modulation Processes, the patterns shaded by vertical lines in Figure 3.3 clearly represent the positive side of an amplitude-modulated waveform XAM(t) with modulation indices going up to 100%. Figure 3.2 shows that the basic carrier signal in XAM(t) is the 11-years solar cycle. Furthermore the modulating waveforms in XAM(t) are deduced directly from the upper envelopes of Figures 3.2 and 3.3. Equation (3.2) indicates that the carrier signal just mentioned is also frequency modulated by the modulating waveforms. In addition, since models have shown that the 11-years solar cycle is generated by a nonlinear harmonic oscillator process, the positive patterns in Figure 3.3 are complemented by negative patterns that represent processes that are not detected through sunspot number. Without being conceptually or otherwise supplemented by corresponding negative envelopes, Figure 3.3 cannot fully represent a free harmonic oscillator operation. This is because when modulated, the oscillator essentially produces an output with both upper and lower envelopes. In the present case, the upper envelopes are positive (see figure 3.3) and the (missing) lower envelopes are negative. It is on the basis of the account just given that: (i) The right hand side of equation (3.3) represents a quasisinusoidal waveform which is nonlinearly amplitude and frequency modulated; and (ii) Parameter Aoo ≈ 0 in conformity with the structure of the patterns in Figure 3.3. This implies that the processes inside the Sun represented by Si(t) are relatively quite strong. These processes may be modulated convection motions, rotational motions, et cetera. The methodology used in this section to analyse Figures 3.2 and 3.3 may be similarly used to analyse some variations in volcanic activity (eg. those in Figure 6.2) and earthquake activity (eg. those in Figures 7.2, 7.5 and 7.8). Such analysis yields

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Ernest C. Njau

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important information about variations in heat/temperature patterns and/or related parameters inside the Earth. Efforts have been made to successfully represent the variation patterns in Figure 3.3 by mathematical expressions. Thereafter the mathematical expressions were used to forward extrapolate the patterns in Figure 3.3 up to year 3440 (see Figure 3.4). Note that the points in Figure 3.4 labelled A, B, C, D, E, F, G, H and I are located at years 1740, 1800, 2060, 2327, 2590, 2853, 3117, 3380 and 3440, respectively. It is from the timing of the peak labelled C that long-term global cooling is expected to start as detailed in chapters 5 and 8.

Figure 3.4: A forward-extension of the last non-zero sunspot number block in Figure 3.3 up to year 3440.

Forward extrapolation of the patterns in Figure 3.3 has been simplified by the following establishment. These patterns are dominated by the 2300 – 2700 years solar cycle (see dashed curve in the Figure) that oscillates about an equilibrium level of 85 to 127 sunspot number. Now the latter cycle is accompanied by its second and fourth harmonics in the following sequence. This cycle is accompanied by: its second harmonic from 5200 B.C. to 3400 B.C., its fourth harmonic from 3400 B.C. to 350 B.C., its second harmonic from 350 B.C. to 1450 A.D., and its fourth harmonic from 1450 A.D. onwards. This sequence apparently indicates existence of a solar cycle whose period is about 5,000 years. Available records show that while existence of the second harmonic lasts for about 1800 years, existence of the fourth harmonic lasts for

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about 3,000 years (eg. see Figure 3.3). This implies that the fourth harmonic (which started existing in 1450) will be in existence up to the next Little Ice Age and slightly beyond.

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Chapter 4

HISTORICAL DEVELOPMENT OF THE SCIENCE OF CLIMATE CHANGES UP TO 1990S

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4.1. INTRODUCTION New findings associated with the science of climate changes that were made between 2000 and 2010 have apparently revolutionalised the whole understanding and realities of what causes climate changes. Fundamental knowledge that changed the general direction of thinking and which paved the way for new lines of research in the science of climate changes was not known before 2000. The impacts made by the 2000 – 2010 scientific findings are so crucial and important that the whole science of climate changes may be divided into two parts. The first part includes all the scientific developments made in this area of science before 2000. This part may be termed “classical science of climate changes” for a reason comparable to that which made the pre-1900 physics to be termed “classical physics”. The second part includes the revolutionary developments made in this area of science in and after 2000. This particular part is called “modern science of climate changes” for a reason comparable to that which made the post-1900 physics to be called “modern physics”. The logic behind dividing the science of climate changes into classical and modern components will be clearer after reading through chapters 4 and 5. This chapter, therefore, deals with the classical science of climate changes which is a prerequisite for the modern science of climate

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changes. All the remaining chapters of the book then deal specifically with the modern science of climate changes.

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4.2. SCIENCE BASED MOSTLY ON THE EARTH’S ORBITAL GEOMETRY It was during ancient times that people started explaining the causes of climate changes through variations in parameters of the Earth‟s orbital geometry only. Records [20] show that the Greek philosopher Aristotle (384 – 322 B.C.) and other philosophers of his time believed that the Sun‟s radiation was constant. Furthermore they believed that climate changes were caused by variations in the solar radiation reaching the surface-atmosphere system due to the Earth‟s rotation and revolution around the Sun. This point of view was accepted up to few centuries after discovery of the sunspot in 1611. The idea of a non-changing solar radiation lasted until telescopes were discovered and used routinely to observe sunspots. It was in 1843 that variability of the number of sunspots was discovered. In 1847 Wolf introduced the sunspot number as a measure of variations in solar radiation. After variability of sunspot number was clearly noted, it was concluded once and for all that the solar radiation is (slightly) variable and not constant. Following the developments given above were attempts to explain longterm climate variations using corresponding changes in the Earth‟s orbital parameters, namely eccentricity, obliquity and precession of the equinoxes (see chapter 2). The first attempt along this direction was made by Adhemar [21]. Other attempts were later on made by Ball [5], Hildebrandt [5] and Ekholm [5]. However, it was Milankovitch [22] who first developed the mathematical theory on how variations in the Earth‟s orbital elements give rise to temperature changes and hence long-term climate changes. The theory establishes existence of temperature variations at a period of about 100,000 years. This theory though is not practically valid unless an amplification of temperature variations due to reflection of solar radiation by enlarging areas of snow and ice is taken into account. An additional and different amplification process is presented in the next chapter. Milankovitch‟s theory and associated calculations have eversince been improved and refined by Vernekar [23] and Berger [3,5] into versions that stand up to the present. In 1956 another theory of climate changes based on mountain building and the Earth‟s orbital variations was presented by Panofsky [24].

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The Milankovitch theory has been successful in accounting for long-term climatic variations at astronomical periodicities. But this theory fails to account for the rapidity of certain changes that accompany glacial-interglacial conversions. Berger [3,5] suggested that the rapidity just mentioned may possibly be accounted for using solar activity. Indeed the next chapter successfully accounts for the rapidity on the basis of solar activity.

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4.3. SCIENCE BASED ON DIRECT EFFECTS OF SOLAR ACTIVITY Introduction of the sunspot number as a measure of solar activity by Wolf in 1847 and the discovery of sunspot number periodicity by Schwabe in 1843 cemented the conclusion that solar radiation is variable. On this basis, researchers attempted to explain climate changes using direct influences of solar radiation variations. The very early hypothesis linking solar variations with climatic changes state that ice ages result from decreases in solar radiation [25]. This hypothesis was severely criticised by Simpson [26] who instead proposed his own theory that ice ages result from increases in solar radiation. Simpson‟s theory (which is alternatively referred to as the “hot-sun, cold-earth theory”) proposes that as solar radiation increases, evaporation, cloudiness, precipitation and storminess give rise to gradual formation of ice sheets provided that the amount of summer melting is less than the amount of winter snowfall. In applying his theory to explain the succession of glacial and interglacial periods within the Pleistocene Ice age, Simpson postulated two maxima and three minima of solar radiation [26]. Despite its general soundness, Simpson‟s theory was criticised in its details. For example, while it predicts that the Riss-Wurn and Gunz-Mindel interglacial periods should be wet and warm and the MindelRiss interglacial period should be dry and cool, available evidence indicates no major differences between the three interglacial periods. Moreover, Simpson‟s theory predicts that in the tropics, one pluvial period represents two glaciations instead of one as actually evidenced. These shortcomings led Willett [27] into modifying and hence improving Simpson‟s theory by postulating four solar maxima instead of two to explain the four glacial periods in the Pleistocene Ice Ages. This improvement made the theory agree better with the major climatic variations during geological history and thus earn support from a number of researchers.

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In 1949 Wil1et [27] pointed out that the only hope for satisfactorily explaining all the global climate changes lies in solar radiation variations. In fact, Willett believed that irregular solar activity can account for all the climatic cycles which have occurred since the Pleistocene epoch. The improved Simpson‟s theory mentioned above is specifically tailored for climatic variations in geological history such as the Pleistocene Ice Ages. In 1957 another theory tailored for climatic changes in geological history was presented by Flint [28]. This theory is based on changes in solar radiation as well as mountain building. Before the advent of satellite observations, research on theories and physical mechanisms commonly tailored for short-term (10 to 100 years) and long-term (103 to 105years) in a unified manner was technically difficult partly because of inadequate knowledge on solar variability. In 1965 Sellers [9] analysed the then available theories of climate change and concluded that none of these theories could explain actual climate changes. It had been known by 1980, mostly through satellite measurements, that the signal of solar (irradiance) variability is energetically weak. This implies that the variability of the solar constant associated with solar (sunspot) cycles would directly drive only an extremely small temperature change at the earth‟s surface. Indeed it is this realisation which disfavoured the hypothesis advanced in 1975/76 that climatic variations may be caused by modulation of the Sun‟s output energy by sunspot cycles [29]. Also the Willett‟s sunspot theory mentioned in the preceding Section and other theories along similar lines were disfavoured by this realisation and the then lack of good explanation of how the relatively small changes in solar energy associated with sunspot cycles can affect large-scale wind motions in the troposphere.

4.4. SCIENCE BASED ON INDIRECT EFFECTS OF SOLAR ACTIVITY As noted above, variations in the solar radiation incident onto the Earth‟s atmosphere are too small to directly cause significant changes in climate. In fact this radiation does not change by more than ~0.6% over periods of 2 years to ~100,000 years. Mindful of this fact, researchers then directed efforts towards seeking for science relating climate changes to solar activity through indirect processes such as amplification processes, trigger mechanisms and chain of sequences. In other words, attention was and has been focussed on

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digging out science of existing or observed Sun-Climate relationships based upon indirect influences of solar activity. By the year 1977 a long list of possible mechanisms that were proposed in order to account for the observed Sun – Climate relationships had been published [30-37]. Most of these mechanisms, though, are based on a chain of events which had not been conclusively established. Furthermore the proposed mechanisms do not include complete knowledge regarding the expected interactions between the Earth‟s atmosphere and the causative solar agents or any coupling involved between the lower and upper parts of the atmosphere. It is mostly on the basis of these deficiencies that, with exception of only few mechanisms such as the one proposed by Schuurmans [38], the abovementioned mechanisms were found to be completely unsatisfactory as clearly reflected in the 1978 reviews by Pittock [39], Herman and Goldberg [40] and Siscoe [41] as well as the 1979 reviews by Scherrer [42] and MacCormac and Seliga [43]. A mechanism involving interactions of atmospheric greenhouse gases and solar flare produced particles was suggested by Schuurmans [38] as a possible explanation of some of the observed Sun-Climate relationships. In his theory, Schuurmans proposed that solar flare produced particles interact with tropospheric and stratospheric greenhouse gases (eg. O3 and H2O) resulting into changes in the radiation balance, pressure patterns as well as atmospheric circulation. Among the early physical mechanisms that were suggested as possible Solar-Climate links after 1977 are: solar irradiance variations caused by catalytic destruction of stratospheric ozone by odd nitrogen and odd hydrogen that have been formed by charged particles in the stratosphere [44], and solar UV flux variations due to corresponding changes in stratospheric ozone [45]. Electrical coupling mechanisms in the atmosphere were also proposed as a possible Sun-Climate link [46,47]. Mechanisms comparable to the latter were put forward by Tinsley et al. [48] who proposed that the global electric circuit (which involves air-Earth electric currents and g1obal thunderstorm activity) plays a role in the Sun-Climate coupling. They suggested that, if available, sufficient amplifications in the low modulation power provided to the global electric circuit by the solar wind could affect the weather. Furthermore they gave an example showing that, to intensify a winter storm in the Gulf of Alaska with a global electric circuit fluctuation, a successful model must provide for a power amplification of about 107. One of the Sun-Climate link mechanisms proposed in the 1990‟s was that reported by Perry [49]. This mechanism consists of the following three basic components:

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Ernest C. Njau Absorption of solar energy by transparent tropical oceans into a deep surface layer; ii. Transport of that energy by major ocean currents; and iii. Transfer of that energy by evaporation into atmospheric moisture and low-pressure systems that would be advantageous for precipitation formation.

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i.

Another mechanism that was proposed to account for the observed SunClimate relationships involve special triggering effects such as formations of additional condensation nuclei to stimulate the release of latent heat [50]. The idea here is that, if substantial enough, the latent heat so released would give rise to changes in the EAS energy patterns and hence also in associated climatic patterns. Dickinson [51] proposed a mechanism for explaining the observed SunClimate relationships, which is based upon variations in cosmic ray flux. In this mechanism, variations in galactic cosmic rays give rise to corresponding variations in the distribution of cloudiness since cosmic rays affect both sulphate aerosol generation and cloud nucleation. The resultant changes in cloudiness distribution would then lead to changes in emission of infrared radiation and absorption of incoming solar radiation by the lower atmosphere. In this case, it is expected that changes in the solar constant would trigger relatively bigger changes in cloud cover, thus linking changes in solar radiation with c1imatic variations. Another mechanism reported by van Loon and Labitzke [52] proposes that changes in solar cycles are likely to result in significant changes in snow cover and cloudiness. The latter changes can then cause significant changes in tropospheric dynamics and feedback processes, and hence sizeable climate variations. Tinsley and Heelis [53] proposed an “electrofreezing” mechanism in which variations in the solar wind give rise to variations in the electrostatic charging of supercooled aerosols and water droplets present on the top portions of clouds. These changes in electrostatic charging will give rise to corresponding changes in precipitation as well as transfer of latent heat in the atmosphere. After all the above-mentioned mechanisms were published, Haigh [54] reported in 1994 that up to the latter year, no physical mechanism had been proposed that can satisfactorily explain the observed correlations between solar activity and the Earth‟s climate. Furthermore even key books and papers related to the subject matter of this chapter which were published between

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1994 and 1999 did not report any mechanism that can satisfactorily explain the observed Sun-Climate relationships [55-63]. However, a string of journal papers [64-80] published from 1995 to 2000 apparently initiated the process of modernising the then existing science of climate changes. Important guidance to this modernisation work was derived from: (i) Results of a complicated electronic system [140] which was developed in 1994 for the purpose of mimicking the actual climate system; and (ii) An analytical climate model which was developed in 1997 (see Njau [141].

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4.5. SCIENCE BASED ON VOLCANIC ACTIVITY Volcanic eruptions inject dust particles into the atmosphere that change the atmospheric albedo with respect to shortwave radiation. These airborne particles hardly change the atmospheric emissivity with respect to longwave radiation, and settle down to the Earth‟s surface after no more than a few years. Largely due to the volcanism-albedo relationship given above, the volcanism theory of climate changes came into existence since about 1960 (eg. see Bryson and Goodman [81]). In short this theory says that temperature decreases as volcanic loading of dust particles into the atmosphere increases. In other words, temperature and volcanic eruption patterns are somehow inversely proportional to each other. It is on this basis that the ~200 years oscillation in occurrences of great volcanic eruptions reported in Lamb [82 ]is associated with corresponding climate changes. But note that this ~200 years periodicity is approximately similar to the 170 – 250 years periodicity in solar activity mentioned in chapter 3. The similarity may probably be due to the recently established fact that solar activity is related to occurrences of volcanic eruptions and earthquakes (see chapter 7).

4.6. SCIENCE BASED ON HUMAN ACTIVITIES Basically human activities influence climate variations if they alter any climate variable either positively or negatively. By emitting heat energy into the surface-atmosphere system (SAS), human activities increase the amount of thermal energy available to run the climate system. On the other hand, some human activities (eg. burning of fossil fuels) increase aerosols and greenhouse gases (ie. carbon dioxide, methane, water vapour, ozone, N2O and

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Ernest C. Njau

chlorofluorocarbons) into the atmosphere. The greenhouse gases absorb much of the outgoing longwave radiation and re-radiate much of it downwards. In this way the greenhouse gases reduce the SAS emissivity with respect to longwave radiation and hence keep the earth‟s surface warmer than it would otherwise have been. The aerosols emitted by human activities may change the SAS emissivity and/or albedo. Such a change can finally alter temperature patterns in the SAS. There is no country in the world where people are not engaged in land use activities. Vegetation clearance affects the surface albedo. It also reduces the CO2 – sinking capacity of the environment involved. If the cleared out vegetation is burnt, heat, some CO2 and aerosols are emitted into the atmosphere. The final result in this case could be weather and climate changes. Of course, the natural climate system does not remain passive and “unconcerned” as human activities attempt to interfere with its natural climate variations. In this case the natural climate system reacts to the human interference according to certain laws and processes that interrelate or bind together variabilties of the climatic parameters touched upon by the human activities. This aspect is dealt with in further details in chapters 5 and 6. The picture already put together in this chapter may be summed up by the following sentence. By the late 1990s all the published works on climate changes seemed to collectively converge on the consensus that mechanisms, science and theory that could account satisfactorily for all the observed climate changes had not been discovered. Accessibility to such discovery was blocked at that time by the following (then unresolved) problems. First, the correlations established between climate changes and solar activity were not stationary in time and space, something which had not been explained. Second, the amount of energy absorbed by the SAS from the variable component of incoming solar radiation had been noted to be too small to drive the observed climate variations directly. The only way this amount of energy could drive the latter variations was through an amplifying process, which had not been discovered. Third, difficulties existed in finding mechanisms that could explain observed rapid climate changes and links between solar wind variations and changes in tropospheric general circulation. Fourth, the anthropogenic role in climate changes was not well known, Fifth, in certain cases direct detection of solar activity periods in climate records cannot be done using standard spectral analysis methods. And sixth, gaps existed in the understanding of associations between climate changes and geophysical processes such as earthquakes and volcanic activity. Solutions of all these problems (which were established in and after 2000) are presented in the next three chapters. It is mostly these

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solutions which have laid down the foundation for the so-called modern science of climate changes. The UN‟s Intergovernmental Panel on Climate Change (IPCC) has concluded in 1990 and 1995 reports [83,84] that human activities are mostly responsible for the global warming that has taken place since about 1950. This conclusion has been echoed in the 2001 and 2007 IPCC reports [85,86]. Besides all these four IPCC reports conclude that solar activity has had and still has negligible forcing or influence on climate variations. In the next two chapters it is mostly the opposite that is established. In other words, it is proved that climate variations have been and are still mostly associated with solar activity and the Earth‟s orbital parameters. Human activities have so far contributed relatively smaller forcing or influence on climate changes. This apparently large difference between the IPCC reports and this book is largely due to the fact that the natural “amplifying” processes described in the next chapter were not considered in the IPCC reports. Non-consideration of the latter amplifying processes in the IPCC reports appears to be due to the fact that these processes were conclusively established and published after completion of the 2007 IPCC report.

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Chapter 5

.

MODERN SCIENCE OF NATURAL CLIMATE CHANGES

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5.1. INTRODUCTION This chapter presents and validates newly discovered science which best describes and accounts for climate changes. It is modernisation of the science in chapter 4 that has given rise to this new science. The first part of the chapter establishes the new science using at least three different methods on the basis of Njau [15,17,18,73]. In the second part of the chapter is a presentation of newly established relationships between solar wind variations and climate variations (mostly after Njau [2]). The final part of the chapter presents analysis of a variety of past climate records which clearly and undoubtedly support, verify and validate the new science contained in the earlier part of the chapter. It also presents new science and theory of rapid climate changes.

5.2. ESTABLISHMENT OF THE NEW SCIENCE 5.2.1. Establishment Based on Frequency-domain Analysis About 99.98% of the thermal energy that runs all the physical processes (including climate changes) in the Earth-atmosphere system (EAS) comes from solar radiation. Also 63 – 66% of the solar energy incident onto the surface-atmosphere system (SAS) is absorbed by the latter as solar (or shortwave) radiation at wavelengths between 0.1 µm and 2.5 µm. This absorbed

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energy is expended in the SAS on physical evaporation, transpiration, photosynthesis, heating up the air and the surface, and setting in motion both the atmosphere and the oceans. It is these processes which control climate variations. These variations, therefore, depend on corresponding patterns of SAS-absorbed short-wave radiation. In order to maintain itself in radiative equilibrium as expected, the SAS emits into space terrestrial (or long-wave) radiation at wavelengths between 4 µm and 80 µm. On this basis, the SAS is commonly viewed as some sort of heat engine which receives heat (from short-wave radiation) at high temperature and rejects it (in form of long-wave radiation) at a slightly lower temperature. In an actual engine, the energy put into the engine for operations is approximately (if not mostly) proportional to the patterns and intensities of the internal heat/temperature field and operations. This basic concept can be applied to the SAS, which is often likened to a heat engine in standard climatology and meteorology textbooks. Since it is the received short-wave radiation which performs meteorological and other processes in the SAS before its final ejection in a different form, variations in the SAS-absorbed solar energy patterns are expected to significantly affect climate variations. It is on this basis that emphasis is put here on detailed analysis of the spatial and time-dependent variation patterns of SAS-absorbed solar radiation. The dominant periodicities in the latter variation patterns are established below using frequency domain analysis. As detailed further in chapter 3, the solar energy stream continuously incident onto the (earth‟s) surface-atmosphere system (SAS) consists of a huge constant component So and relatively small variable components represented by V(t), where t denotes time. The components in V(t) are a seasonal component, components associated with the earth‟s orbital geometry, and solar (or sunspot) cycles components. Let us consider components So and qn(t), such that qn(t) arbitrarily represents any one of the variable components listed above. Since the global SAS albedo is about 0.34, the corresponding SAS absorptivity ao ≈ 0.66. Therefore, the portions of So and qn(t) actually absorbed into the SAS are aoSo and aoqn(t), respectively. Let the amplitudes of aoSo and aoqn(t) be denoted by Ho and hn, respectively. Note that Ho>>hn. Graphical plots of aoSo and aoqn(t) are given in Figure 5.1. It is practical and realistic to look at finite stretches HT(t) and QT(t) of aoSo and aoqn(t), respectively, each having time length T, say extending from

to

. The amplitude spectrum (ie. Amplitude versus

frequency plot) Hs(ω) of HT(t) is shown in Figure 5.2 while the amplitude

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spectrum Qs(ω) of QT(t) is shown in Figure 5.3, where ω represents angular frequency. Both Hs(ω) and Qs(ω) are expressed mathematically as: (5.1) and (5.2) where f ′ = f – fn, f = ω/2π and and also Qs(ω) = 0 when

VALUE OF ENERGY COMPONENT

VALUE OF ENERGY COMPONENT

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Note that Hs(ω) = 0 when

Ho

hn 0

0 TIME

(a)

TIME

(b)

Figure 5.1. Graphical plots of solar energy components aoSo (see (a)) and component aoqn(t) (see (b)) that are continuously absorbed into the SAS.

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Ernest C. Njau HS(ω)

HO

0

FREQUENCY

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Figure 5.2. A plot of the amplitude spectrum of HT(t). The small arrows show directions along which the plotted structures move as T increases. QS(ω)

hn Largely exaggerated in size for greater clarity

fn

FREQUENCY

Figure 5.3. A plot of the amplitude spectrum of QT(t). The small arrows show directions along which the plotted structures move as T increases.

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61

QS(ω) Ho

hn Largely exaggerated in size for greater clarity

FREQUENCY f

f=0

f = fn

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Figure 5.4. Amplitude spectra present in the SAS due to energy components HT(t) and QT(t). The small arrows show directions along which the plotted structures move as T increases. Note that fn is the frequency of qn(t).

Also Ho = aoSo so that Hs(ω) has peaks or maxima of values 0.21aoSo, 0.13aoSo, 0.09aoSo, 0.07aoSo, …… Since energy components HT(t) and QT(t) exist together in the SAS, it follows that these two energy components give rise to amplitude spectra Hs(ω) + Qs(ω) in the SAS as illustrated in Figure 5.4. Note that fn represents the frequency of qn(t) in hertz. As the SAS continues to receive more solar energy from So and qn(t) over time duration longer than the initial time length T, the new overall time length continuously increases. Consequently the amplitude structures in Figure 5.4 correspondingly move along the directions shown by the small arrows in the latter Figure. In the frequency range from f = 0 up to f = fn in Figure 5.4, the amplitude spectrum Hs(ω) opposes the changes or movements made by the amplitude spectrum Qs(ω). Under certain conditions which quasi-continuously exist in the SAS, the changes in Qs(ω) and Hs(ω) between f ≈ 0 and f ≈ fn completely stop each other. Note that there is no stoppage at exactly f = 0 because there exists under these conditions a net force/motion towards the right-hand side at f = 0.

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During this stoppage, the large peaks of Hs(ω) stand and remain approximately at the frequencies of Qs(ω). Strictly speaking the large peaks stand at frequencies very slightly less than those jest mentioned. As a reasonable approximation, however, the large peaks may be assumed to stand at the above-mentioned frequencies. In this way, large heat/temperature oscillations occur in the SAS approximately at frequencies even

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though qn(t) is relatively tiny. In this case the (small) oscillation qn(t) has received huge apparent amplification. Also other large oscillations at frequencies etc. are created. The analysis through which qn(t) has just been subjected can similarly be applied to any of the components of V(t) and yield results similar to those just given above but with fn replaced by the frequency of the particular component of V(t) analysed. The overall picture established here is that the SAS heat/temperature variation patterns contain dominant oscillations at frequencies of: each solar cycle, half the frequency of each solar cycle, annual and quasibiennial oscillations, the 100,000 years Milankovitch oscillation and ~200,000 years oscillation, and other (frequency) values related to solar cycles. The variation patterns also undergo changes in phase and/or oscillation mode at certain time sequences. During sufficiently high levels of turbulence in the SAS, the dominant oscillations at the frequencies just listed give rise to temperature patterns shaped into “node-antinode oscillations (NAOs)” which consist of a series of alternating nodes and antinodes. On the other hand, temperature patterns shaped into “sinusoidal oscillations (SOs)” are formed when sufficiently low levels of turbulence exist in the SAS. As an illustration, global mean temperature variations since 800 A.D. have been dominated by an SO at the sunspot-related periods of 400 – 550 years and 1000 - 1250 years (see Figure 1.2 in chapter 1.). More detailed variations of global mean temperature since 1856 reveal dominance of SOs and NAOs at a period equal to that of the second harmonic of the 80 – 120 years solar cycle (see Figure 5.5). The averages of these SOs and NAOs form a non-ideal sawtooth wave whose falling phases coincide with the early parts of the SOs and NAOs. Note that the antinode and minimum in Figure 5.5 coincide with a minimum and maximum of the 80 – 120 years solar cycle, respectively. Thus a negative correlation between temperature and solar activity is implied here.

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o

C

0.6 0.4 0.2 0.0 -0.2 -0.4 -0.6

1860

1880

1900

1920

1940

1960

1980

2000

TIME IN YEARS

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Figure 5.5. A plot of global mean surface temperature over the period 1856 – 2001. The bars represent annual values as departures from the 1961 to 1990 mean. Also the smooth curve shows the results of filtering the annual values to reveal long-term fluctuations. We have used advanced curve-fitting methods and dashed curves to plot the most dominant amplitude-modulation envelopes formed by the bars. The arrows show times at which an envelope mode changes to another envelope mode. Except for the dashed curves, the diagram has been reproduced by kind permission from Tiempo, Issue 43 (March 2002), page 26.

Note that the SOs and NAOs just mentioned are riding on the single SO which dominantly characterises Figure 1.2 whose next peak is expected at around 2060. It is easy to realise that in Figure 5.5 an NAO takes over just after year 2000. This particular NAO (whose period is equal to that of the second harmonic of the 80 – 120 years solar cycle) will effectively slow down, halt and possibly slightly reverse the global warming that had persisted before ~2000. Analysis of the global land-air and sea-surface temperature records since 1861 on page 252 of the WMO Bulletin vol. 44 (1995) clearly reveals significant presence of a variation period equal to that of the second harmonic of the 80 – 120 years solar cycle. Detailed predictions for the future are given in chapter 8. As an additional illustration, note that temperature variations in the whole of the northern hemisphere since 553 A.D. are dominated by one NAO and one SO at a dominant periodicity equal to ~1160 years. The next maximum of this SO is expected to occur around 2060. Note that the ~1160 years periodicity coincides with the periodicity of the 1000 – 1250 years solar cycle. There is another observation which enforces the established relationship between solar activity and the global temperature variations in Figure 5.5. The temperature variation patterns in the latter Figure undergo rapid phase/mode

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Ernest C. Njau

Temperature increasing

changes whenever the thick dashed curve and thin dashed horizontal line in Figure 3.2 cross each other. Obviously the next peak in Figure 5.6 is expected to be reached at around 2060. Analysis of observed mean northern hemisphere surface temperature variations (see Kellogy [126]) shows that these variations have been dominated by a period equal to that of the second harmonic of the 80 – 120 years solar cycle since 1898. These variations reveal minima in 1915 and 1970 as well as a maximum in 1947. They are supposed to have a maximum around 2005 and a minimum around 2035. Further supporting details are given in Figure 7.16. Several cases are presented in the rest of this chapter and in chapters 6 to 8 that provide solid support and verification of the Sun-Climate relationships established in this Section.

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500

1000

AD

1500

2000

Figure 5.6. Variations of the index of Northern Hemisphere temperature from 553 A.D. to 1950. We have used advanced curve-fitting methods to plot (in dashed curves) the variation envelopes of the solid-line variations at periods longer than 600 years. The inverted arrow shows the time at which the node-antinode envelope changes to a sinusoidal envelope. Except for the dashed curves, the figure has been reproduced by kind permission from Lamb H. H. (1982): Climate, History and the Modern World, Methuen, London.

5.2.2. Establishment Based on Stationary Heat/temperature Conditions In this Section we re-establish what has been established in the previous Section using a different methodology. To begin with, we are interested here in how the solar energy absorbed into the whole SAS at a particular time to varies with longitude θ only. Let E(,to) represent the variation with respect to θ of solar energy absorbed into the whole SAS at time to. In this case E(,to) may be expressed as

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where S is the solar energy incident on top of the atmosphere, a() represents θ-dependent SAS absorptivity with respect to incident solar energy and F(,to), which extends over 360° longitude only, is partly sketched in Figure 5.7. We assume that F(,to) is approximately a 1-wavelength part of a halfrectified sinusoidal wave along the zonal circumference of the earth with a wave number , where the degree symbol refers to longitude. As is well known, S consists of a large constant component So, and relatively small components at frequencies equal to those of the ISRC cycles defined in Section 3.4 of chapter 3. We should note that F(,to) is non-zero only over a zonal stretch of 180 longitude degrees. Before expanding equation (5.3) we assume (as is commonly done in standard meteorology/climatology textbooks) that when looked at as a whole, the globe and hence SAS has an approximately constant mean albedo and hence zonal absorptivity . On this basis, equation (5.3) may be

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expanded into the form

(5.4)

F(,to)

0 o

180

Longitude

Figure 5.7. Schematic plot of part of a function F(,to) which mathematically lets the day-side part of the SAS normally open to solar radiation but shields the night-side part of the SAS from solar radiation at time to.

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where

is the amplitude of the nth component of S, n is the nth phase

constant

for

the

variable

components

in

S,

Zo(θ)

=

and Ko, c1, c2 and c3 are

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constants. Physically equation (5.4) represents a situation in which the Earth is receiving solar energy instantaneously. So to make the equation incorporate the Earth‟s rotation, each (earth-fixed) longitude  should be replaced by ‟ such that ‟ represents earth-fixed longitude  that is continuously rotating eastwards with the Earth infront of energy stream S, and also that to should be replaced by varying time t. Introduction of θ‟ implies that Asin(ωt ± kθ) differs from Asin(ωt ± k‟θ‟) as follows. In the former sinusoidal term, k is wave number along an assumedly stationary θ-axis. But in the latter sinusoidal term, k‟ is wavenumber along a rotating θ-axis. Note that motion or shifting of the energy profile E(,to) in equation (5.4) through the longitudes is achieved by changing the rotational position of latitude  on the right-hand side of equation (5.4). If the changes just mentioned are made, equation (5.4) is transformed into the following equation.

(5.5) The difference between E(,to) in equation (5.4) and E(θ′,t) in equation (5.5) is clarified further as follows. Function E(,to) contains F(,to) which represents the profile in Figure 5.7 spread through all the longitudes but is stationary with respect to time and longitude. Now E(θ′,t) is equal to E(,to) except that term F(,to) is replaced by F(‟,t) which is in the second pair of square brackets on the right hand side of equation (5.5). What F(θ′,t)

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represents is the profile in Figure 5.7 but with the longitudes continuously passing by the (stationary) profile, thus mimicking the eastward rotation of the terrestrial longitudes. Now let ET(θ′,t) represent the pattern of solar energy absorbed into the SAS over time duration T, that is, from reference zero time to time T. In this case we can express ET(θ′,t) as follows: ET(θ′,t) = E(θ′,t) [Function which restricts existence of E(θ′,t) over period T].

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(5.6) where Tn decreases as T increases for a fixed n, and gn is constant for a fixed n. Let us start from initial zero time and assume that T is replaced by t. Then as time t increases, all the frequencies Tk for k = 1, 2, 3, …. correspondingly decrease, making each sinusoid on the right-hand side of equation (5.6) represent an unstable oscillation unless the frequency decreasing process stops. Detailed analysis of equation (5.6) shows that conditions under which the frequency decreasing process mentioned above stops temporarily and hence gives way to existence of stable oscillations is: and hence

, that is, Sn = Tk and Sn = 2Tk for k =

1, 2, 3, …. and n = 1, 2, 3, ….. Under these conditions, which will hereinafter be referred to as “stability conditions”, the following string of large, successive and quasi-stable waves are formed: and , where j = ½ or 1 and each of m, n and i is equal to 1, 2, 3, …. . These waves reverse their phases in quasi-regular sequences as time passes due to the phase reversing sequences in the series on the right-hand side of equation (5.6). Largeness of the waves in the string of waves just mentioned is realised when

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we note that

Ernest C. Njau ao  0.66, Zo(θ′) ≤ 1, cn  1 and gm  1. We have,

therefore, established above that the (small) variable components in aoS receive huge apparent amplifications in the SAS. Correspondingly other large oscillations at frequencies related to those of aoS are created in the SAS. Since the stability conditions are discretely and quasi-continuously created as time passes, the string of waves mentioned above is created discretely and quasicontinuously in the SAS. Consequently, stable oscillations are formed quasicontinuously over the whole SAS because the stability conditions are fulfilled by the infinitely large number of sinusoids on the right-hand side of equation (5.6) in quick and inheriting successions as time passes. Besides, the infinity in the number of the sinusoids as well as their evolutionary characteristics are always maintained with time. All these conditions give rise to quasicontinuous existence in the whole SAS of stable stationary and moving oscillations and waves more or less in the manner that stationary and moving pictures are formed in cinema, TV and computer movies through stitching together of a succession of individual pictures. More physical interpretation of the “stability conditions” given above may be given as follows. The frequency spectra of ET(θ′,t) always consist of infinite series of structural patterns whose (positive) frequencies collectively decrease with time. Each pattern consists of three spectrally connected amplitude peaks such that the central peak (CP) is much the largest and has its energy derived from the constant component of incident solar energy. The lower frequency peak (LFP) and the upper frequency peak (UFP) are each separated from the CP by frequency Sn for a given value of n. As time passes, the series of patterns drift towards zero frequency. When the LFP of any pattern reaches the zero frequency position, the pattern motion stops temporarily because the LFP must stop at the zero frequency mark and reverse its motion as it cannot physically go to negative frequencies. Note that actual oscillations and waves cannot have negative frequencies. During this temporary stoppage, and a considerably large amplitude stands at frequency . Now as time further passes, the LFP reverses its motion and starts moving away from the zero frequency mark. Then there comes a time at which the LFP overlaps with the CP in a head-on collision. At this stage the pattern motion stops temporarily. Under this stoppage condition, and a considerably large amplitude stands at frequency The account given above shows clearly that at least four categories of large and quasi-stable waves and oscillations X1(θ′,t), X2(θ′,t), X3(θ′,t) and

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X4(θ′,t) which reverse their phases quasi-regularly as time passes are formed in the whole SAS such that:

(5.7)

(5.8)

(5.9) and

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(5.10) where G1(‟) and G2(‟) are positive for westward motions and negative for eastward motions. Here G1(θ‟) and G2(θ‟) define zonal wave numbers along a rotating earth. Nonlinearities in the SAS give rise to harmonics of the waves and oscillations mentioned above. It is interesting to note that the large oscillations in X1(′,t) and X3(′,t), which are formed in the SAS, have frequencies related to those of the relatively tiny oscillations in the solar energy incident onto the SAS. So we have apparent amplification factors as large as

. If X2(θ′,t) and X4(θ′,t) are

considered, then amplification factors as large as 660 will be realised. Amplification factors as large as about 3143 are in existence (eg. see Njau [88]). Indeed these amplification factors amplify the direct radiative forcing (DRF) on climate variations to give rise to the existing amplified radiative forcing (ARF) on climate variations. All the 1990, 1995, 2001 and 2007 reports on climate change issued so far by the Intergovernmental Panel on Climate Change (IPCC) have used the DRF rather than the actually operating ARF. Due to the huge difference between the ARF and the DRF, it is obvious that had the ARF been used in the IPCC reports instead of the DRF, radiative

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forcing would have been seen and realised to dominate all other forcings in as far as climate changes are concerned. The oscillations represented by equations (5.7) to (5.10) acquire spatial wavelengths that are consistent with (and are dictated by) the resonant modes of the SAS. For the sake of brevity all the oscillations represented by equations (5.7) to (5.10) will hereinafter be referred to as “global heat/temperature waves (GHW)”. The zonal components of the GHW have north-south crests and troughs with zonal wavelengths

such that CE is the Earth‟s zonal

circumference and n = 1,2,3, …. And the latitudinal structures of GHW have latitudinal wavelengths

, where CL is the pole-to-pole distance along the

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Earth‟s surface. Those zonally moving GHW with zonal wavelengths

,

where k is a positive odd number, are associated with the Southern Oscillation [2 ]. Also the zonally moving GHW are associated with the North Atlantic Oscillation [2]. By definition, the Southern Oscillation is a see-saw in atmospheric surface pressure (or atmospheric mass) between the Indian Ocean and the central tropical Pacific ocean. It is measured by the Southern Oscillation Index (SOI), which is the difference in surface pressure between Darwin (12° S, 131° E) and Easter Island (27° S, 109° W). On the other hand, the North Atlantic Oscillation is alternation of atmospheric mass between the subtropical and subpolar regions of the North Atlantic Ocean. It is measured by the North Atlantic Oscillation Index (NAOI), that is, the difference between the normalised mean (winter) surface-pressure anomally for Ponta Delgada (in the Azores) and that for Akureyri (in Iceland). The eastward-moving components of the GHW are associated with the Bermuda Triangle Mysteries and El Nino events [64,65]. In the El Nino events, the heat carried by the latter components is focused onto the tropical Pacific ocean west of Central America by the lofty concave-shaped line of Rocky and Andes mountains. Conceptually at least, the relation or association between El Nino events and the Southern Oscillation can be easily deduced from the account just given above. As is well known, the early stages of an El Nino event look like an amplification of the seasonal heat/temperature cycle. We should note here that the annual or seasonal heat/temperature cycle can be significantly amplified by any heat/temperature oscillation related to any ISRC cycle through NAOmode interactions. For example, an 11-years heat/temperature oscillation together with another heat/temperature oscillation at a period equal to that of

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the second harmonic of the 80 – 120 years solar cycle greatly amplified the annual zonal heat/temperature cycle (in the tropics) during the early stages of the 1982/83 ENSO episode (eg. see Figure 2 in Njau [66]). The same two oscillations also greatly amplified the annual zonal heat/temperature cycle in the tropics just before the 1997/98 El Nino event. Perhaps the greatest amplification of the annual heat/temperature cycle on record occurred just before the record-breaking 1905/06 El Nino event. This amplification apparently resulted from a sudden falling phase of a sawtooth heat/temperature oscillation at a period equal to that of the second harmonic of the 80 – 120 years solar cycle (eg. see Figure 5 in Njau [69]). Annual SOI variations (see Figure 5.8) are positively correlated with corresponding variations in the 80 – 120 years solar cycle (see Figure 3.2). Note that the major minimum and maximum in Figure 5.8 coincide, respectively, with adjacent major minimum and maximum in Figure 3.2. On the other hand, the annual NAOI variations (see Figure 5.9) are negatively correlated with the 80 – 120 years solar cycle. Note that the major antinode and node in Figure 5.9 coincide, respectively, with adjacent major minimum and maximum in Figure 3.2. Some negative correlations have also been found between the 80 – 120 years solar cycle and variations in the Northern Hemisphere Zonal Index (NHZI) [2]. The NHZI is simply the difference in zonally averaged sea-level pressure between 35° N and 65° N. It is easy to understand why the NHZI should be negatively correlated to the 80 – 120 years solar cycle. The latter cycle is negatively correlated to global mean temperature as already shown. Now this temperature varies with its latitudinal gradient. Therefore, since the NHZI measures this gradient, it should correlate negatively with the 80 – 120 years cycle. More detailed correlations between solar cycles at periods shorter than 80 years and variations of southern oscillation as well as north Atlantic oscillation are given in Njau [2]. It is implicit from the account given above that the southern oscillation shows some physical characteristics of the tropical parts of the GHW. Also the north Atlantic oscillation shows some physical characteristics of non-tropical parts of the GHW. So both SOI and NAOI report on the GHW but at different latitudes. Actually physical interpretations of records of SOI and NAOI easily lead to establishment of the GHW. The contents already given in Section 5.2.1 and 5.2.2 enable us to explain many climatic phenomena that have not been fully explained. We know from the two sections just mentioned that for any solar cycle (say, at period P) there is in the SAS a large heat/temperature waveform at period Tp, such that Tp is equal to or otherwise related to P. Solar cycles are not completely stationary,

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they keep changing their periods at least slightly. Thus while the heat/temperature waveform just mentioned above has specific spatial wavelength λ (based on the SAS‟s resonant modes), it has (at least slightly) variable period Tp. If the waveform is moving at velocity Vp, then 20.0

10.0

0.0

-10.0

-20.0 1880

1900

1920

1940

1960

1980

YEAR

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Figure 5.8. Annual SOI variations from 1876 to 1989 (solid lines) together with envelopes formed by the solid lines. The average of the solid-line variations is plotted using dotted curves.

Figure 5.9. Variations in the NAOI from 1865 to 1997 (solid lines). The envelope formed by the solid-line variations has been plotted out using dashed curves.

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Length of cycle (years)

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Year

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Figure 5.10. Variations in global mean temperature and period of the 11-year solar cycle as a function of time. Reproduced by kind permission from Davidson J. P., Reed W. E. and Davis P. M. (1997): Exploring the Earth, Prentice-Hall N. J.

(5.11) Any change δTp in Tp gives rise to a change δVp in Vp. If we assume that λ is approximately constant, then

(5.12) Equation (5.11) shows that as P and hence Tp increase, there is less “stirring up” of the associated energy in the SAS. Also as P and hence Tp decrease, there is more “stirring up” of the associated energy in the SAS. Thus if the waveform associated with equations (5.11) and (5.12) has a global structure (like GHW), then global mean temperature will be inversely proportional to P and hence also to Tp. Note that the proportionality still stands even if the heat/temperature waveform were stationary. This conclusion is

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verified by Figure 5.10 which shows that global mean temperature is inversely proportional to the period of the 11-year solar cycle. The conclusion is established in a different way at the end of the section. Suppose that Vp is sufficiently small. Then if P and hence Tp make large to-and-fro variations, equation (5.12) shows that δVp correspondingly becomes positive and negative. Since Vp is sufficiently small the overall velocity also correspondingly becomes positive and negative. The result is that the whole heat/temperature waveform structure represented by equations (5.11) and (5.12) will perform oscillations (ie. to-and-fro motions) at the frequency at which P and hence Tp change. If generalised, the account given above leads to the following conclusion: Heat/temperature waveforms in the SAS associated with any solar cycle and whose drifting velocity is sufficiently small perform to-and-fro oscillations at the frequency at which the solar cycle period changes.

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5.2.3. Establishment Based on Stationary Frequency Conditions This section develops the proof already developed in sections 5.2.1 and 5.2.2 using a different methodology. Dominant influence of the ISRC cycles on climate variations may be established again using stationary conditions of frequencies associated with SAS heat/temperature frequencies as follows. Let us look at the whole SAS as one complete system. In this case we can generally express the solar energy stream Y absorbed into the SAS over time T as a function of in section 5.2.2) and in section 5.2.2) as follows:

(5.13) where So is a relatively large constant, An and ωn are constants for a fixed (or given) value of positive integer n, Bk is a constant for a given value of positive integer k, Wk is a time-dependent frequency for a given value of k, and t represents time. We can include a phase constant in sinWkt by writing sin(Wkt + Ck). However, this move will not change the final conclusion. Here we assume that for any value of n. A comparison of equation (5.13) and

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75 given

in the previous section, where the longitudinal variation has been removed since we are looking over the whole SAS in a generalised way. If we differentiate equation (5.13) with respect to t we get

(5.14) Let us start with one fixed value of k. In this case, equation (5.14) may be rearranged into the following form:

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(5.15) We are interested in the conditions under which frequency Wk remains constant with respect to time. Under these conditions so that equation (5.15) changes into:

(5.16) Now if we integrate equation (5.16) with respect to time, we shall get a version of Y that is modelled upon the condition . This particular version of Y is given below after integration of equation (5.16) with respect to time:

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(5.17) Stable or quasi-stable heat/temperature oscillations exist in the SAS at any value of Wk which on substitution into equation (5.13) converts the equation into a form similar to equation (5.17). We note that equations (5.13) and (5.17) acquire similarity when

and when

conditions Y has large waveforms

. Under these and

former waveform reflects the large apparent amplification factor

. The .

Even without involving equation (5.13), it is clear that equation (5.17) displays one oscillation and its harmonic(s) when such that m = 2, 3,4, ….. Under this condition large quasi-stable heat/temperature oscillations exist

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at frequencies

and

. These oscillations undergo phase changes at

certain time sequences. Since

and

are arbitrarily chosen values of

frequency, the account given above has established again that the ISRC cycles have dominant influences on SAS heat/temperature variations and related changes in the other climate parameters. There is yet another fourth method through which dominant influence of the ISRC cycles on climate changes may be established. This fourth method is based on amplitude modulation theory, and is given in references [18,80]. It is easy to explain again the relationship between global temperature and the 11years solar cycle period illustrated in Figure 5.10. According to equation (3.2) the period of the 11-years solar cycle varies in anti-phase mode with the (amplitude of) solar activity. In other words, long solar cycles generally occur during low solar activity while short solar cycles generally occur during high solar activity. As is well known, cloudiness is approximately proportional to cosmic ray intensity. Since cosmic rays maximise during low solar activity and minimise during high solar activity, cloudiness generally decreases and increases together with the period of the 11-years solar cycle. This implies that global temperature should vary in anti-phase mode with the period of the 11years solar cycle as illustrated in Figure 5.10.

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SOLAR WIND

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90O N

60O N NORTH

30O N

0O

30O S

60O S SOUTH

90O S

Figure 5.11. The meridional general circulation model derived in the Appendix. Locations in the troposphere at which air streams oppositely brush each other are labelled A.

5.3. SOLAR WIND AND SOLAR ACTIVITY INFLUENCES ON THE TROPOSPHERIC GENERAL CIRCULATION In 1954 Palmer [89] proposed a meridional general circulation model extending from the Earth‟s surface up to the thermosphere. The model consists of three 3-cell meridional circulation systems packed one on top of the other. The lowest system is the well known tropospheric general circulation system illustrated in Figure 2.5. Recently an attempt by Njau [90] was made to derive mathematically a general circulation model similar or comparable to that developed earlier by Palmer. The initial condition assumed in this attempt is existence of the well known meridional tropospheric general circulation. After assuming this initial condition, the ensuring mathematical derivation was conducted as shown in the Appendix. The derivation finally established the meridional general

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circulation model illustrated in Figure 5.11. This figure shows a system of gear wheels coupled together through friction and turbulent exchanges. The effort for this gear wheels system is applied by the solar wind as illustrated. If we consider the load to be in the tropospheric polar region, then the system has a mechanical advantage of about 1.6 x 108. But if the load is in the tropospheric equatorial region, the system has mechanical advantage of about 4.7 x 108. With such huge values of mechanical advantage, the model in Figure 5.11 enables very small variations in the solar wind momentum to give rise to very large forces that significantly drive the meridional tropospheric general circulation (MTGC). What follows is another mechanism or process through which solar activity influences the tropospheric general circulation. As is well known, cyclones generally move horizontally between latitudes 5° and over 60° in both hemispheres. Records in Milton [125] show that the frequencies and annual cumulative deviations of cyclones vary at a dominant period equal to that of the 80 – 120 years solar cycle. They vary approximately in phase with the latter solar cycle, and had their last maxima in the 1960s and early 1970s. Since the largely poleward horizontal motions of cyclones oppose the equatorward motions of the surface arms of the polar and Hadley circulation cells, these cells and the ITCZ are weakened and strengthened, respectively, during maxima and minima of the 80 – 120 years solar cycle. Since the 80 – 120 years solar cycle is accompanied by its second harmonic since about 1830, we would expect variations (in certain regions) of cyclones to reflect a period equal to that of the latter second harmonic. Indeed this period is well reflected in variations of annual numbers of named hurricanes in the north Atlantic ocean since 1886 (see Limbert [132]) and many rainfall and temperature patterns. On the other hand, the circulation cells above the troposphere in Figure 5.11 are weakened and strengthened (by the solar wind), respectively, during minima and maxima of solar cycles. Influences of the mechanism/process explained above on the polar ozone holes are discussed in Section 5.9. The model in Figure 5.11 successfully explains why changes occur in the MTGC one to few days after the Earth has crossed a solar-wind magnetic sector boundary (as reported in Hargreaves [33]). Furthermore the model successfully explains why changes in the tropospheric pressure patterns occur one day or longer after formation of a solar flare [33]. Note that the horizontal arms or branches of the 18 circulation cells in Figure 5.11 form horizontal air flows. But due to the influence of the Earth‟s rotation and coriolis forces (eg.

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Hundredths of a millimetre

see chapter 2), the air flows follow directions that make non-zero angles with the north–south direction. 70 60 50 40 30 20 3500

3000

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500 BC

AD

500

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Figure 5.12. Ring widths (twenty-year averages) in the growth rings of Bristlecone pine trees near the upper tree line in the White Mountains, California from 3431 B.C. (see solid lines). The ring width variations may be taken as indicating variations of summer warmth and/or its seasonal durations. Dashed lines have been used to sketch the amplitude-modulation envelopes formed by the solid-line variations. The solid-line variations have been reproduced by kind permission from Lamb H. H. (1982): Climate, history and the modern world, Methuen, London. The arrows point at build-ups which give rise to the second harmonic of the 2300 – 2700 temperature oscillations. 1 0 -1 0

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Figure 5.13. Temperature variations (shown in sigma units) in China for the period 0 – 2000 A.D. (see solid lines). The most dominant oscillation characterising the solid-line variations has been fitted through these variations using a dashed curve. The solid-line variations have been reproduced by kind permission from Yang et al. (2002): “General characteristics of temperature variation in China during the last two millennia”, Geophys. Res. Lett. 29, 1210 -1214.

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5.4. RECORDS-BASED DOMINANCE OF SOLAR ACTIVITY ON CLIMATE CHANGES In preceding chapters as well as chapter 8 some records have been presented which prove that climate variations have been and are dominantly influenced or controlled through solar activity and changes in the Earth‟s orbital parameters. Additionally the analysis in Section 5.2 undoubtedly establishes that natural processes have so far been dominant controllers of climate changes. In this Section more records are presented which further enforce the fact that solar activity plays a dominant role in controlling climate changes. Let us start with the record of past temperature variations in the U.S.A. shown in Figure 5.12. All the minima of the thick solid curves in the latter Figure approximately coincide with minima in the 2300 – 2700 years solar cycle shown in Figure 3.3. Also all the maxima of the thick solid curves in Figure 5.12 approximately coincide with maxima of the 2300 – 2700 years solar cycle. In accordance with the theory given in Njau [87,88], the variation envelopes in Figure 5.12 undergo a rapid phase change after a period of 2300 – 2700 years. Indeed this further confirms that the variations in the figure are dominantly controlled by a periodicity of 2300 – 2700 years. Natural processes which (due to increased nonlinearity) introduce a second harmonic of the 2300 – 2700 years temperature oscillation in Figure 5.12 are pinpointed by singleheaded and double-headed arrows. It is introduction of the second harmonic from around 1700 that has partly contributed to the rapidity of the post-1650 warming trend. Since the maximum phase of the second harmonic mentioned above has been introduced rather rapidly (eg. see also what happened around 2700 – 2800 B.C.), a long-term cooling trend will start before 2100. Look at the record of temperature variations in China shown in Figure 5.13. These variations have minima in years ~450 and 1600 as well as a maximum in ~900. This displays a variation period of ~1150 years, which is approximately equal to that of the second harmonic of the 2300 – 2700 years solar cycle. On the basis of the 1150 years periodicity, China is expected to start on a long-term cooling trend at about year 2050. It has been established earlier [91] that rainfall and temperature variations in England have been dominantly controlled by solar activity. This point is elaborated further in chapter 8. Temperature variations in the northern hemisphere, southern hemisphere and equatorial zone are displayed in Figure 5.14. Let us start looking at the temperature variations in the region south of latitude 23.6° S.

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0.4

0.2

0.0

Northern latitudes (90oN – 23.6oN)

0

-0.4 Low latitudes (23.6oN - 23.6oS)

T oC

0.2

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-0.2

0.0

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Southern latitudes (23.6oS - 90oS)

1880

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1960

1980

Figure 5.14. Observed surface temperature trends plotted in thin solid lines in three latitudinal zones from 1880 to 1978. The dominant amplitude-modulation envelopes formed by the thin solid lines are plotted using dashed lines. Also long-term averages of the thin solid-line variations have been plotted using thick solid lines. The thin solid lines have been reproduced by kind permission from Hansen et al. (1981): “Climate impact of increased carbon dioxide”, Science 213, 957.

Clearly the variation patterns in this southern region are changing at a dominant period equal to that of the 80 – 120 years solar cycle but in antiphase mode with respect to the latter cycle. Note that the antinode and minimum in the southern hemisphere plot in Figure 5.14 coincide,

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Temperature anomalies (oC)

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respectively, with a minimum and an adjacent maximum of the 80 – 120 years solar cycle (see Figure 3.2). On the basis of the sunspot-related periodicity displayed in Figure 5.14, the warming trend which started in the southern hemisphere at around 1960 will expectedly stop and reverse at about 2040. We now direct attention to the topmost plot in Figure 5.14 which represents temperature variations in regions north of latitude 23.6° N. These temperature variations are dominated by a sawtooth oscillation at a period equal to that of the second harmonic of the 80 - 120 years solar cycle. Note that the left-hand side minimum in the topmost plot of Figure 5.14 coincides with a minimum of the 80 - 120 years solar cycle. Also the next maximum of the latter solar cycle approximately coincides with a next minimum in the topmost plot of Figure 5.14. Clearly the dashed envelope in the latter plot (which displays sawtooth oscillations) in mounted on a longer period variation represented by the thick curve. It is the rising rapidity of the thick curve which shortened the falling phase of the above-mentioned sawtooth oscillation which started just after 1900. On the basis of the dominant periodicity of the temperature variations in the region north of latitude 23.6° N, the next maximum of the variations is expected to occur at around 2010. This implies that the latter region is expected to start cooling at around 2010. Already the U.S.A. (see chapter 1) and Canada (see the next paragraph) are at an initial stage of a cooling trend.

Calendar Year AD

Figure 5.15. A plot of temperature variations in the Canadian Rockies (see the solid lines). Dashed lines have been used to sketch out the most dominant amplitudemodulation envelopes formed by the solid lines. The latter lines have been reproduced by kind permission from Chambers et al. (1999): Progr. Phys. Geogr. 23, 181 – 198.

Each of the two lower plots in Figure 5.14 shows a periodicity equal to that of the 80 – 120 years solar cycle as follows. The dashed envelopes for

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southern latitudes display an SO minimum in ~1966 and an NAO node in ~1880. This implies presence of a dominant oscillation at a period of ~90 years. Now the dashed envelopes for low latitudes display a major minimum around 1880, and would have displayed another major minimum in 1966 had the ~1940 SO–to–NAO change not taken place. This shows presence of a dominant oscillation at a period of ~86 years. The latter oscillation is clearly accompanied by its second harmonic. Note that the ~90 years period displayed in Figure 5.14 features also in five-yearly averages of surface temperatures for latitudes 0 to 80° N, latitudes 0 to 80° S, and the whole Earth as reported in Lamb [82]. As noted in chapter 3, the most dominant periods in solar (or sunspot) activity after year 1100 include 400 -550 year, 1000 - 1250 years and ~ 350 years. The ~ 350 years sunspot-related periodicity is dominantly associated with the temperature variation patterns in Canada shown in Figure 5.15 as follows. The latter temperature variation patterns display a minimum at 1225, a node at 1575, a maximum at 1415 and an antinode at 1750. This implies presence of a most dominant variation period of about 343 years (which is sufficiently close to ~ 350 years) whose rising phase takes about 183 years. The last rising phase in Figure 5.15 started at about 1830, and it should stop at around 2010. Therefore, Canada is expected to start on a cooling trend at around 2010. It has been shown through similar analysis in Njau [2] that the northern hemisphere part north of latitude 30° N and the African region extending from 0° to 30° S and from 10° to 40° E will expectedly start on a cooling trend around 2010. Also according to Figure 5.14, the low latitudes (23.6° N – 23.6° S) are apparently not in a warming trend. All the projections given in this chapter are in agreement with the global mean temperature predictions (up to year 2100) presented in chapter 8. Last but not least, it is worth noting that dominance of solar activity influences on climate variations at periods less than 100 years has been clearly established in the author‟s book [2] and a string of journal papers in the references list. Of relevance here is overwhelming association between climate variations and solar cycles at periods less than 100 years.

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5.5. CAUSES OF RAPID CLIMATE CHANGES There are four major causes of rapid climate changes. The first cause is simply existence of climatic waveforms (associated with ISRC waves) whose waves have rapid rising or falling phases. Waves with rapid rising or falling phases are: sawtooth waves (which have rapid falling phases), exponential pulse waves (which have rapid rising phases), et cetera. For example, the temperature waves in Figures 1.3, 1.4 and 1.7 are all exponential pulse waves. You can see that all these waves have rapid rising phases. Before looking at the second major cause of rapid climate changes, let us briefly note an interesting characteristic of ISRC waves. Each ISRC wave (eg. a solar cycle) has an average (or equilibrium) level about which it oscillates. For example, the solid line in Figure 3.3 represents the equilibrium level of the 2300 – 2700 years solar cycle. Also the thin dashed horizontal line in Figure 3.2 represents the equilibrium level of the 80 – 120 years solar cycle. As a general rule, the times at which a (sufficiently long-period) ISRC wave crosses its equilibrium level coincide with rapid global and/or regional climate changes. For example, all the rapid temperature changes in Figure 5.12 coincide with times at which the 2300 – 2700 solar cycle crosses its equilibrium level (see Figure 3.3). Global mean surface air temperature patterns undergo rapid changes whenever the 80 – 120 years solar cycle or the 2300 – 2700 years solar cycle crosses its equilibrium level (see Figure 5.5). Available reports [2] show that the crossings of the 80 – 120 years solar cycle through its equilibrium level also approximately coincide with: (i) Minima of the length of the day; (ii) Changes from NAO to SO or vice versa in the patterns of summer monsoon rainfall in India; and (iii) Minima/nodes in the [(Normalised winter rainfall) – (Normalised summer rainfall)] variation patterns at Adelaide, Hobart and Auckland. Berger [5] gives graphical variations of the 100,000 years insolation signal cycle due to the 100,000 years variation in eccentricity of the Earth‟s orbit (see chapter 2). Calculations of the equilibrium level of the latter signal cycle have been made from the graphical variations provided in Berger [5]. It has been found that the insolation signal cycle crossed its equilibrium level at about the following timings or times: 430,000 years ago, 170,000 years ago, 130,000 years ago and about 10,000 years ago. Interestingly it is during all these four timings that large rapid temperature changes took place in the north Atlantic ocean and Greenland (see Figures 5.16 and 5.17). Section 8.3 of chapter 8 gives additional examples of coincidences of rapid climate changes and times at which ISRC waves cross their equilibrium levels.

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C

Summer temperature Northern Atlantic

14

10

6 0

100

50

140

Time (x1000 years B.P.)

Figure 5.16. Changes in summer temperature in the northern Atlantic during the past 136,000 years (solid lines). Dashed lines have been used to plot the dominant NAO and SO formed by the solid-line variations. Arrows point at rapid and significant temperature changes. The solid lines have been reproduced by kind permission from Berger A. (ed) (1981): Climatic variations and variability: Facts and theories, D. Reidel Publishing Company, Dordrecht.

15

Temperature OC

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17

13

11

9 1

0.8

0.6

0.4

0.2

0

(106 years)

TIME IN YEARS AGO

Figure 5.17. Greenland temperatures over the past million years (solid lines). The dominant NAOs and SO formed by the solid lines have been plotted using dashed lines. Rapid and large temperature changes are shown by arrows. Except for the arrows and dashed lines, the diagram has been reproduced by kind permission from Houghton et al. (1990) [83].

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Sometimes a change from NAO to SO or vice versa of a climatic parameter (such as temperature) involves rapid changes. As an illustration, note that all the major conversions from NAO to SO or vice versa in Figures 8.1 (see dotted lines) and 8.3 (see dashed lines) involve rapid temperature changes. So a third cause of rapid climate changes is simply a transition from climatic NAO to climatic SO or vice versa. The fourth major cause of rapid climate changes involves only climatic NAOs. Generally an NAO is simply a multiplicative or amplitude-modulating interaction between an oscillation related to an ISRC wave and other variations. If the amplitude of the oscillation is greater than the amplitude(s) of the latter variations, some distortions known (in the language of electronic signal processing techniques) as “overmodulation distortions” result. In these distortions some rapid changes occur at the nodes of the NAOs involved. Overmodulation distortions are frequent features in climatic records. Look, for example, at the temperature variation records for Japan shown in Figure 5.18. 16

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15

°C 14

13

12 1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

YEAR

Figure 5.18. A plot of annual mean air temperature at 23 sites over Japan from 1900 to 1990 (thin solid lines). The average of the latter lines has been drawn using a thick solid curve. Dashed curves show the NAO structure of the temperature variations. The arrows point at occurrences of large rapid temperature changes. The solid lines have been reprinted by kind permission from Limbert D. W. S. (1991): “Weather events of 1990 and their consequences”, WMO Bulletin 40, 328 – 351.

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Due to overmodulation distortions, the temperature rapidly shoots out of the narrow nodes around 1945 and 1989. Note that the whole NAO (in Figure 5.18) is dominated by a periodicity approximately equal to that of the 22 years solar cycle. Also the mean value of the temperature variations is dominated by a period equal to that of the 4th harmonic of the 80 – 120 years solar cycle.

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5.6. RELATION BETWEEN PERIODS OF ISRC CYCLES AND AMPLITUDE OF ASSOCIATED SAS TEMPERATURE OSCILLATIONS There are two notable establishments that have been made in Section 5.2 and Njau [87,88]. The first establishment is that, for each ISRC cycle, there are significant temperature oscillations in the SAS associated with that cycle. So if all the ISRC cycles are considered, the obvious implication is that a number of temperature oscillations related to these cycles continuously exist in the SAS. The second establishment concerns all the global/hemispherical temperature oscillations associated with the ISRC cycles. Arbitrarily consider any of the latter temperature oscillations (at an ISRC cycle period) and denote its peak-to-peak amplitude and period by Au and Tu, respectively. Using past records, it is easily shown through mathematical manipulations that if Au is given in °C and Tu is given in years, then: (5.18) where m ≈ 0.38 and qu ≈ 0.15. For example, the peak-to-peak amplitude of the 11-years global temperature oscillation is about 0.37°C (see Njau [79]). This amplitude value can be obtained from equation (5.18) by putting Tu = 11. Also the temperature oscillation amplitude of about 12.5°C in Figure 1.7 can be approximately obtained from equation (5.18) by putting Tu = 100,000 to 122,000 years. Although equation (5.18) directly applies to global and hemispherical temperature oscillations, it can also apply (approximately, at least) to regional and locational temperature oscillations.

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5.7 PREDICTION OF FUTURE GLOBAL TEMPERATURE VARIATIONS USING EQUATION (5.18) Consider all the solar cycles at periods longer than 30 years which are expected to significantly influence global temperature over the next century. These solar cycles are: the 80 – 120 years solar cycle and its second harmonic, the 170 – 250 years solar cycle, the 1000 – 1250 years solar cycle, and the 2300 – 2700 years solar cycle. On the basis of equation (5.18), calculations have been made of the peak-to-peak amplitudes of the global temperature oscillations associated with the solar cycles just listed above. These amplitude values and other related data are given in Table 5.1. Table 5.1 Some data on global temperature oscillations associated with selected solar cycles. Period of oscillation (in years)

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Year of occurrence of next or last maximum of oscillation Peak-to-peak amplitude of oscillation (in °C)

About 60 About 2000 About 0.7

80 - 120 About 2040 About 0.9

170 250 About 2100 About 1.1

1000 1250 About 2060 About 2.2

2300 2700 About 2730 About 3.0

Global average temperature has increased by 0.7°C since the mid-1800s. According to the Intergovernmental Panel on Climate Change (IPCC) [85], global temperature will increase by between 1.4 and 5.8°C by assuming uncontrolled emissions of human-generated greenhouse gases. As explained in chapter 6, the latter greenhouse gases expectedly amplify amplitudes of existing natural temperature oscillations. The gases also expectedly increase the mean level of global temperature patterns. However, influences of these gases on global temperature are largely minimised/nullified by Kirchhoff‟s law of radiation (see chapter 2). The latter law and the well known radiative equilibrium conditions attempt to maintain, on a long-term average, approximately constant absorbed solar energy content and hence temperature in the SAS. But the absorbed energy shapes into spatial and time-dependent waveforms whose positions and associated parameters in the SAS influence the SAS mean temperature. Whenever global temperature is made in this way to move away from its equilibrium value through corresponding changes in the absorbed solar energy content, the KLR and radiative equilibrium conditions attempt to restore the SAS temperature and energy content back to their equilibrium levels. This is why global temperature has been varying or oscillating about some equilibrium levels for millions of years through natural

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“adjusting” processes that involve cloudiness, atmospheric CO2, … etc. So any human-induced disturbances on global mean temperature (eg. through greenhouse gases) are dealt with accordingly by KLR and the radiative equilibrium conditions. In the light of the brief account given above, we can approximately predict future global temperature variations using Table 5.1. If we forward-extrapolate global temperature up to year 2100 using only the oscillations in Table 5.1, the results will be as follows. Predictions will be arrived at which show that global temperature up to 2100 will expectedly vary approximately as shown in Figure 8.5. Note that the latter figure has been established through a different methodology. It is very important to note that the natural climate system always attempts to ensure that terrestrial temperature patterns do not depart too much from their equilibrium levels. This is achieved through different natural processes. For example, the Canada temperature patterns in Figure 5.15 were made to avoid a long downward minimum stretch between 1520 and 1780 through a change from SO to NAO in 1520. Another illustrative example is shown in Figure 5.16 concerning temperature patterns for the Northern Atlantic. The maximum and minimum temperature patterns in this figure are “pulled” towards the equilibrium level through low-frequency attenuation. As an additional illustration, look at the Greenland temperature patterns in Figure 5.17. From about 1,000,000 years ago the NAO has been progressively drifting away from the equilibrium level by dropping down. As a solution the climate system changed it into an SO that starts with a nearly ending rising phase around 430,000 years ago. In order to ensure that the SO does not project the pattern too far from the equilibrium level through its next minimum, the climate system replaced this SO with an NAO around 170,000 years ago. These examples tend to show that the climate system always ensures that global temperature patterns are not drifting too far away from their equilibrium level by natural or human-induced processes. There is geological evidence that global surface temperature has been varying about an approximately constant equilibrium level (of about 288 K).

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5.8 ACTUAL SHAPES OF TERRESTRIAL TEMPERATURE VARIATION PATTERNS ASSOCIATED WITH CYCLIC VARIATIONS IN INCIDENT SOLAR ENERGY In trying to defend the IPCC reports and explain away dissenting views, several papers published in peer-reviewed journals since 1993 have wrongly assumed that terrestrial temperature patterns associated with cyclic variations in incident solar energy must be cyclic ! First, let it be known that these terrestrial temperature patterns essentially consist of SO and NAO series or harmonics with phase-changing sequences which often distort their direct cyclicities. Several examples are given in this book to justify this point. Additional examples can also be found in other books. For example, Peixoto and Oort [10] provides annual-mean surface air temperature variations over the northern and southern hemisphere oceans from 1870 to 1979. On being analysed, these temperature variations have been found to vary at a most dominant period equal to that of the second harmonic of the 80 – 120 years solar cycle. The minima of the temperature variations coincide with minima and maxima of the 80 – 120 years solar cycle. Also maxima of the temperature variations coincide with midpoints of adjacent minimum – maximum pairs of the latter solar cycle. This implies that the oceans involved are currently at or just past maximum temperatures and that they will cool for about 30 years. The expected cooling of the oceans will naturally decrease the CO2 content in the atmosphere. Variations of mean annual number and sustained wind speed of Atlantic hurricanes (which influence atmospheric CO2) reported in Peixoto and Oort [10] and Houghton et al [84] apparently vary together with the 80 – 120 years solar cycle. Both the number and the speed had their last maxima around 1960 and are expected to display their next minima around 2035. Some monthly-mean sea-surface temperature variations in the eastern equatorial Pacific ocean from 1958 to 1988 are also reported in Peixoto and Oort [10]. Clearly these temperature variations are dominantly characterised by NAO series at a period equal to that of the 22 years solar cycle. Second, these terrestrial temperature patterns may lose direct cyclicities depending on whether their cyclic (waveform) components undergo phase changes as they zonally circle the earth. This point is elaborated below. Let us label a cyclic wave or oscillation that does not change phase after each complete zonal circling of the earth “an even oscillation or wave”. Let us also label a cyclic oscillation or wave that undergoes a phase change of 180° after each complete zonal circling of the earth “an odd oscillation or wave”.

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Suppose a cyclic temperature oscillation whose frequency f is equal to or related to that of a particular ISRC cycle truly exists in the SAS. Let us refer to this temperature oscillation simply as “ISRC-related temperature oscillation”. The direct cyclic characteristic of the latter oscillation will be masked in the overall SAS temperature variation patterns under the following conditions.

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(i) Suppose that the ISRC-related temperature oscillation is odd and is mixed with its odd harmonics such that every other harmonic changes phase by 180°. All these variations will collectively form a sawtooth waveform at fundamental frequency f. Such a waveform is illustrated in Figures 5.10, 7.16 and 8.4. (ii) Suppose that an odd ISRC-related temperature oscillation and an even ISRC-related temperature oscillation both exist in the SAS. Let these two oscillations be added to a constant component and their odd and even harmonics such that every other harmonic changes in phase by 180°. All these variations will form an exponential pulse waveform at fundamental frequency f. Such a waveform is illustrated in Figures 1.3, 1.4 and 1.7. All these illustrations are associated with the 100,000 years oscillation mentioned in chapters 1 and 2. Over each complete cycle of this oscillation, the incident solar energy varies elliptically at the following two components: an even component Am cosωm t and an odd component Bm sinωm t Here ωm is the frequency of the 100,000 years oscillation while both Am and Bm are amplitude terms. We should, therefore, expect that terrestrial temperature patterns associated with the 100,000 years oscillation are shaped into exponential pulse waveforms. (iii) Suppose that an even ISRC-related temperature oscillation is in existence. If this oscillation is mixed with a constant component and its odd harmonics, the whole collection will form a triangular waveform at fundamental frequency f. (iv) Consider a situation in which an even ISRC-related temperature oscillation exists together with a constant component

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and both of its even and odd harmonics. If every other harmonic changes phase by 180°, the whole collection will form a fullrectified sinusoidal waveform at fundamental frequency f. (v) Consider a situation similar to that given in (iii) above but with every other harmonic changing phase by 180°. In this case the whole collection will form a square wave with fundamental frequency f.

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5.9 THE OZONE HOLE AND SOLAR ACTIVITY The phrase “ozone hole” has been popularly given to the dramatic springtime decrease in the Antarctic stratospheric ozone layer that extends from an altitude of 15 km to an altitude of 25 km. since the late 1970s. This hole was discovered by Farman et al. [133] in 1985. Some years later it was found that another relatively less pronounced polar ozone hole exists over the Arctic [134]. Formation and existence of polar ozone holes are strongly assisted or enabled by the lowness of temperatures over the poles during spring and winter. During a polar winter the stratospheric temperature is lowest at both the pole (experiencing winter) and the equator but highest in midlatitudes notably at and near latitudes 50° S and 75° N. Since the last Little Ice Age, the non-equatorial northern hemisphere has warmed up faster than the non-equatorial southern hemisphere. Due to this fact (and maybe other factors) winter and spring temperatures over the Arctic do not go as low as corresponding temperatures over the Antarctic. It is no wonder, therefore, that the Antarctic ozone hole has been more pronounced than the Arctic ozone hole. The mechanisms and processes responsible for formation of polar ozone holes are well given in previous publications (eg. see Solomon [135], Chanin [136], WMO [137], Fischer and Staehelin [138], McFarlane et al. [139] and others). In this section, therefore, focus is put specifically on how solar activity varies the polar ozone holes. As detailed in Section 5.3, the Hadley and polar cells of the tropospheric general circulation are weakened and strengthened, respectively, during maxima and minima of the 80 – 120 years solar cycle by motions of cyclones. In addition, the circulation cells above the troposphere in Figure 5.11 are strengthened and weakened during maxima and minima,

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respectively, of the 80 – 120 years solar cycle. On the basis of the processes just mentioned, air with relative minimum of ozone is transported into polar stratosphere in spring during minima of the 80 – 120 years solar cycle. Also air relatively rich in ozone is transported into the polar stratosphere in spring during maxima of the 80 – 120 years solar cycle. Therefore, the polar ozone holes vary at similar period and in phase with the latter solar cycle. Records show that the Antarctic ozone hole was at its relative minimum during the last maximum of the 80 – 120 years solar cycle. The conclusion given above is further enforced and supported as follows. Cosmic rays significantly contribute in producing nitrogen oxides (in the stratosphere) which destroy ozone catalystically. Now variation of cosmic rays is generally antiphase with corresponding variation of solar activity. This implies that largest destruction of stratospheric ozone by nitrogen oxides in polar regions takes place during minima of the 80 – 120 years solar cycle. On the other hand, relatively smallest destruction of ozone in polar regions by nitrogen oxides takes place during maxima of the 80 – 120 years solar cycle. This realization together with the conclusion reached in the last paragraph indicate existence of an 80 – 120 years oscillation in the polar ozone holes as already (partly) verified by available records. On the basis of this oscillation, it is expected that the Antarctic ozone hole will reach its greatest depth between 2030 and 2040. Of course, human-made chlorofluorocarbons, bromine and other ozone-depleting gases are currently assisting natural processes in deepening the polar ozone holes. It is on this basis that enforcement of the Montreal Protocol (1987/1990) and its Amendments is highly recommended.

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Chapter 6

MODERN SCIENCE OF HUMAN-INDUCED CLIMATE CHANGES

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6.1. INTRODUCTION Human activities have for years been blamed for some of the climate changes [83-86], notably through anthropogenic greenhouse gases. However, a number of scientists and a section of the general community still doubt on the reported extent and modalities in which humans cause climate changes [92,93]. Furthermore recent studies have revealed that human technologies possibly affect climate changes in ways that have not been reported before [15]. All these are clear indicators showing that the causative role of humans in past, present and future climate changes is not fully known. This apparent gap in climate-related knowledge is filled up (at least partly) in this chapter. Specifically the chapter presents the key science and theory associated with how human activities can possibly cause climate changes. From this presentation it is easy to deduce the extent to which humans have interfered with (and can still interfere with) the natural climate variability.

6.2. CLIMATIC INFLUENCE OF ANTHROPOGENIC GREENHOUSE GASES In this section we look at how human-generated greenhouse gases (GHG) can affect climate variations under all practically possible scenarios. In each of the scenarios we assume that human-induced GHG are injected into the

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atmosphere under certain conditions. The airborne GHG then contribute in trapping and retaining longwave radiation which would otherwise disappear into space. Consequently this leads to accumulation of energy into the SAS and hence continuous maintenance of energy pattern into the SAS. Since the atmosphere is dominantly characterised by meteorological variations at frequencies related to those of the ISRC cycles, we expect that the atmospheric GHG injected into the atmosphere by human activities will undergo small variations at frequencies related to those of the ISRC cycles. For example, the growth rate of atmospheric CO2 concentrations at Mauna Loa, Hawaii is dominantly characterised by SOs and NAOs at a period equal to that of the 11year solar cycle (see Figure 6.1). Also the globally averaged atmospheric CO2 growth rate has been varying at a period equal to that of the 11 years solar cycle. While the dominant NAO/SO oscillation period is that of the latter solar cycle, a rapid phase change and NAO-to-SO or SO-to-NAO change takes place along each NAO/SO rising phase. Thus about 1½ oscillations are made before the next rapid change. This dominant relationship between solar activity and CO2 variations in Figure 6.1 implies that the latter variations are largely influenced directly and possibly indirectly by natural processes. Therefore, this inference shows that if large human-generated GHG are present in the SAS, their influences simply amplify or add to existing natural patterns. In this case what we see are just amplified natural variabilities as illustrated in Figure 6.1. The human component aligns itself with the existing natural patterns as elaborated later on. More information on how humaninduced GHG may influence climate changes is given in the following scenarios. Scenario One: Suppose human activities generate GHG at such a rate that approximately constant GHG concentration is maintained in the atmosphere. In this case the longwave radiation absorbed into the SAS would consist of a large constant component and small variations at frequencies related to those of the ISRC cycles. This is because the absorbing medium is continuously subjected to environments and processes whose variabilities are dominantly influenced by the ISRC cycles. Analysis of this situation in line with the methodology given in Section 5.2.1 leads to the following conclusion. A fraction of the energy stream trapped into the SAS by the GHG will dominantly oscillate at frequencies related to those of the ISRC cycles. In this case the specific fraction of the trapped longwave radiation will amplify (existing) natural oscillations related to the ISRC cycles. The remaining

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fraction of absorbed longwave radiation will add as heat into the SAS at zero frequency.

Figure 6.1. Growth rate of atmospheric CO2 concentrations since 1958 in ppmv/year at the Mauna Loa, Hawaii station (see solid lines). The smooth curve shows the same data after being filtered to suppress variations on time-scales less than ~10 years. The SOs and NAOs formed by the solid lines are sketched using dashed lines. The solid lines have been reproduced by kind permission from Houghton et al. (2001) [85].

Scenario Two: Let us now assume that human activities inject GHG into the atmosphere at a constant rate over time length T. The energy absorbed into the SAS by the GHG over time length T consists of small variations at frequencies related to those of the ISRC cycles (see justification in the previous scenario) and another larger variation whose amplitude spectrum JT(ω) is given as (eg. see Giacoletto [94]):

(6.1) where angular frequency ω = 2πf. Analysis of this situation (see Section 5.2.1) leads to the conclusion that a fraction of the longwave radiation absorbed into the SAS by the GHG will dominantly oscillate at frequencies related to the sufficiently small frequencies

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in the ISRC cycles. Thus part of the absorbed longwave radiation will simply amplify the (existing) natural oscillations related to the ISRC cycles. The remaining fraction will be added to the SAS at zero frequency. Scenario Three: Consider a situation in which human activities generate GHG emissions at a rate having a generally increasing variation of any shape (eg. exponential shape, … etc). The amplitude spectrum of the absorbed longwave radiation will have lobes that coincide with those of a sinc function representing similar time-length. Detailed analysis of this situation leads to the conclusion that a fraction of the longwave radiation pattern absorbed into the SAS by the GHG will oscillate at frequencies related to some frequencies of the ISRC cycles (see justification in the previous scenarios). This fraction of absorbed longwave radiation will effectively amplify (existing) oscillations related to the ISRC cycles. The remaining fraction will add into the SAS as heat at zero frequency. The conclusions associated with the three scenarios given above and even section 5.2.1 are consistent with a physical law given in Njau [15]. This law may be stated as follows: The finite stretches or portions of different signals continuously absorbed into a medium continuously contribute energy (and hence amplitude) onto the frequencies of each other, regardless of the smallness of the signals. The contributions of a signal are proportional to its size. Thus the small signals are apparently amplified by the relatively larger signals. Suppose that one of these different signals has frequency fo. Then all other signals at frequencies less than fo will create quasi-stable oscillation(s) at frequency (or frequencies) slightly less than fo. Also all other signals at frequencies greater than fo will create quasi-stable oscillation(s) at frequency (or frequencies) slightly greater than fo. It is this law which makes the constant component of solar radiation and that of terrestrial radiation absorbed into the SAS apparently amplify the relatively small variable components of the solar radiation absorbed into the SAS. The latter components have frequencies equal to those of solar cycles. According to the above-mentioned law and Section 5.2.1, SAS-absorbed solar radiation and terrestrial radiation can only vary global mean temperature about its long-term average level. They cannot change the latter level, which has remained fairly constant (ie. between 285K and 288K) for a very long time. What is of probably greater importance concerning human-generated GHG is as follows. As noted in chapter 2, the SAS part below 60 – 70 km. altitude obeys Kirchhoff‟s Law of radiation (KLR). Consequently for any amount of longwave radiation trapped therein by human-generated GHG, there

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is an equal amount of shortwave radiation that is correspondingly denied entry into this specific SAS part. Since ~71% of the whole shortwave radiation absorbed into the whole SAS is trapped at the Earth‟s surface, application of KLR to the SAS below 60 – 70 km. altitude has significant corresponding effects or consequences in the lower part of the SAS. This would imply that a large part of longwave radiation increase trapped by human-generated GHG is possibly erased through KLR. This is because shortwave radiation equal to the increase is denied entry into the SAS. Then a deficit of about 71% of the energy denied entry is created in the lower part of the SAS. Obviously this deficit significantly reduces the net energy trapped by the human-generated GHG.

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6.3. CLIMATIC INFLUENCE OF HUMAN-GENERATED HEAT Since the beginning of the industrial revolution (1750 – 1850), human activities have been progressively emitting waste heat (however clean) into the SAS from power stations, factories, domestic premises, outdoors fireworks, warfare fires, exhausts of motor cars, aeroplanes, … and so on. By the year 2000, the total human-generated waste heat production rate (into the SAS) at global level had reached [95]. It has been shown [15] that the heat energy emitted by humans into the SAS due to electric energy uses alone will equal that correspondingly absorbed by the SAS from the Sun during the year Q (in A.D. form) such that:

(6.2) where Ωe is efficiency in fraction form, and αe is the fractional annual rate of increase of waste heat production by human activities at global level. Ryabchikov [4] reports values of Ωe and αe as 0.40 and 0.08, respectively. If we substitute these two values into equation (6.2) we will get Q ≈ 2143. This year would change to 2157 if we assume a currently unrealistic efficiency of 80%. This clearly shows that it is necessary to take into account the anthropogenically generated waste heat energy in the SAS when looking into possible climate changes associated with human activities.

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The possible influence on climate changes of anthropogenically generated waste heat in the SAS can be arrived at using the methodology adopted in the previous Section for longwave radiation trapped in the SAS by GHG. Alternatively the influence can be derived mathematically as in Njau [15]. The conclusions established in the latter reference (which can also be generated using the methodology adopted in the previous Section) may be summarised as follows. i.

Part of the heat energy emitted into the SAS by human activities amplifies the natural temperature/heat oscillations in the SAS that are related to the ISRC cycles. ii. The other part of the heat energy emitted into the SAS by human activities gets into the SAS mostly as energy at zero frequency.

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6.4. CLIMATIC INFLUENCE OF ELECTRIC AND COMMUNICATION TECHNOLOGIES The Sun continuously sends solar radiation to the Earth, pushes solar wind momentum onto the magnetopause, and creates electric currents as well as electric and magnetic fields in the Earth-atmosphere system (EAS). We have seen in chapter 5 how the solar radiation stream absorbed into the SAS gives rise to large climatic variations at frequencies related to those of the ISRC cycles. We have also seen in the same chapter how variations in the solar wind affect the meridional tropospheric general circulation. The question which we should at this point ask ourselves is: Do the electric currents as well as the magnetic and electric fields induced into the EAS by solar activity give rise to any climatic changes as well? This Section attempts to provide an answer to the just given question. Solar activity induces electric currents in the Earth‟s atmosphere. These electric currents in turn induce electric and magnetic fields inside the Earth. In parallel, humans induce comparable electric and magnetic fields inside the Earth through horizontal electric power lines and communication cables/wires. Take the case of horizontal electric power lines carrying electric current Ie. Many of these power lines operate at frequencies such as 50 Hz (eg. in Europe), 60 Hz (eg. in America and Africa), 30 Hz and 25 Hz. If at magnetic latitude

m

current

amperes, the latter

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current creates magnetic flux density at the top of the Earth‟s mantle (see next chapter) that is larger than that existing there naturally [96]. In this case human activities are inducing into the top of the mantle magnetic fields greater than those induced therein by solar activity and other natural processes. Apart from electric power lines, humans can induce large electric and magnetic fields inside the Earth through large currents along transoceanic communication cable systems. Even in the case of some transoceanic optical fibre cables, these cables are lined up with copper sheaths. Each of the copper sheaths carries (large) electric currents for repeater power supply. If these currents are sufficiently large, they will induce significant magnetic fields and currents inside the earth. What we have just realised is that human electric and communication technologies somehow compete with solar activity in inducing electric currents as well as magnetic and electric fields inside the Earth. Now suppose it is established that solar activity influences earthquakes and volcanic eruptions through induced electric and magnetic fields. In this case it follows that human activities can similarly influence occurrences of earthquakes, volcanic eruptions and associated climatic changes. This conclusion would be most likely if for a start, we prove that variations in at least the (climatechanging) volcanic eruptions are related to solar activity. Variations of major volcanic eruptions that caused reported instances of dry fogs, twilight glows and other atmospheric manifestations from 1680 up to 1982 have been plotted in Figure 6.2. The dashed curve in the latter Figure displays minima at years 1725 and 1930 as well as a maximum at 1830. This implies presence of a periodicity of 205 years, which is within the periodicity range of the 170 – 250 years solar cycle shown in Figure 7.7. The dashed curve (in Figure 6.2) does not only have a periodicity approximately equal to that of the latter solar cycle. It also lags behind the solar cycle by about 40 years. These observations, together with other related details given in the next chapter show that volcanic activity (accompanied by associated climate changes) is related to solar activity. On the basis of this relationship, it is easy to see that the world will experience the next major maximum of volcanic eruptions at around 2035. This major maximum will expectedly suppress the (slight) global warming trend which is expected to start around the same time (see chapter 8 for more details). Large volcanic eruptions introduce some significant global cooling trends. For example, the volcanic eruption in 1991 of Mount Pinatubo in the Philippines lowered global temperatures by 0.4 to 0.5°C. In addition, the volcanic eruption some 70,000 years ago of Mount Toba apparently brought a six-years long global freeze. In a similar manner,

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future maxima and minima of earthquakes occurrences at global level or in different regions may easily be predicted. For example, occurrences of earthquakes at global level will reach the next major maximum around 2035. This prediction is elaborated in the next chapter in connection with Figure 7.13. Apart from issues concerning climate changes, attention should be given to possible influences of the predicted volcanic activity maximum (at around 2035) on air communications. We know that airborne volcanic ash is very dangerous to aircraft engines. It clogs up the engines, and this happens when the ash melts and congeals in the turbines of the engines. For example, the Eyjafjallajokull volcano in Iceland erupted on 20/03/2010 and 14/04/2010. Due to the plumes of volcanic gases and silicate ash emitted by the two eruptions, many flights over Europe and North Africa were cancelled for six days to weeks. During the last maximum of the 170 – 250 years oscillation in volcanic activity (see Figure 6.2), the Eyjafjallajokull volcano erupted continuously from December 1821 up to January 1823. Indeed this shows a rough picture of the problems that we may face around 2035. A detailed spectral analysis of the solid-line variations in Figure 6.2 establishes not only a dominant period equal to that of the 170 – 250 years solar cycle, but also another period equal to that of the second harmonic of the latter solar cycle. Both of these periods dominantly characterise variations of earthquakes as elaborated in the next chapter. Having shown above that volcanic activity is related to solar activity, let us now go back to our major issue. How do human electric and communication technologies influence climate changes? The short answer is this. Through induced electric and magnetic fields inside the Earth, these technologies enhance variations in the naturally existing volcanic eruptions (and earthquakes) as detailed in the next chapter. The enhancements upon the natural volcanic eruptions then give rise to climate changes through well known processes [81,82]. It is important to note that the ~2035 volcanic activity maximum associated with the 170 – 250 years solar cycle coincides with the next maximum of the 80 – 120 years oscillation in earthquake activity (see Figure 7.13).

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Eruption magnitude per decade

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Figure 6.2. A plot of variations per decade of major volcanic eruptions that caused reported instances of dry fogs, twilight glows and other atmospheric manifestations from 1680 to 1982 (see solid lines). An average of the solid-line variations has been sketched using a dashed curve. The data for the solid lines has been derived from another graph in Meinel A. and Meinel M. (1991): Sunset, Twilight and Evening Skies, Cambridge University Press, Cambridge, p. 77.

Just as there is a 170 – 250 years oscillation in volcanic activity (see Figure 6.2), there is also a 170 – 250 years oscillation in earthquake activity (see Figures 7.6 and 7.8). However, the former oscillation phase leads the latter oscillation by about 90° phase angle. Apparently such phase relationship also exists between 80 – 120 years oscillations in earthquake activity and volcanic activity. Indeed this is one form of verification for Figure 7.1. Specifically verification is given for the point of view that both earthquake activity and volcanic activity are associated with processes inside the Earth that are largely related to the ISRC cycles.

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Chapter 7

MODERN SCIENCE OF NATURAL AND HUMAN-INDUCED CHANGES IN EARTHQUAKES, VOLCANIC ACTIVITY AND RELATED CLIMATE

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7.1. INTRODUCTION This chapter tells why and how human activities may have a hand in some of the hundreds of thousands of earthquakes that occur annually as well as in some of the volcanic eruptions and related climate changes. Besides, the chapter also shows that solar activity dominantly influences variations of earthquakes and volcanic eruptions. Remember also that we have seen in the earlier chapters of the book how this same solar activity dominantly influences climate variations. In the account that follows we mention and involve three layers of the solid Earth. These three layers are upper mantle, asthenosphere (which is part of the upper mantle) and outer core. The upper mantle (whose large part conducts electricity) lies between depths of about 10 km. and 1000 km. below the Earth‟s surface. It is made up of rocks containing iron, magnesium, silicon, calcium and oxygen. High electric conductivity exists at a depth of 15 km and between depths of 75 km. and 80 km. Electric conductivity also increases with depth from a depth of 400 km. downwards. Between depths of 80 km. and 400 km. there is an electric conductivity minimum of about 10-3 ohm-1m-1. This information about mantle electric conductivity is used in section 7.2, noting that good conductors of electricity are also good conductors of heat. The

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asthenosphere (whose temperature variations affect changes in earthquakes and volcanic activity) lies between depths of about 100 km. and 700 km. below the Earth‟s surface. The outer core (which is fluid and whose fluid motions carry electric currents) lies between depths of 2900 km. and 5100 km. below the Earth‟s surface. The following information about the structure of the solid Earth is also useful in this case. This information is given below in order to simplify the subsequent presentation. The topmost layer of the Earth (with a thickness of 50 to 400 km.) is a solid shell of rock called lithosphere. Its topmost part is called crust, and it has a thickness of 5 to 50 km. The lithosphere itself is divided into about 12 major plates which freely float onto the asthenosphere. As already implied above, the asthenosphere is made of hot, soft, semiliquid and easily flowing material. This soft composition of the asthenosphere makes it easy for the lithospheric plates floating on it to constantly jostle each other. In fact the lithospheric plates lock onto each other to form a jigsaw puzzle in which its pieces (in this case the plates) continuously jostle one another. It is the movements resulting from this jostling process which ultimately give rise to earthquakes and volcanic activity. This is why extensive volcanic activity and most earthquakes are concentrated along the boundaries of the lithospheric plates. Some (few) other earthquakes, though, are associated with fault movements inside the Earth. It is now easy to deduce from the short account given above that sufficiently large temperature waveforms (or other structures) with their associated thermal expansions in the asthenosphere have significant influences upon earthquakes and volcanic activity.

7.2. HOW NATURE AND HUMAN ACTIVITIES INFLUENCE EARTHQUAKES, VOLCANIC ACTIVITY AND RELATED CLIMATE As mentioned in the earlier chapters of this book, some scientific methods have been used successfully to prove that solar activity dominantly influences climate variations [2,15]. Later on, these methods (which include a newly developed physical law) were slightly modified to suit geophysical processes and then used to prove that solar activity also dominantly influences variations in earthquakes and volcanic activity. Figure 7.1 shows a simplified summary of the processes through which nature and humans influence occurrences of earthquakes and volcanic activity. A corresponding Figure summarising the

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processes through which solar activity dominantly varies climate changes is Figure 1 in Njau [15]. Clearly the process 1(b)  2(b)  3  4  5 in Figure 7.1, for example, is quite obvious and undisputable. Concerning (2a) in Figure 7.1, it is well known that part of the Earth‟s magnetic field is due to induced electric currents in the mantle called telluric currents. Note that temperature patterns flow upwards inside the Earth while solar radiation in the atmosphere flows downwards. This situation is likely to create anti-phase relationships between solar activity related temperature variations in the SAS and those in the asthenosphere. There is, therefore, a possibility that variations in geothermal energy emissions are characterized by variation periods related to those of solar activity [97]. The relationship between solar activity and earthquakes as well as volcanic activity summarized in Figure 7.1 has been verified and supported by records. Some of these records have been presented and analysed in Jaggar [98], Davidson [99], Aki [100], Simpson [101], Stothers [102], Njau [103,104], et cetera. Specifically, occurrences of large earthquakes in the Nankai Trough (Japan) have an average period equal to that of the 170 – 250 years solar cycle [105]. Also earthquakes of moderate magnitudes in the San Andreas fault at Parkfield, California (U.S.A.) occur at a period equal to that of the 22-year solar cycle (Kauffman [106]). Concerning volcanic activity, available records show that variations of this activity at different regions of the world are dominated by periods equal to those of solar activity (eg. see Bullard [107], Ollier [108], Decker and Decker [109]). Further verification of Figure 7.1 using actual records is briefly given below. Annual number of earthquakes with M  5.5

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Figure 7.2. A graphical plot of the annual numbers of all earthquakes with Richter scale magnitude M  5.5 within the Turkey area for the interval 1913 – 1970 (see histograms). We have used a dashed curve to fit the most dominant oscillation through the earthquake variations. We have reproduced by kind permission the histograms from Alsan E. et al. (1976): “An earthquake catalogue for Turkey for the interval 1913 – 1970”, Tectonophysics 31, T13 – T19.

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1a. Solar activity gives rise to continuous formation of electric current changes in the magnetosphere and ionosphere**. These electric current changes give rise to variations in the Earth‟s magnetic field (ie. geomagnetic field) inside the solid Earth.

1b. Varying solar wind driven disturbances and oscillations in the outer magnetosphere and its Earth‟s closed magnetic field lines.

2a. The upper mantle is a good conductor of electricity. Therefore electric currents are induced into it by the variations in the Earth‟s magnetic field mentioned above (through a law called Faraday‟s induction law). These induced currents give rise to small variations in the geomagnetic field inside the outer core (through a law called Ampere‟s circuital law).

2b. Small variations in the Earth‟s magnetic field inside the Earth‟s outer core through which the closed field lines in 1(b) pass.*

3. The small variations in the geomagnetic field inside the outer core exert small forces and hence disturbances on the current-carrying fluid motions in the outer core which are related to solar activity. This is according to a law called Fleming‟s Left Hand Rule.

1c.

4. The small disturbances in (3) above introduce small variations (related to solar activity) into the large heat energy stream continuously flowing out of the outer core.

2c. Small disturbances in the upward-flowing heat energy stream heading towards the asthenosphere.

Surface or under-surface shakes or explosions whose disturbances travel down past the asthenosphere.*

5. On reaching and entering into the plastic and partly molten asthenosphere, the heat energy stream mentioned in (2c) and (4) above consists of a large constant component and tiny variable components related to solar activity and other factors. Application of the physical law developed in Njau 15 to this situation leads to the conclusion that solar activity dominantly influences asthenospheric temperature variations and hence variations in earthquakes and volcanic activity.

** Since electric power transmissions, industrial and some transoceanic communication cable systems generate comparable electric field variations in the (lower) atmosphere, human activities significantly influence variations of earthquakes and volcanic activity (see Njau [96]). * Human-induced explosions or perturbations of the Earth‟s magnetic field lines mentioned in 2(b) can vary earthquakes and volcanic eruptions through this route. Figure 7.1. Simplified summary of the mechanisms through which variations in earthquakes and volcanic activity are related to solar activity and human activities. This relationship is later on well verified by actual records.

Annual maximum earthquake magnitude

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Figure 7.3. A graphical plot of maximum earthquake magnitude (on the Richter scale) per year in Greece (see solid lines). We have used dashed lines to plot the most dominant amplitude-modulation envelopes formed by the solid-line variations. We have reproduced by kind permission the solid lines from Bath M. (1983): “Earthquake frequency and energy in Greece”, Tectonophysics 95, 233 – 252.

Variations in the annual numbers of all earthquakes with Richter scale magnitude M  5.5 within the Turkey area from 1913 to 1970 are shown in Figure 7.2. The mean value of the annual variations (represented by a dashed curve) oscillates at a period (approximately) equal to that of the 11-year solar cycle. One of the possible causes of these 11-year variations in Figure 7.2 is a zonally moving asthenospheric temperature SO whose period is equal to that of the 11-year solar cycle. This is in line with the mechanisms proposed in Figure 7.1. Note that the locus formed by the highest values at and near the peaks of the dashed curve in Figure 7.2 has a variation approximately similar to that of the dashed curve in Figure 7.13. Let us now look at how the maximum earthquake magnitude per year in Greece varies with time as shown in Figure 7.3. The variations in the latter Figure are such that nodes (and antinodes) are formed at a period approximately equal to that of the 22-year solar cycle. This obviously shows that the mechanism that basically controls occurrences of annual maximum earthquake magnitudes is modulated by an oscillation whose period is equal to that of the 22-year solar cycle. The variations in Figure 7.3 can be possibly caused by zonally moving asthenospheric temperature NAOs at a period equal to that of the 22-year solar cycle. Next let us look at the variations of the annual number of the earthquakes with Richter scale magnitude M  7 since 1900 (see Figure 7.4). As shown by the dashed curves, these earthquake variations have a dominant period equal to that of the third nonlinear harmonic of the solar cycle sketched in Figure 3.2 using a thick dashed curve. This global earthquake periodicity may be explained as follows. Application of the theory/analysis used in Njau [2] to the process in which electromagnetic disturbances (due to atmospheric electric

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currents (eg. see Figure 7.1)) continuously penetrate into the solid Earth leads to the following conclusion. A zonally moving temperature structure comparable to the GHW (see chapter 5) continuously exists in the asthenosphere. Just as the southern oscillation acquires zonal wavelength of about 360 longitude degrees, the zonally moving temperature structure in the asthenosphere also acquires the same wavelength. Suppose this temperature structure has a period TD equal to that of the solar cycle sketched in Figure 3.2 using a thick dashed curve. Now over time TD, the peak of the temperature structure passes zonally under four major and different lithospheric plates that touch each other. These major plates are: the Pacific plate, the Indian plate, the African plate, and the South American/Nazca plate. In Bath [110] these four major and zonally connected lithospheric plates are named as: Pacific plate, Australian plate, Africa plate, and America plate. Passage of the asthenospheric temperature peak under the four major lithospheric plates (shown in Bath [110]) during time TD obviously gives rise to three or four oscillations or cycles in global earthquake variations. This is the picture when we look at the whole globe. But if we focus on an individual region on one of the major lithospheric plates, the earthquake variations at that particular region are likely to display a dominant period equal to TD together with smaller complete oscillations during each period TD. This point of view is illustrated by Figure 7.5 in connection with earthquakes in the San Fransisco area. From about 1830 to about 1940, the 80 – 120 years solar cycle makes one complete oscillation. Correspondingly the dashed envelopes in Figure 7.5 also make one major complete oscillation, with an NAO before 1890 and an SO after 1890. This implies that the NAO and SO patterns in Figure 7.5 vary at a period equal to that of the 80 – 120 years solar cycle. It is easy to deduce that the region associated with Figure 7.5 is currently experiencing a peak in earthquake variations (as already verified by recent observations and reports). The peak just mentioned approximately coincides with corresponding peaks in the patterns shown in Figures 7.6 and 7.8. The next peak in the pattern of Figure 7.4 is expected to occur between 2020 and 2040. Note that the arrow in Figure 7.4 points at a phase change which may lead to a change in the effective harmonic. In addition, four relatively smaller complete oscillations are superimposed upon the one major oscillation just mentioned in Figure 7.5 from 1830 to 1940. The apparent relationships between solar activity and earthquakes as well as volcanic activity briefly reported above can indeed be used to predict occurrences of earthquakes and volcanic activity using the known knowledge of solar activity.

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Figure 7.4. Histograms of the annual number of earthquakes with Richter scale magnitudes  7 since 1900. We have used dashed lines to plot the most dominant amplitude-modulation envelopes formed by the histograms. The arrow points at occurrence of a rapid change in the envelope variation phase. We have reproduced by kind permission the solid lines from Lowrie W. (1997): Fundamentals of Geophysics, Cambridge University Press, Cambridge.

Decade

Figure 7.5. A graphical plot of the number of damaging earthquakes in the San Fransisco area from 1800 to 1966 (see histograms). We have used dashed lines to plot the most dominant amplitude-modulation envelopes formed by the histogram variations. The arrow points at a time during which a change from “node-antinode” envelope to “sinusoidal” envelope took place. We have reproduced by kind permission the histograms from Young K. (1975): Geology: The paradox of earth and man, Houghton Mifflin Company, Boston.

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NO. OF EQKS/10 YRS

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Figure 7.6. A plot of variations in the number of central Appalachian earthquakes per 10 years period from 1770 through to 1960 (see histograms). We have used dashed lines to draw out the most dominant NAO and SO formed by the earthquake variations. The arrow points at a change from NAO to SO. We have reproduced by kind permission the histograms from Bollinger G. A. (1969): “Seismicity of the central Appalachian states of Virginia, West Virginia and Maryland – 1758 through 1968”, Bull. Seism. Soc. Am. 59, 2103 – 2111.

Figure 7.7. A plot in solid lines of: (a) The 11-years sunspot or solar cycle, and (b) The amplitude of the 11-year solar cycle since 1700.We have used dashed lines to draw the most dominant amplitude-modulation envelope formed by the solid-line variations. We have reproduced by kind permission the solid lines from Paul M. and Novotna D. (1999): “Sunspot cycle: A driven nonlinear oscillator?”, Phys. Rev. Lett. 83, 3406 – 9.

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Figure 7.8. The decadal number of intra-plate earthquakes with Richter scale magnitude M  6.4 in south west Japan (see solid lines). We have used dashed lines to plot out the most dominant NAO and SO formed by the solid-line variations. The arrow points at a change from NAO to SO.We have reproduced by kind permission the solid lines from Shimazaki K. (1976): “Intra-plate seismicity and inter-plate earthquakes: Historical activity in southwest Japan”, Tectonophysics 33, 33 – 42.

Another set of interesting earthquake variations is illustrated in Figure 7.6. The figure is characterised by an NAO before 1870 and an SO after 1870. This NAO/SO combination displays a periodicity equal to that of the 170 – 250 years solar cycle. This inference is verified by the fact (already confirmed by recent records) that the ongoing SO (in Figure 7.6) has a minimum around 1990. Note that the change from NAO to SO which occurred around 1870 in Figure 7.6 coincides with similar changes in Figures 7.5 and 7.8. The variations of earthquakes in southwest Japan displayed on Figure 7.8 can be analysed in a manner similar to that just followed in analyzing the earthquake variations in Figures 7.5 and 7.6. Specifically, the NAO and SO in Figure 7.8 display a dominant period equal to that of the 170 – 250 years solar cycle (see Figure 7.7) since year 1610. Furthermore, the change from NAO to SO at year 1890 in Figure 7.8 is accompanied by an envelope phase reversal. That is why numbers of earthquakes after 1890 decrease with time in Figure 7.8. The period of 170 – 250 years together with the 1890 phase reversal just mentioned can be used to make reasonable short-term predictions of earthquake occurrences in southwest Japan. The arrow in Figure 7.8 points at the time in which a second harmonic of the 170 – 250 years earthquake

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oscillation is introduced. This means that earthquake variations in southwest Japan after 1890 will vary in phase with the dashed curve in Figure 7.13, reaching the next maximum around 2035. We have seen that the earthquake variations illustrated in Figures 7.2, 7.3, 7.4, 7.5, 7.6 and 7.8 have dominant periods equal to those of the 11-years solar cycle, the 22 years solar cycle, the 2nd harmonic of the 80 – 120 years solar cycle, the 80 – 120 years solar cycle, the 2nd harmonic of the 170 – 250 years solar cycle and the 170 – 250 years solar cycle, respectively. The 170 – 250 years periodicity for Figure 7.6 is supported by a graphical plot of annual seismic activity in the central Appalachian region (U.S.A) in Bollinger [111] which is clearly characterized by this particular periodicity. Note that the envelope and phase changes which took place in 1870 in Japan (see Figure 7.8) resulted into location of an SO maximum at about year 2000. This implies that the post – 1870 SO in Figure 7.8 is expected to gradually decrease from the maximum (in about 2000) down to a minimum (in about 2100). In contrast, the annual and decadal numbers of earthquakes in the Appalachian region are expected to increase from year 2000 – 2010 to year 2100. Meinel and Meinel [112] report variations at global level of major volcanic eruptions causing reported instances of dry fogs, twilight glows and other atmospheric manifestations, from 1680 to 1982. After being analysed using the ETM described in chapter 8, the variations of the volcanic eruptions were found to be dominantly characterized by an NAO at a period equal to that of the 170 – 250 years solar cycle (Njau [97,104]). This NAO has adjacent nodes at years 1725 and 1935, and varies at the same period and in phase with the sunspot NAO in Figure 7.7(b). This chapter has so far illustratively shown that variations in earthquakes and volcanic eruptions are related to solar activity. These variations also take the forms of NAOs and SOs that involve NAO-to-SO conversions, SO-toNAO conversions, and some envelope phase changes. In some cases, the phase changes take the form of quasi-regular phase reversals. A typical illustrative example is shown in Figures 7.9 and 7.10. Figure 7.9 displays variations of maximum yearly magnitude for earthquakes in the Azores-Alboran region, Atlantic ocean. Obviously the NAOs and SO in Figure 7.9 vary at a period equal to that of the third harmonic of the 80 – 120 years solar cycle. Besides, a phase reversal occurs whenever an NAO changes to an SO or vice versa. Figure 7.10 shows variations of largest magnitude in a year versus time for earthquakes in the Granada – Malaga region, Spain. The SOs and NAO in this figure vary at a period equal to that of the third harmonic of the 80 – 120 years solar cycle.

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Also envelope phase reversals take place as indicated by inverted arrows in Figure 7.10. Take note that the phase change sequences in Figure 7.9 are systematically ahead of those in Figure 7.10 by 6 to 9 years. More information may be obtained by analysing Figures 6.2, 7.2, 7.5 and 7.8 through the same methodology that has been used to analyse Figures 3.2 and 3.3 in Section 3.5. Analysis of Figures 6.2, 7.2, 7.5 and 7.8 in this way shows existence of modulating oscillations in heat/temperature patterns and/or related parameters inside the earth. Generally these modulating oscillations have similar periods to (and are out of phase with) those in Figures 6.2, 7.2, 7.5 and 7.8. Since solar activity can easily be predicted, the contents in this chapter lead us to convenient methods by which we can predict future variations of earthquakes and volcanic activity. The contents of this chapter have also pointed at a possibility that human activities can significantly influence occurrences of earthquakes and volcanic eruptions. Previously efforts have been directed and concentrated mostly at possible human influences on the ozone layer and climate change, leaving aside the now equally possible human influence on earthquakes and volcanic eruptions.

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Figure 7.9. Maximum yearly magnitude for earthquakes in the Azores – Alboran region (see solid lines). We have used dashed lines to draw the most dominant NAOs and SO formed by the solid-line variations. The inverted arrows show times at which an NAO changes to an SO or vice versa. We have reproduced by kind permission the solid lines from Udias A. et al. (1976): “Seismotectonic of the Azores-Alboran region”, Tectonophysics 31, 259 – 289.

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Figure 7.10. The Largest magnitude in a year versus time for earthquakes in the Granada – Malaga region (see solid lines). We have used dashed lines to draw the most dominant SOs and NAO formed by the solid-line variations. Times at which envelope phase reversals take place are shown by inverted arrows. We have reproduced by kind permission the solid lines from Udias A. and Munoz D. (1979): “The AzoresAndalusian earthquake of 15 December 1884”, Tectonophysics 53, 291 – 299.

7.3. NEW ENVIRONMENTAL DISASTERS THAT CAN BE CAUSED BY HUMAN ACTIVITIES Two newly discovered mechanisms by which human activities lead to occurrence and/or encouragement of environmental disasters have already been given in this book. In the first mechanism, the (waste) heat energy emitted into the atmosphere by humans contributes in giving rise to climate changes (eg. see Njau [15] for details). In the second mechanism, certain variations in horizontal transmissions of heavy electric currents by humans give rise to changes in earthquakes and volcanic eruptions (eg. see Figure 7.1 and Njau [97,103,104] for details). These two mechanisms were published only very recently. A third mechanism easily follows from Figure 7.1. Any human activity which causes (small) variations in the closed Earth‟s magnetic field lines passing through the outer core gives rise to variations in earthquakes and volcanic eruptions through processes 1(b)  2(b)  3  4  5 in Figure 7.1. Remember that it has already been implied in connection with the latter Figure that human activities that create large atmospheric electric currents give

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rise to variations in earthquakes and volcanic eruptions. They also interrupt the natural relationship between solar activity and atmospheric lightning occurrences reported in Hargreaves [33]. And it has been established in Njau [15] that human activities which emit large heat energy into the atmosphere give rise to climate variations. The mechanisms just mentioned link human activities to variations in earthquakes, volcanic eruptions and the climate. Some additional new mechanisms which obviously follow from the established and published findings reported in this book are presented below. We all know that most satellites are parked in geosynchronous orbits located at altitudes of about 35,784 km. above the Earth‟s surface. These (geostationary) satellites orbit the Earth over the equator. All the satellites‟ orbits are located in the upper part of the magnetosphere. Since these satellites are several thousands in number, they introduce very small disturbances into the upper equatorial circulation arms of the system illustrated in Figure 5.11. But since the latter system has almost infinitely large mechanical advantage and velocity ratio, the very small satellites-caused disturbances just mentioned give rise to significantly large variations in the tropospheric general meridional circulation system and hence climate variations. Therefore, implementations of geostationary satellites technologies should be in the list of anthropogenic causes of climate changes and hence need to be properly regulated. Experimental studies of the ionosphere (ie. the ionized part of the atmosphere above about 60 km.) have involved a number of methodologies. In some methodologies, radio soundings of the ionosphere are conducted using ionosonde techniques and incoherent scatter techniques. These particular methodologies propagate radio waves into the ionosphere from ground-based high power transmitters. In some other methodologies, the ionosphere is heated by powerful electromagnetic waves from very powerful ground-based radio transmitters. All the methodologies just mentioned give rise to small variations in the ionospheric electric currents (eg. see Davies [113]). Consequently these (human) methodologies are capable of ultimately giving rise to variations in volcanic eruptions and earthquakes through the mechanism summarized in figure 7.1. Let us now consider all the airborne civilian and military hardwares within the Earth‟s atmosphere and hence Earth‟s magnetic field. These airborne hardwares (whose outer surfaces are largely made of electrically conducting materials) include rockets, missiles, aeroplanes, helicopters and satellites. Let us also consider all moving ground-based hardwares whose outer surfaces are largely made of electrically conducting materials. These moving ground-based hardwares include trains, trams, motorcars, motorcycles, bicycles, tractors,

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military tanks, aircraft carriers, lorries, boats, ships, submarines, et cetera. At any one time, millions of these airborne and ground-based hardwares are in motions. Obviously the Earth‟s magnetic flux is essentially drawn into these moving hardwares. Consequently the moving hardwares correspondingly vary the average magnetic flux density throughout the closed Earth‟s magnetic field lines passing through those hardwares. However, it is only the airborne hardwares in general and the ground-based hardwares in non-equatorial regions which encounter those Earth‟s magnetic field lines that pass through the Earth‟s outer core. Therefore, the world wide motions of all the hardwares just mentioned create (small) disturbances in the Earth‟s magnetic field inside the outer core. These (small) disturbances ultimately give rise to variations in earthquakes and volcanic eruptions through a process that starts from the third step onwards in Figure 7.1. As if it is not enough, the account that follows shows that our radio communication technologies can affect the climate, volcanic activities and earthquakes. Magnetic storms (ie. disturbances in the Earth‟s magnetic field that last up to several days) give rise to large electric currents in the atmosphere of the order of 106 to 107 amperes. These storms form when the magnetosphere is impacted by solar wind whose southward magnetic field is sufficiently large [113]. Just before reaching the magnetosphere, the solar wind has a magnetic field strength of about 10-9 T (Ratcliffe [114]). As explained further in Budden [115], there are plenty of human-generated electromagnetic waves continuously passing through the day-side outer boundary of the magnetosphere which have magnetic field strengths equal to or greater than 10-9 T. This is not surprising because some satellites (such as SOLRAD H1 and ISEE-3) orbit the Earth inside the solar wind some fair distance from the magnetosphere. In addition, some very powerful radio transmitters (such as those involved in ionospheric heating experiments) exist on the ground and which transmit radio waves upwards. Large north-south magnetic fields at or just outside the day-side magnetosphere are generated by long and heavycurrent electric transmission lines. This is the case if these (a.c. or d.c.) power lines are aligned along the east-west direction or have non-zero components along the latter direction. Think of a situation in which the southward magnetic field of solar wind just outside the day-side magnetosphere is becoming large enough. Suppose then that large and extensive electromagnetic waves with large southwardnorthward magnetic vectors are propagated vertically across the top of the magnetosphere. The waves will make the magnetic field in the solar wind lose its pre-existing consistently southward orientation by introducing and

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maintaining continuous north-south oscillations in the overall magnetic field. In this case the electromagnetic waves have significantly interfered with the role of the solar wind of influencing magnetic storms through its southward magnetic field. The fact that human-generated electromagnetic waves having magnetic field strength equal to or greater than 10-9 T exist just outside the day-side magnetosphere has the following three implications. First, human-generated electromagnetic waves can cause some modulations in the size of the southward magnetic field of solar wind just outside the day-side magnetosphere and also in the amount of solar wind particles that penetrate into the magnetosphere. Second, human-generated electromagnetic waves can give rise to significant variations in the tropospheric general circulation and hence climate through the system in Figure 5.11 (whose mechanical advantage and velocity ratio are nearly infinitely large). Third, since variations of magnetic storms are accompanied by large changes of atmospheric electric currents, human-generated electromagnetic waves can give rise to variations in earthquakes and volcanic eruptions through the mechanism summarized in Figure 7.1. Ground-level or underground explosions or shakes whose disturbances travel down past the asthenosphere ultimately give rise to variations in earthquakes and volcanic eruptions. As long as the disturbances cause (small) variations in the upward-moving heat energy stream proceeding onto the asthenosphere, influences on earthquakes and volcanic eruptions ultimately result in accordance with Figure 7.1. Finally let us look again at route (1c)  (2c)  (5) in Figure 7.1. Earthquakes and volcanic eruptions can use this route to feed or send disturbances back downwards past the asthenosphere and hence initiate other earthquakes and volcanic eruptions. This shows that earthquakes and volcanic eruptions can continue sustaining or re-generating themselves on their own through the closed-loop process illustrated in Figure 7.11. Perhaps more interesting information about earthquakes at global level may be obtained from Figures 7.12 and 7.13. The variations shown in Figure 7.12 are those for total (or accumulated) global strain energy release by earthquakes from year 1900 up to year 1955. These variations show the following two interesting features. First, the variations display two most dominant periods, namely 5 to 7 years and 13 to 14 years. The second period and the first period are approximately equal to the periods of the 11-year solar cycle and second harmonic of the latter cycle, respectively. Each maximum or minimum in Figure 7.12 approximately

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coincides with a maximum or minimum of the 11-year solar cycle. Note that from 1893 to 1913 the period of the 11-year solar cycle was 12 to 13 years, and it is from 1900 to 1931 that the oscillations in Figure 7.12 had a period of 13 to 14 years. Comparable oscillations at regional level have been reported in Srivastava [116]. Second, the width of the dashed envelope in Figure 7.12 is approximately inversely proportional to the dashed curve in Figure 7.13. This means that Figure 7.12 displays a most dominant variation period equal to that displayed in Figure 7.13. Apparently the latter curve displays a period equal to that of the 80 to 120 years solar cycle. In fact, the trigonometric Fourier series expansion of the dashed curve in Figure 7.13 consists of a most dominant oscillation at the period of the latter solar cycle together with a number of its relatively higher harmonics. You should be aware of the great period overlap between the 80 – 120 years solar cycle and the second harmonic of the 170 – 250 years solar cycle. A look now at both Figures 7.4 and 7.13 shows that the earthquake variations represented by these two figures are dominantly characterized by one oscillation with a period equal to that of the 80 to 120 years solar cycle together with its third (nonlinear) harmonic. As would be expected, the frequency of this harmonic is greater during the rising phase of the dashed curve in Figure 7.13 than during the falling phase of this curve. The next maximum of the dashed curve in Figure 7.13 and the next node in Figure 7.12 are expected to occur around 2035. Note that the phase change shown by an arrow in Figure 7.4 signals that the dashed curve in Figure 7.13 will next go through a sharp minimum. Initial earthquakes and volcanic eruptions

(1c)

(2c)

(5)

Triggered earthquakes and volcanic eruptions

Climate variations through Figure 5.11

Variations in magnetospheric magnetic field and magnetospheresolar wind interactions

Variations in upper mantle temperature, electric conductivity, relative permeability and magnetic shielding capacity.

Figure 7.11. A closed-loop process or mechanism through which earthquakes and volcanic eruptions can sustain or maintain or re-generate themselves by quasicontinuously triggering new earthquakes and volcanic eruptions. Note that symbols (1c), (2c) and (5) are those used in Figure 7.1.

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Figure 7.12. Total global strain energy release by earthquakes from 1900 to 1955. Strain energy is computed by taking square root of earthquake energy. Reproduced with kind permission from Tucker R. H., Cook A. H., Iyer H. M. and Stacey F. D. (1970): Global Geophysics, The English Universities Press Ltd., London.

Existence of quasi-stationary and zonally moving heat/temperature waveforms in the SAS (known as GHW) has been reported and discussed in chapter 5. Similarly the earthquake variation patterns presented in this chapter clearly imply existence of stationary and zonally moving heat/temperature waveforms (somehow comparable to the GHW) in the asthenosphere. The periods of these waveforms are mostly related to those of solar activity as may be deduced from analysis of earthquake variations. Also theoretical considerations show that the asthenospheric heat/temperature waveforms are approximately anti-phase to the corresponding SAS heat/temperature waveforms. Verification of this anti-phase relationship can be obtained from interpretation of the anti-phase variation plots of temperature and magnetic intensity deduced from a deep-sea core (see page 264 of Hargreaves [33]). The verification is as follows.

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Number per year

30

20

10

Total number = 1822 1900 1910

1920

1930

Annual mean = 20 1940 1950

1960 1970

1980

1990

Year

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Figure 7.13. Same as Figure 7.4, but now a dashed curve has been fitted through the earthquake variations to reveal dominant periods longer than 60 years.

The solar wind flow energy density decreases as distance from the Sun increases. Thus over each (100,000 years) Milankovitch cycle, the solar wind flow energy density just outside the dayside magnetosphere goes through one 100,000 years variation cycle. According to Figure 7.1, this gives rise to large temperature oscillations in the asthenosphere and the nearby (electrically conducting) upper mantle. The electric conductivity of the latter decreases as temperature increases. Also the corresponding relative permeability changes with temperature. As the upper mantle temperature displays a 100,000 years oscillation, the magnetic shielding capacity of the upper mantle also displays 100,000 years oscillation. Correspondingly the magnetic intensity at/near the Earth‟s surface also displays a 100,000 years oscillation. The latter oscillation has a minimum and a maximum coinciding, respectively, with a minimum and a maximum of the upper mantle/asthenosphere temperature. Records in Hargreaves [33] show that a 100,000 years oscillation in global temperature is anti-phase to a 100,000 years oscillation in near surface magnetic intensity. This, therefore, shows that the 100,000 years oscillation in global temperature is anti-phase to a corresponding 100,000 years oscillation in upper mantle/asthenosphere temperature.

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Initial variations in magnetosphere-solar wind interactions

Variations in magnetospheric and ionospheric electric currents and climate (through Figure 5.11)

123

(2b) (3) (4)

Variations in magnetic shielding capacity of the upper mantle and hence in magnetospheric magnetic field and magnetosphere-solar wind interactions

Variations in upper mantle temperature

(5)

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Figure 7.14. Processes in the earth-atmosphere system (additional to those in Figure 7.11) which can self-generate and sustain themselves. The numbers represent the meanings shown in Figure 7.1.

We have realized in connection with Figure 7.11 that earthquakes, volcanic activity and asthenosphere/upper mantle temperature variations can collectively self-generate and sustain themselves. Figure 7.14 now shows that even variations in magnetospheric and ionosphere electric currents can continue self-sustainably when solar activity sleeps down to non-varying conditions. Obviously the chapter has introduced new relationships between climate, solar activity, upper atmospheric processes and geophysical processes. These upper atmospheric and geophysical processes together with solar activity influences should be taken into account when one is making sufficiently refined and accurate climate predictions. Another important realisation brought up in this chapter is that all variations in earthquakes and volcanic activity are somehow related to the ISRC cycles. This follows an earlier realisation that all climate variations are also somehow related to the SCR cycles.

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Ernest C. Njau Small variable energy signals ETV(t) from the antenna Large constant energy ETC(t) derived from the power supply

Large picture and sound signals SPS(t) at the frequencies of ETV(t)

TV system

(a) A TV system

Small variable energy signals EAV(t) from the Sun and inside the Earth Large constant energy EAC(t) from the Sun and inside the Earth

Large climate and geophysical variations ECG(t) at frequencies related to those of EAV(t)

Asthenosphereatmosphere system

(b) The asthenosphere-atmosphere system

Figure 7.15. Simplified block diagrams of a TV system and the asthenosphereatmosphere system. o

C

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0.8 0.6 0.4 0.2 0.0 -0.2 -0.4 -0.6 -0.8 1860

1880

1900

1920

1940

1960

1980

2000

Figure 7.16. Mean annual surface air temperature in the northern hemisphere north of latitude 30oN for the 1856 through 1998 period. The bars represent annual values as departures from the 1961 – 1990 mean, and the smooth curve shows the result of filtering the annual values to reveal long-term fluctuations. The NAO and SO formed by the temperature variations have been sketched using dashed curves. Arrows pinpoint minima, maxima and antinodes of the NAO/SO structures. Except the dashed curves and arrows, the diagram has been reproduced by kind permission from Tiempo, issue 38/39 (2001) p.38.

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7.4. COMPARISON BETWEEN A TV SYSTEM AND THE ASTHENOSPHERE-ATMOSPHERE SYSTEM In terms of energy signal flows and processings, the asthenosphereatmosphere system and a television system compare with each other as shown in Figure 7.15. In Figure 7.15(a), the large SPS(t) are derived from the relatively small ETV(t) through amplification processes (which involve ETC(t) provided by the power supply and TV electronic circuits). In Figure 7.15(b), the energetically large ECG(t) is derived from the relatively small EAV(t) through natural amplification processes (which involve EAC(t)) as detailed in Njau [15,87,88]. It is basically non-involvement or non-consideration of the latter amplification processes which made the role of solar activity in climate changes appear negligibly small in the IPCC reports [83-86]. The amplification processes in the TV system (in Figure 7.15(a)) are energised or enabled by the humanmade power supply. In a similar and comparable manner, ECG(t) in Figure 7.15(b) derives its frequencies from EAV(t) and its enlarged amplitudes from the natural EAC(t). In other words, ECG(t) is powered by EAC(t) and not by the relatively tiny EAV(t), which simply provides the frequencies. Harmonics are caused by nonlinearities and distortions. Just as a TV or radio system amplifies the small information signals that enter through the antenna, the asthenosphere-atmosphere system amplifies the small solar activity driven energy variations that enter downward onto the atmosphere and upward onto the asthenosphere. So the asthenosphere-atmosphere system is some kind of a natural amplifier. Therefore, human activities will cause large variations in the asthenosphere-atmosphere system if they give rise to (even small) variations in the energy entering into the system at the top of the magnetosphere or at the bottom of the asthenosphere. Such variations will go through a large natural amplification process.

7.5. CORRELATION BETWEEN SURFACE TEMPERATURE AND EARTHQUAKE ACTIVITY The smooth curve in Figure 5.5 is approximately a full-rectified sinusoidal wave at a period of about 60 years. This period is approximately equal to that of the second harmonic of the 80 – 120 years solar cycle. The same conclusion

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can be made for the smooth curve in Figure 7.16. Now when the variations in Figure 7.16 are projected to sea level, the variation period changes from ~ 60 years to 80 – 120 years (see the thin solid-line curve in Figure 7.17). What is more interesting here is the following. The thin solid-line curve in Figure 7.17 varies at apparently the same period and in phase with the dashed curve in Figure 7.13. Just as the dashed curve in Figure 6.2 is apparently part of a full-rectified sinusoidal wave, the dashed curve in Figure 7.17 is apparently part of another full-rectified sinusoidal wave. So both Figures 7.13 and 7.17 reflect high positive correlation between surface temperature and earthquake activity. If projected to sea level, the variations in Figure 7.13 would probably result into a dominant variation at a period approximately equal to that of the dashed curve in Figure 7.17. This point of view is most likely because Figure 5.14 shows that global variability of surface air temperature since 1880 has been greatly influenced by the region north of 23.6° N. The average of the three plots in Figure 5.14 displays general variation features fairly similar to those reflected by the region north of 23.6° N. In that case, the just established positive correlation between surface temperature and earthquake activity would be further supported. In any way, this correlation implies existence of spectral and phase relationships between surface temperature and temperature in the asthenosphere as mentioned earlier in this chapter. This is because earthquake activity is significantly influenced by variations in asthenospheric temperature. Correlations between surface temperature and asthenospheric temperature will enable geologists and geophysicists to study variations in asthenospheric temperature variations and related geophysical parameters using the more available surface temperature records. In ending this Section we should try to explain scientifically why the dominant oscillation period in Figure 7.16 is different from that in Figure 7.17. Chapter 5 has established existence of zonally (or longitudinally) moving heat/temperature waves (ie. the GHW). To be long lasting, these waves should have wavelengths equal to division of the zonal circumference by integer numbers. Suppose that at a specific wavelength λg and altitude z above sea level, a GHW wave exists at frequency fg and zonal velocity vg. Thus (7.1) Differentiation of equation (7.1) with respect to z gives

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(7.2) For waves with sufficiently large λg,

so that equation (7.2)

approximates into

(7.3) In order for the GHW wave to maintain its structure or shape over the relevant altitudes as it moves zonally, vg should increase as altitude increases. This according to equation (7.3) implies that fg should increase as altitude increases. In other words the period

of the wave increases as

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altitude decreases, reaching a maximum at sea level.

Figure 7.17. Mean annual surface air temperature in the Northern Hemisphere north of latitude 30oN for the 1891 through 1978, projected to sea level. Reproduced by kind permission from Gruza G. V. and Rankova E. Ia. (1979): “Dannye o strukture I izmenchivoski klimata (Data on the structure and variability of climate)”, Vsesoiuznyi Nauchnoissledovatelskii Institut Gidrometeorologicheskoi informacii Mirovoi Centr. Dannykh, Obninsk, pp. 201.

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Ernest C. Njau Now for sufficiently small values of λg,

becomes quite large. In this

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case fg may increase or decrease with altitude, depending on corresponding values of vg. It can similarly be shown that periods of GHW waves decrease as distance from the equator decreases at constant altitude. So periods and spatial wavelengths of GHW and associated waves generally vary with altitude and latitude, depending upon the factors given above.

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Chapter 8

A MODERN METHOD FOR PREDICTING CLIMATE CHANGES

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8.1. INTRODUCTION It is always useful to know how the climate will change in future. A number of methods have, therefore, been developed with the specific aim of using them in predicting future climate changes. Each of these methods has a model representation of how the climate changes, and uses such representation to generate or simulate future climate variations. It is not surprising that all these methods are identified or named by the types of models they use to represent the climate. So far the methods that have been used to predict climate changes include: statistical models, physical models, analytical models and general circulation models (GCMs). In this list, it is the GCMs that have been most popularly used. Also all the IPCC reports on climate changes issued so far have been largely based on GCM results. For detailed descriptions of GCMs, the reader is directed to Kiehl and Ramanathan [117], Stensrud [118], and others. Significant errors have been reported recently in GCM climate predictions. A number of such errors contained in all GCM results or climate simulations are given in details in Njau [2]. Specifically GCMs cannot simulate the Sun-Climate relationships presented in this book because of the processes of averaging in time and space incorporated into the models. Indeed this is a major deficiency of climate predictions made through GCMs. It is this deficiency which prompted new moves to search for a modern climate prediction method after the second (1995) IPCC report. This modern method is called Envelope – Tracing Method

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(ETM) or Science – Extension Model (SEM). It was first reported in 2000, and has been substantially improved eversince. The next section briefly describes the ETM and illustrates how this method is used to make climate predictions.

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8.2. THE ENVELOPE – TRACING METHOD (ETM) With the advent of the modern science of climate changes, it is possible to make quite accurate future climate predictions using the ETM. This is because the ETM basically looks at past climate records and then skillfully fits the modern science onto the records as well as the associated graphics. Then the fitted science and graphics are extended into the future under acceptable conditions and limits using graphics fitting techniques. So the ETM first masters the science that governed all the available past climate records. After the mastery, it uses the science to draw associated graphics through the records. These graphics represent variabilities in the past climate. Finally the ETM “lets” the science and graphics systematically continue to operate into the future over a limited period of time. The ETM was first reported in Njau [17] in 2000. A more refined version of the method can be found in a 2009 book by Njau [2]. Generally the ETM is a simple and user-friendly method whose implementation does not demand large computer power and time. Before we go to actual climate predictions made through the ETM, we will summarise the steps that one has to follow in the process of implementing the ETM. If you want to make climate predictions using the ETM, you will have to go systematically through the steps listed below. First step. Make a time-domain graphical plot of the climatic parameter data given. Second step. Use accurate curve-fitting method to fit SOs and/or NAOs onto the graphical patterns of the climatic parameter variations in the graph. Here we establish the sequence in which the actual science involved shaped the climatic variations represented by the data. What follows is fitting of mathematical expressions onto the NAO/SO series, including their switching sequences. Third step. Carefully study the series of SOs and/or NAOs in the second step as well as their switching sequence(s). Then set up mathematical representations of the series and their switching sequences.

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Fourth step. On the basis of the results from the third step, extend forward one NAO or SO. If the sequence(s) in the third step is (are) long enough, then two or more NAOs and/or SOs may be extended. Fifth step. Ensure that all the SO/NAO series in the fourth step are related to or associated with at least one of the ISRC cycles mentioned in Section 3.4. Sixth step. If the fifth step is satisfactorily completed, then draw a longterm mean curve through all the graphical structures realised in the fourth step. The curve is extended through the extended SO/NAO structures mentioned in the fourth step. Ensure that this curve is related to at least one of the ISRC cycles. Seventh step. Make predictions on the basis of the envelopes of the SO/NAO structure(s) extended in the third step or on the basis of the curve extended in the sixth step or on the basis of the average trends of the individual SO/NAO structure(s) just mentioned above. For a given set of data, the prediction based on envelopes or mean trends of the individual SO/NAO structures is more detailed than that based on the overall average curve for all the SO/NAO structures. In order to make the art of implementing the ETM as clear as possible, a number of illustrative examples are given below. In the first example, variations of average temperature in central England up to 2050 are predicted and justified. In the second example, variations of mean temperature in Stockholm (Sweden) and Svalbard Lufthavn (near the north pole) up to 2040 are predicted and accounted for. In the third example, predictions of global mean temperature up to and beyond 2100 are made and justified. Other examples are given in connection with Greenland, Austria and global mountain glaciers. The predictions made are for temperature variations. However, parallel predictions can easily be deduced for all those weather/climate parameters which are related to temperature. For example, temperature is inversely proportional to absolute humidity (ie. water vapour density), relative humidity, specific humidity, vapour pressure, dew point and mixing ratio. Also temperature is directly proportional to saturation specific humidity, saturation vapour pressure and saturation mixing ratio. It is hoped that after going through all the illustrated climate predictions, one should be able to successfully predict any other future climate changes using the ETM. Note that in a nearly similar manner, the ETM may be used to predict future volcanic activity and occurrences of earthquakes. For example, all the

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earthquakes variation patterns in chapter 7 may easily be forward-projected using the ETM.

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Illustrative Example One Look at the average temperature variations in central England from 1660 to 1970 (see thin solid lines) plotted in Figure 8.1. The long-term mean of the variations represented by the thin solid lines has been plotted in the Figure using a thick solid curve. This curve is part of the temperature oscillation related to a serial combination of a 400 – 550 years cycle and a 1000 – 1250 years cycle (see Figure 1.2) whose next maximum is expected to occur at around 2063. Figure 8.2 illustrates the temperature oscillation related to a serial combination of a 400 – 550 years cycle and a 1000 – 1250 years cycle in more details. Calculations show that the oscillation related to a serial combination of a 400 – 550 years cycle and a 1000 – 1250 years cycle in Figure 8.2 will expectedly reach its next maximum at around 2063. Some NAO/SO series have been fitted onto the thin solid-line variations in Figure 8.1 using dotted curves. It is noted that the NAO/SO patterns have a consistent period equal to that of the 170 – 250 years solar cycle illustrated in Figure 7.7. In the NAO/SO series in Figure 8.1, a change from NAO to SO or vice versa takes place during the early rising phase of the latter solar cycle. There was a change from NAO to SO in about 1935 (see Figure 8.1). Obviously the SO which started at around 1935 is expected to display a minima around 1970 and the next maximum around 2055 as illustrated in Figure 8.1. Since this maximum approximately coincides with the next maxima in Figures 1.3 and 8.2, central England will start on a prolonged cooling trend at around 2060. Analysis of winter temperature variation records in England and Wales (reported in Burroughs [127]) shows that these variations are dominated by a period equal to that of the 170 – 250 years solar cycle. They are expected to reach the next maximum in 2060 – 2080. For the sake of thoroughness, we have also taken records of temperature variations in midlatitudes 45 – 55 °N from Dick [128] and analysed them. The analysis shows that these temperature variations are dominated by an NAO mode from 1904 to 1970 and an SO mode after 1970. Both modes have a period equal to that of the second harmonic of the 80 – 120 years solar cycle. The temperature patterns display a maximum around 2000 and are expected to reach the next minimum around 2035.

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Figure 8.1. A plot of average temperature in central England from 1660 to 1970 (see thin solid lines). The long-term average of the thin solid-line variations has been plotted using a thick solid line. Also dotted curves have been used to plot out the NAO/SO series formed by the thin solid-line variations. A transition from NAO to SO or vice versa is indicated by an arrow. We have reproduced by kind permission the thin solid-line variations from Lamb H. H. (1982): Climate, History and the Modern World, Methuen, London.

Figure 8.2. The estimated average accumulated warmth of the growing seasons prevailing at sites near the upper limit of cereal cultivation in the hill country of southeast Scotland in the period 1856 – 1995 (dashed line) and its variations (solid line). Reproduced by kind permission from Lamb H. H. (1982): Climate, History and the Modern World, Methuen, London.

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Illustrative Example Two Plotted in thin solid lines in Figure 8.3 are annual mean temperature variations for Stockholm (Sweden) and Svalbard Lufthavn. Some NAOs and SOs have been fitted onto the thin solid-line variations using dashed lines. Also a long-term average of the thin solid-line variations has been drawn using a thick solid curve. The latter curve represents the temperature oscillation associated with the 400 – 550 years solar cycle and the 1000 – 1250 years solar cycle (see Figure 1.2) whose next maximum is expected to occur around 2063. Now the series of NAOs and SOs in Figure 8.3 display a periodicity equal to that of the second harmonic of the 80 – 120 years solar cycle. Note that a change from NAO to SO or vice versa takes place in Figure 8.3 about 10 years after a maximum or a minimum of the latter solar cycle. And each NAO mode (or SO mode) goes through an approximately one oscillation cycle before changing to the other mode. On this basis, the SO for Stockholm and NAO for Svalbard Lufthavn that started around 1970 are expected to proceed up to 2040 as illustrated in Figure 8.3. While the next NAO for Stockholm will expectedly make temperature non-increasing after ~ 2040, the next SO for Svalbard Lufthavn will expectedly decrease temperature after about 2060. Considering the timing of the global temperature oscillation associated with the 400 – 550 years solar cycle and the 1000 – 1250 years solar cycle and the next major peak of global volcanic eruptions which is expected around 2035 (see chapter 6), temperatures in Stockholm and Svalbard Lufthavn are expected to start on a long-term decreasing trend at around 2060. During the last major peak of volcanic activity (which took place around 1830), temperature was suppressed downwards at global level (eg. see Figure 1.2), in the whole of the northern hemisphere (eg. see page 317 of Lamb [82]) and in England (eg. see Figure 8.2). Dick [128] reports temperature variations in the Arctic region (60 – 90 °N) from 1904. An analysis of these variations shows that they are dominated by an SO mode at a period equal to that of the second harmonic of the 80 – 120 years solar cycle. These variations display a maximum around 2000 and are expected to reach the next minimum around 2035.

Illustrative Example Three The NAO/SO series for global mean surface temperature variations are plotted in Figure 8.4 using dashed lines. These NAO/SO series are riding upon

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Annual mean temperature (°C)

the 400 – 550/1000 – 1250 years temperature oscillation in Figure 1.2 whose next maximum will expectedly occur around 2063.

8

(a)

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1940

1940

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Figure 8.3. Annual mean temperature variations for (a) Stockholm (Sweden) and (b) Svalbard Lufthavn plotted in thin solid lines. Dashed lines have been used to sketch out the NAO/SO series formed by the thin solid lines. Also thick solid curves have been drawn through the long-term averages of the solid-line variations. We have reproduced by kind permission the thin solid lines from Karlen W. (2005): “Recent global warming: an artefact of a too-short temperature record?”, Ambio 34, 263 – 264.

The NAO/SO series in Figure 8.4 display a variation period equal to that of the second harmonic of the 80 – 120 years solar cycle. Note that each NAO mode or SO mode lasts for a duration similar to the period of the latter second harmonic before changing to the other mode. Also the NAO/SO series form a continuous sawtooth wave with a period equal to that of the second harmonic of the 80 – 120 years solar cycle. The sawtooth wave has minima approximately coinciding with maxima and minima of the latter solar cycle. There is a transition from SO to NAO between ~ 2000 and ~ 2010. This transition and the ensuring NAO should stop or even reverse the post – 1970 global warming trend up to about 2040. This is because the post – 2000 NAO (like the post – 1880 NAO) is partly sawtooth shaped and hence displays a generally decreasing trend during its initial ~ 30 years. It is existence of such temperature decreasing trend starting just after ~ 2000 that will extinct and slightly reverse global warming up to around 2040. The expected major

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maximum of global volcanic activity (at ~ 2035) and the next maximum of the 400 – 550/1000 - 1250 years global temperature oscillation (at ~ 2063) will combine with the other processes given earlier to make global mean temperature start on a long-term decreasing trend around 2060 (see Figure 8.5). The predictions shown in the latter Figure have been made using the ETM prediction steps given earlier in this section. Available records [119] show that global mean temperature variations since 2000 have been approximately following the predictions given in Figure 8.5. Recent records also show that a slight leveling off of the rise in temperature of the top 700 metres of the world‟s oceans has been in existence since 2003. o

C

0.6 0.4 0.2

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0.0 -0.2 -0.4 -0.6

1860

1880

1900

1920

1940

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2000

TIME IN YEARS Figure 8.4. A plot of global mean surface temperature from 1856 to 2001. The bars represent annual values as departures from the 1961 – 1990 mean. Also the smooth curve shows the results of filtering the annual values to reveal long-term fluctuations. The NAO/SO series formed by the bars are sketched out using dashed lines. A change from NAO to SO or vice versa is indicated by an arrow. We have reproduced by kind permission the bars from Tiempo, Issue 43 (March 2002), p. 26.

Records of global sea level variations available in Strahler [142] implicitly indicate existence (in those records) of a 170 – 250 years oscillation. This oscillation has a minimum around 1895 and a maximum apparently between 2000 and 2012. Interestingly this maximum coincides with the start of the global cooling trend shown in Figure 8.5.

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~ 270 years long cooling trend

Figure 8.5. ETM based predictions of global mean surface air temperature up to and beyond year 2100.

Corresponding to the predictions in Figure 8.5 are other predictions presented in the 1990 IPCC report [83] and based on GCMs (see Figure 8.6). The 1995, 2001 and 2007 IPCC reports present predictions more or less similar to those shown in Figure 8.6. It is easy to realise that if Kirchhoff‟s law of radiation and solar activity influence on climate are ignored, then the variations in Figure 8.6 will overlap or closely match with those in Figure 8.5. In order to take into account Kirchhoff‟s law of radiation accurately, GCMs will have to deal with the whole atmosphere below altitude 60 – 70 km. And in order to take into account all major Sun-Climate relationships, GCMs will have to do away with spatial and time-dependent averaging processes. In addition it will be necessary for GCMs to inherit the structures of all important

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temperature oscillations that are ongoing at the starting times of the models. This inheriting process can be easily facilitated by the ETM.

Figure 8.6 Lowest value (see lower curve) and highest value (see upper curve) of global mean temperature above its 1765 value from 2000 up to 2100 as derived from predictions in the IPCC‟s 1990 report [83]. These predictions are based on the business-as-usual scenario.

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SEASONAL RAINFALL (mm)

1400 1200 1000 800 600 400

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Figure 8.7. Seasonal rainfall at Tabora (5° 5'S, 32° 50'E), Tanzania from 1924 to 1985 (see solid lines). The average of the solid-line variations has been drawn using a thick solid line. Also dashed curves have been used to plot the NAO and SO formed by the thin solid lines.

Figure 8.8. A plot of annual precipitation at a station near Springfield in Colorado (U.S.A.) from 1890 up to 1970 (solid lines). The dominant SO formed by the solid lines has been plotted using dashed curves. The solid lines have been reproduced by kind permission from Critichfield H. J. (1974): General Climatology, Prentice – Hall, Englewood Cliffs, N. J.

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Figure 8.9. Annual rainfall at Seoul, Korea from 1770 up to 1944 (solid lines). Discontinuous lines have been used to plot the NAOs and SOs formed by the solid-line variations. Phase changes in NAO/SO structures are indicated by arrows. Except for the arrows and dashed curves, the diagram has been reproduced by kind permission from Flohn H. (ed) (1969): General Meteorology 2, Elsevier Publishing Company, Amsterdam.

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OTHER ILLUSTRATIVE EXAMPLES (i) Example concerning Greenland The three illustrative examples given above form a small percentage of climate predictions already made (by the author) using the ETM. All those predictions that are not included in this book were made simply by following the prediction steps listed earlier in this section. One of these predictions has been based on the records of oxygen isotope variations in northwest Greenland from 300 A.D. which have been arranged to read as equivalent to a temperature curve (see Lamb [82]). Application of the ETM to this particular Greenland temperature record has yielded predictions that may be summarized as follows. The warming trend that started in Greenland at about 1960 is expected to proceed up to about 2050. Thereafter Greenland will undergo a large and rapid cooling trend at least up to about 2100 under the influence or association of the 170 – 250 years solar cycle and the 400 – 550 years solar cycle. There is obvious consistency between this particular prediction (concerning Greenland temperature) and the predictions illustrated in Figure 8.3. Simple forward extrapolations of the temperature patterns in the latter Figure shows that Stockholm and Svalbard Lufthavn (which may be taken to represent the Arctic) will start on a cooling trend in 2050 – 2060. Separate

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analysis of temperature variations in north-west Greenland from 300 A.D. done by Njau [129] shows that these variations are dominated by a period equal to that of the 400 – 550 years solar cycle. These temperature variations are expected to reach the next maximum around 2070. (ii) Examples concerning Austria and global mountain glaciers A record of yearly means of air temperature in 58 Austrian stations from 1775 to 1990 has been recorded and analysed in Njau [73]. The analysis shows that from 1775 to 1970 the temperature variations are characterized by NAO waveforms at a period equal to that of the second harmonic of the 80 – 120 years solar cycle. Around 1970 the NAO waveforms changed to SO waveforms at the same periodicity. On this basis, Austria is expected to undergo a cooling trend from 2000 – 2010 up to about 2035. In addition, Austria temperature variations are also strongly characterized by a period equal to that of the 170 – 250 years solar cycle. Thus variation patterns of Austria temperature at a period of 170 – 250 years had the last minimum at around 1900. These patterns are expected to reach their next maximum in 2035 – 2050. Thereafter Austria will expectedly start on a long-term cooling trend that will exist beyond 2100. Haeberli et al. [130] and Rothlisberger [131] report a series of changes in global mountain glaciers since 1520. On being analysed, these changes have yielded the following results. The patterns formed by the cumulative glacier mass/length changes vary at similar period but in anti-phase mode with the global temperature oscillation in Figure 1.2. Remember that the latter oscillation is formed by a portion at a period equal to that of the 400 – 550 solar cycle and another portion at a period equal to that of the 1000 – 1250 years solar cycle as detailed in chapters 1 and 3. The global temperature oscillation in Figure 1.2 had its last minimum in about 1625 and is expected to reach its next maximum in about 2060. This temperature variation is accompanied by inverse variations in absolute humidity, relative humidity and specific humidity. As would be expected, the masses/lengths of the global mountain glaciers had their last maximum around 1625. Specifically the 23 Swiss glaciers and the Grindelwald glacier reached their last maxima in 1600 – 1660 (eg. see Rothlisberger [131]). Therefore it is expected that the ongoing retreat/depletion of the global mountain glaciers will stop and reverse around 2060.

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8.3. Predicted Future Deadly Droughts On the basis of the contents in the previous chapters, it is clear that precipitation variations and hence occurrences of droughts are associated with one or more of the GHW waveforms. Look, for example, at the seasonal rainfall variations in Tabora, Tanzania displayed in Figure 8.7. These variations are dominated by an NAO before 1966 and an SO after 1966, all at a periodicity equal to that of the 11-years solar cycle. So the droughts that took place at Tabora in the early 1970s and early 1980s are clearly associated with the 11-year solar cycle. Significant correlations between rainfall variations and the 11-years solar cycle have been reported by Hargreaves [33] in connection with rainfall in Australia, latitude 50° – 60° N, latitude 60° – 70° N and latitude 70° – 80° N. Apart from the 11-years solar cycle, the 22-years solar cycle has been significantly correlated with rainfall and occurrences of droughts in South Africa, the U.S.A., Australia and Brazil [33]. The duration and seriousness of droughts increase with the period of the GHW cycles they are associated with. Thus a look at Figure 3.2, therefore, shows that the deadliest droughts between years 1800 and 2100 are those associated with the 80 – 120 years solar cycle. This point of view will be verified using past records before predictions are made for timings of the next deadly droughts. Variations in annual precipitation at a station near Springfield in Colorado (U.S.A.) are shown in Figure 8.8. The average of these variations has main minima approximately coinciding with maxima and minima of the 80 – 120 years solar cycle in Figure 3.2. In other words, the rainfall variations in Figure 8.8 are dominated by an oscillation whose period is equal to that of the second harmonic of the 80 – 120 years solar cycle. Next look at the rainfall variations at Seoul, South Korea shown in Figure 8.9. These rainfall variation patterns are characterised by the following three features. First, they undergo phase changes whenever the thick dashed curve and thin dashed horizontal line in Figure 3.2 cross each other. Second, they make an approximately complete cycle between two adjacent arrows in Figure 8.9. And third, they have minima/maxima coinciding with maxima and minima of the 80 – 120 years solar cycle. This means that the rainfall variation patterns oscillate at a dominant period equal to that of the second harmonic of the 80 – 120 years solar cycle. Forward extrapolations of the plots in Figures 8.8 and 8.9 show that major droughts will occur in the U.S.A. and Korea during 2030 – 2040.

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Figure 8.10. General rainfall in England and Wales (thin, solid and vertical lines) as a percentage of the 1881 – 1915 average from 1726 up to 1960. The NAOs and SOs formed by the solid lines have been plotted using dashed curves. Arrows show timings at which phase changes take place in NAO/SO structures. Except for the arrows and dashed curves, the diagram has been reproduced by kind permission from Manley G. (1962): Climate and the British Scene, Collins, London.

Rainfall variations in England and Wales (see Figure 8.10) display characteristics comparable to those already mentioned in connection with rainfall at Seoul, South Korea. The rainfall variation patterns in England and Wales have the following three characteristics. First, they change phase only at the times during which the thick dashed curve and thin dashed (horizontal) line in Figure 3.2 cross each other. Second, the minima/nodes of the rainfall patterns coincide approximately with minima of the 80 – 120 years solar cycle. And third, the antinodes of the rainfall patterns approximately coincide with maxima of the 80 – 120 years solar cycle. This third characteristic is shown by Figure 8.11 to exist even beyond the duration of Figure 8.10. Forward extrapolation of the variations in Figure 8.10 shows that rainfall variation patterns in England and Wales will experience an antinode-to-node transition during 2030 – 2040. In East Africa rainfall patterns are dominated by an oscillation w hose period is equal to that of the second harmonic of the 80 – 120 years solar cycle [2]. For example, the annual rainfall patterns at Murang‟a, Kenya (see Figure 8.12) have nodes approximately coinciding with maxima and minima of the 80 – 120 years solar cycle. A major drought occurs just after each node. As explained further in Njau [2], temperature variations in the southern Africa

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region since 1900 have also been dominated by a period equal to that of the second harmonic of the 80-120 years solar cycle. These variations have a maximum in 2003 – 2010 and are expected to reach the next minimum around 2040.

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Figure 8.11. Annual precipitation levels recorded for the River Kerry in northwest Scotland from1957 to 1991 (solid lines). The NAO formed by the solid lines has been plotted using dashed curves. Except the dashed curves, the diagram has been reproduced by kind permission from Hastie et al. (2003): Ambio 32, 40 - 42.

Figure 8.12. A plot of annual rainfall at Murang‟a (0° 43‟ S, 37° 10‟ E), Kenya from 1901 up to 1996 (solid lines). The dominant NAO formed by the solid-lines has been drawn using dashed curves.

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60 (a) SAHEL Annual rainfall departure (%)

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0

-20 -40 -60 1880

1900

1920

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Time in years

140 % of 1931 – 60 Mean

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Figure 8.13. Annual rainfall variations in the Sahel region (see thin solid lines whose average is shown by the thick solid curve) from 1900 to 1992. Dashed lines have been used to draw the dominant SOs formed by the thin solid lines.

120

(b) EDGE OF SAHEL

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Figure 8.14. Annual rainfall variations at the edge of the Sahel region (see solid lines). Dashed lines have been used to draw the dominant NAO and SO formed by the solid lines.

Recall that the major drought in the Sahel region of Africa that happened in the 1970s hit newsmedia headlines all over the world. That drought came as a surprise for nobody could have predicted it. With the knowledge currently at

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our disposal, we can certainly predict occurrence of any drought of that magnitude. Let us now look at the past rainfall variation patterns in the Sahel region (Figure 8.13) and at the edge of the Sahel region (Figure 8.14). All these patterns are clearly dominated by an oscillation whose period is equal to that of the second harmonic of the 80 – 120 years solar cycle. On this basis, forward extrapolations obviously show that both the Sahel region and its edge (represented by Figure 8.14) will experience a major drought between years 2020 and 2030. This particular drought, like the 1970s Sahelian drought, is related to the 80 – 120 years solar cycle. The account given above can provide clues on what made the 1970s Sahelian drought so biting. Around 1940 fairly rapid temperature and other climate changes took place in different regions of the world (eg. see Figures 5.5, 5.8, 5.14 and the Figures in this section). These rapid changes coincide with the time at which the 80 – 120 years solar cycle crossed its equilibrium level (see Figure 3.2). The Sahel region was not exempted from taking part in these rapid global climate changes. Consequently the dominant oscillation in the Sahelian rainfall patterns (whose period is equal to that of the second harmonic of the 80 – 120 years solar cycle) underwent the following rapid changes around 1940 (see Figure 8.13). First, it rapidly changed its phase and jumped onto a phase of about 69° before a maximum. Second, it was rapidly amplified. These two rapid changes greatly lowered the next rainfall minimum and also greatly increased the gradient magnitude along the next falling phase of the dominant rainfall oscillation. It appears that the 1970s drought in the Sahel region was caused by changes in global temperature patterns which in turn changed the ITCZ‟s seasonal variation patterns that are climatically influential to the Sahel region. The latter patterns are obviously a determining factor in the rainfall variation patterns in the Sahel region. Reports by Salinger [121] and Riehl [122] show that rainfall variations in Australia, New Zealand, Senegal and around Puerto Rico are strongly related to the 80 – 120 years solar cycle. In the Australia – New Zealand region, rainfall variation patterns have major minima/nodes that coincide with maxima and minima of the 80 – 120 years solar cycle. In other words, these rainfall patterns are dominated by an oscillation whose period is equal to that of the second harmonic of the 80 – 120 years solar cycle. As far as rainfall variation patterns in Senegal and around Puerto Rico are concerned, these patterns have major minima at and around maxima and minima of the 80 – 120 years solar cycle. So these patterns are dominated by an oscillation whose period is equal to that of the second harmonic of the 80 – 120 years solar cycle.

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Relevant calculations reveal that the next minimum of the 80 – 120 years solar cycle is expected to occur between 2020 and 2035. This realisation together with the account already given in this Section certainly show that deadly droughts are expected to occur in different regions around the Earth between 2020 and 2035. Other deadly droughts thereafter can be predicted using the associations between rainfall variation patterns and the GHW waveforms. Clearly the focus in this section has been on prediction of deadly droughts. However, the same methodology may be tailored for and used in predictions of other climatic phenomena. In this way it can easily be shown that both the next antinode in the patterns of Figure 5.9 and the next minimum in the patterns of Figure 5.8 are expected to occur around 2015. By implication, a stinging El Nino is expected to take place around the latter year. In a similar manner, analysis of records of Atlantic hurricane frequency variations indicate occurrence of a major maximum around 2035. Interestingly it is around the latter year that maxima of earthquake activity and volcanic activity are also expected to occur as elaborated in chapter 6 to 7.

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APPENDIX MATHEMATICAL DERIVATION OF THE MERIDIONAL GENERAL CIRCULATION MODEL IN FIGURE 5.11 We start with awareness of the observed 3-cell tropospheric general circulation in Figure 2.5 of chapter 2. Consider a region (hereinafter called “region Ω”) centred at point P in Figure A1 and which includes part of the stratosphere above the Hadley cells and the circulation air motions flowing towards and away from P. Under steady state conditions, the vertical and horizontal air velocity patterns in region Ω will be functions of x and z. This means that gravitational forces, Coriolis forces, buoyant forces, pressuregradient forces and other relevant forces maintain continuous air motion patterns whose meridional velocity components are functions of spatial locations. We are here assuming existence of an approximately steady 3-cell meridional general circulation in the troposphere. This steadiness-based assumption is commonly used in several meteorology/climatology textbooks. The assumption just mentioned may be represented mathematically as: and

(A.1)

where t denotes time, A(x, z) and B(x, z) are functions analytic in a domain G of the x, z - plane. Note that A(x, z) # 0 and also B(x, z) # 0 since we are interested in air motions which trace curves through region Ω. Here the theory of limits requires existence of functions:

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Ernest C. Njau x = x(t) and z = z(t)

(A.2)

which satisfy equations (A.1) for a specific range of t. Let us now make the transformation: and

(A.3)

where , r, α and s are all variable parameters. A combination of equations (A.1) and (A.3) and expansion of the resultant A and B terms into Taylor‟s series finally yields

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(A.4)

(A.5) where Ax, Az, Axx, Axz and Azz are partial derivatives of A(x, z) and also Bx, Bz, Bxx, Bxz and Bzz are partial derivatives of B(x, z). The singular points of equations (A.1) are the intersections of the curves A(r, s) = 0 and B(r, s) = 0. Suppose that one of the singular points is located at point Bo (ro, so). Then the characteristic equation of the motions in region Ω with respect to the latter point is given as

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(A.6)

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where P = Bx(ro, so), Q = Bz(ro, so), R = Ax(ro, so), T = Az(ro, so) and w is a variable. Equation (A.6) is a characteristic equation of the system governed by equations (A.1). According to the stability theorem of nonlinear mechanics (which is also called Liopounoff‟s theorem), the characteristic roots of equation (A.6) determine the stability characteristics of the air motions in region Ω [e.g. Davis [120], Kryloff and Bogoliuboff [123]]. The following equation is easily obtained from a combination of equations (A.1):

(A.7) We assume that the following solution of equation (A.7) exists throughout some specific domain G: (A.8) The first equation in equations (A.1) can be solved explicitly for x in terms of z and

Also the second equation in equations (A.1) can be solved

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explicitly for z in terms of x and

. Thus we can represent this realisation by

the equations: (A.9) where

and

.

Now differentiation of the two equations (A.1) gives

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(A.10)

(A.11)

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Ernest C. Njau If we now replace

equations (A.9),

by A(x, z) from equations (A.1), x by F(z, ) from

by B(x, z) from equations (A.1) and z by H(x,

from

equations (A.9) in equations (A.10) and (A.11), we get (A.12) (A.13) Equation (A.12) is satisfied separately by z(t) while equation (A.13) is satisfied separately by x(t). For a system governed by equations (A.1), equations (A.12) and (A.l3) are found to be identical. Thus x(t), as well as z(t), is a solution of the characteristic equation (A.14) Therefore, the explicit expressions for x and z are given as

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(A.15) where a, b, c and d are constants and k1 and k2 are the roots of equation (A.6). If t is now eliminated from equations (A.l5) we get the equation (A.16)

where M =

. Equation (A.16) represents generally the

meridional curves followed by averaged air motions in region Ω. It is noted that equation (A.16) plots the Hadley cells through region Ω only when both k1 and k2 are real, but differing in sign. But when equation (A.16) plots out the Hadley cells in this way, it also inevitably plots a pair of circulation cells above the Hadley cells as schematically illustrated in Figure A.2. Thus existence of one circulation cell above each Hadley cell is implied by application of the laws of nonlinear mechanics. In other words, it has been proved using non-linear mechanics that Figure A.1. should be presented in a more complete and detailed form by Figure A.2.

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Figure A.1. Schematic section of meridional air motions in the equatorial parts of the general circulation as commonly found in meteorology/climatology textbooks. It displays no circulation cells above the Hadley cells.

A further conceptual justification for transformation of Figure A.1 into Figure A.2 may be based on kinematic arguments. If there is a saddle point at the tropopause (eg. near point P in Fig. A.1), then by continuity there must be a second circulation above each Hadley cell (as shown in Figure A.2). Now the key question is whether there is a saddle point at the tropopause. According to standard meteorology textbooks, the rising air (in the rising branch of the Hadley cell) reaches the tropopause, which acts like a barrier, causing the air to move laterally towards the poles. But this barrier imparts onto the rising air some downward force due to the weight of the air in and above the tropopause. Consequently some of the latter air is inevitably dragged into the horizontal motions of the upper branches of the Hadley cells, thus continuously creating a saddle point at the tropical tropopause due to continuity considerations. Justification for existence of a saddle point at the equatorial tropopause may also be deduced from the widely reported time-height section of monthly-mean zonal wind component in the lower stratosphere near the equator from 1953 to 1985 (eg. see Peixoto and Oort [10]). An analysis of this time-height section clearly reveals continuous existence of downward air motions in the equatorial lower stratosphere (eg. see Njau [2]). A saddle point is obviously formed as the

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downward motions encounter the motions in the rising and upper horizontal branches of the Hadley cells. We have repeated the whole analysis already given in this section after replacing region Ω with another region near the top of: (i) The falling branch of a Hadley cell and the adjacent falling branch of a mid-latitude cell, and (ii) The rising branch of a mid-latitude (or Ferrel) cell and the adjacent rising branch of a polar cell. When dealing with (i) and (ii) above, we assumed existence of circulations consisting of rising cold air and sinking warm air due to forcing by waves and vortexes or eddies. This is necessary because outside the tropics, the circulation is (mostly) characterised by the Lagrangian flow, which is driven by waves and heating/cooling. All these analyses led to firm conclusions that one circulation cell exists just above each mid-latitude cell and also one circulation cell exists just above each polar cell. These conclusions have been arrived at through application of the stability theorem of nonlinear mechanics.

Figure A.2. Same as Figure A.1 but with addition of the circulation cells (above the Hadley cells) which have been established theoretically in the text.

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Appendix

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What we have established theoretically is existence of one 3-cell meridional circulation just above the troposphere. If this new circulation does not reach the magnetosphere, then application of non-linear mechanics laws to the regions around the top parts of its vertical branches (as we have done through equations (A.1) to (A. 16) with respect to the tropospheric circulation) would establish existence of another relatively higher 3-cell meridional circulation. The trend similarly continues with establishing of 3-cell meridional circulations until the topmost 3-cell meridional circulation reaches the top of the magnetosphere. Also the two highest cells of the latter circulation mechanically couple to two open circulation cells (with infinitely large radii) formed by the solar wind along and outside the topmost layer of the magnetosphere. Expectedly the open circulation cells just mentioned are not followed on the top side by circulation cells because they are incomplete and open. Generally the implication here is that there exists between the earth‟s surface and the top of the magnetosphere two or more 3-cell meridional circulation systems arranged one on top of another into a fluid mechanical pattern looking very much like an arrangement of loosely or smoothly coupled gears. For the sake of brevity, we shall hereinafter refer to the just mentioned mechanical pattern as “surface-to-magnetosphere circulation systems” or simply “SCS”. The branches of the circulation cells making up the SCS are made of air motions. But since air is a gas and is fundamentally turbulent, it does not necessarily move like a rigid mechanical system. Individual air parcel motions execute extremely complex trajectories. Moreover, the mode of causation of circulation entities is waves interacting with critical surfaces, which are only weakly related to the location of circulation cells. It should, therefore, be stressed here that existence of the SCS is based on net air movements along its circulation cells regardless of the nature, causes and other characteristics of the physical processes which ultimately give rise to these net air movements. This is why the SCS is a fluid mechanical system of gears to which the rules governing a corresponding rigid mechanical system of gears can be relevantly applied. As the solar wind continues to impinge upon the day-side magnetopause, it creates (along the magnetospheric top portion) a continuous meridional fluid flow which mechanically and positively couples onto the two topmost branches of the topmost 3-cell circulation of the SCS. Such positive mechanical coupling (which effectively makes the earthward solar wind form two incomplete circulation cells at infinitely large radii just above the topmost 3-cell circulation of the SCS) is possible only if the SCS consists of an odd number of 3-cell meridional circulations. Actual existence of the SCS has been

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verified using available atmospheric records [Njau [2]]. The verified SCS consists of three 3- cell meridional circulation systems, one in troposphere, one in the stratosphere-mesosphere, and one in the thermosphere (see Figure 5.11). Before proceeding further, let us look in more details at the SCS circulation cells outside the tropics. It is well known that the direct Hadley cells are much stronger than the indirect Ferrel cells. Also the direct polar cells are quite weak. On this basis, the directly opposing circulations at the SCS regions labelled A (see Figure 5.11) effectively make Eulerian circulation not very useful outside the tropics. If one puts red dye into the Ferrel cell one will find that the dye flows poleward and downward, in an effective extension of the Hadley cell. The circulation flow outside the tropics is thus mostly characterised by the Lagrangian flow, which is driven by waves and heating/cooling. The Stokes drift by Rossby waves is greater than the Eulerian circulation. In particular, the directly opposing SCS circulations in the regions labelled A (see Figure 5.11 ) would appear to make the Ferrel cells (as they actually are) only small statistical residues which result after zonal averaging of large, almost compensating, northward and southward flows in the quasistationary atmospheric waves. Also the directly opposing SCS circulations just mentioned above can give rise to large waves and vortexes in the upper air levels. The upper air tropospheric motions in middle latitudes are superimpositions of vortexes, waves and a weak meridional circulation. But both the waves and vortexes (some of which can be formed within the SCS concepts) would carry cold air equatorward and warm air poleward by forcing cold air to rise and warm air to sink. So the key concepts in the SCS agree reasonably well with realities and observations as further detailed in Njau [2]. Since its topmost branches physically contact the solar wind which also partly penetrates into the magnetosphere at low latitudes, the whole SCS together with the two incomplete or open circulation cells formed just above it by the solar wind collectively act as some form of smoothly coupled gear system with: (i) Extremely large mechanical advantage (MA) and velocity ratio (VR) for mechanical disturbances applied at the top of the magnetosphere, and (ii) Infinitely large MA and VR for mechanical disturbances in the day-side solar wind just outside the magnetopause. Note that the magnetosphere responds readily and rapidly to changes in the solar wind, and that it experiences some degree of solar disturbances at all times [Hargreaves [33]]. Implicitly, small perturbations at the topmost branch of the SCS by solar wind variations can cause significantly large variations in the tropospheric 3-cell meridional circulation and hence in corresponding

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climate/weather changes. Perhaps it is not surprising, therefore, that the SCS has recently been used to successfully explain all the observed relationships between climate variations and the solar wind as well as the interplanetary magnetic field [Njau [2]]. As detailed in the latter reference, the SCS also successfully explains observed relations (Stringer [124], Pittock [39]) between tropospheric air circulations and the times at which solar-wind sector boundaries cross the earth.

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REFERENCES [1] [2] [3]

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[4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14]

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[96] Njau E. C. (2009): “Influence of electric power transmissions upon climate, earthquakes and volcanic eruptions”, University of Dar es Salaam Preprint No. UD/2009/1, pp. 21. [97] Njau E. C. (2008): “Variability of geothermal energy emissions”, Accepted abstract for the World Renewable Energy Congress X, Glasgow, Scotland, 19 – 25 July 2008. [98] Jaggar T. A. (1931): “Volcanic cycles and sunspots”, Volcano Letter, No. 32b. [99] Davidson C. (1938): Studies on the periodicity of earthquakes, Murby, London. [100] Aki K. (1956): “Some problems in statistical seismology”, J. Seismol. Soc. Japan 8, 205 – 228. [101] Simpson G. C. (1967): “Earthquakes and solar activity”, Quart. J. R. Soc. 93, 217 – 220. [102] Stothers R. B. (1989): “Volcanic eruptions and solar activity”, J. Geophys. Res. 94, 17371 – 17381. [103] Njau E. C. (2009): “Mechanisms linking solar activity to variations in earthquakes, geothermal energy emissions and volcanic activity – Part 1”, University of Dar es Salaam Preprint No. UD/09/99. [104] Njau E. C. (2009): “Mechanisms linking solar activity to variations in earthquakes, geothermal energy emissions and volcanic activity – Part 2”, University of Dar es Salaam Preprint No. UD/09/214. [105] Lundgren L. (1986): Environmental geology, Prentice-Hall, Englewood Cliffs, New Jersey. [106] Kauffman J. (1990): Physical geology, Prentice-Hall, Englewood Cliffs, New Jersey. [107] Bullard F. M. (1962): Volcanoes: in history, in theory, in eruption, University of Texas Press, Austin.. [108] Ollier C. (1969): Volcanoes, The MIT Press, Cambridge. [109] Decker R. W. and Decker B. B. (1991): Mountains of fire, Cambridge University Press Cambridge.. [110] Bath M. (1979): Introduction to Seismology, Birkhauser Verlag, Boston. [111] Bollinger G. A. (1969): “Seismicity of the central Appalachian states of Virginia, West Virginia and Maryland – 1758 through 1968”, Bull. Seism. Soc. Am. 59, 2103 – 2111. [112] Meinel A. and Meinel M. (1991): Sunsets, Twilight and Evening Skies, Cambridge University Press, Cambridge. [113] Davies K. (1990): Ionospheric Radio, Peter Peregrinus Ltd,. London.

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[114] Ratcliffe J. A. (1972): An introduction to the ionosphere and magnetosphere, Cambridge University Press, Cambridge. [115] Budden K. G. (1985): The propagation of radio waves, Cambridge University Press, Cambridge. [116] Srivastava H. N. (1983): Forecasting earthquakes, National Book Trust, India. [117] Kiehl J. T. and Ramanathan V. (eds) (2006): Frontiers of climate modelling, Cambridge University Press, Cambridge. [118] Stensrud D. J. (2007): Parameterization schemes: Keys to understanding numerical weather prediction models, Cambridge University Press, Cambridge. [119] An article titled “Scientists: The Earth has not warmed for decade” that appeared in several newspapers in 2009, for example see Daily News (Tanzania), 23 November 2009. [120] Davis H. T. (1962): Introduction to nonlinear differential and integral equations, Dover Publications, New York. [121] Salinger J. (1994): “Climate change in the Pacific”, Tiempo 14, 17 – 19. [122] Riehl H. (1978): Introduction to the Atmosphere, McGraw-Hill Book Company, New York. [123] Kryloff N. and Bogoliuboff N. (1943): Introduction to nonlinear mechanics, Princeton University Press, Princeton. [124] Stringer E. T (1972): Techniques of Climatology, W. H. Freeman and Company, San Francisco. [125] Milton D. (1974): “Some observations of global trends in tropical cyclone frequencies”, Weather 29, 267 – 270. [126] Kellogg W. W. (1978): “Effects of human activities on global climate – Part II”, WMO Bulletin XXVII, 3 – 10. [127] Burroughs W. J. (1980): “Average temperature and rainfall figures in British winters”, Weather 35, 75 – 79. [128] Dick C. (2005): “Frozen assets: the cryosphere‟s role in the climate system”, WMO Bulletin 54, 75 – 82. [129] Njau E. C. (2005): “Expected halt in the current global warming trend”, Int. J. Renewable Energy 30, 743 – 752. [130] Haeberli W., Maisch M. and Paul F. (2002): “Mountain glaciers in global climate-related observation networks”, WMO Bulletin 51, 18 – 25. [131] Rothlisberger F. (1980): “Tree – rings and climate: A retrospective survey and new results”, WMO Bulletin XXIX, 170 – 177.

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[132] Limbert D. W. S. (1991): “Weather events of 1990 and their consequences”, WMO Bulletin 40, 328 – 351. [133] Farman J. C., Gardiner B. G. and Shanklin J. D. (1985): “Large losses of total ozone in Antarctica reveal seasonal ClOx/NOx interaction”, Nature 315, 207 – 212. [134] Rex M. et al. (1998): “In situ measurements of stratospheric ozone depletion rates in the Arctic winter 1991/1992: A Lagrangian approach”, J. Geophys. Res. 103, 5843 – 5853. [135] Solomon S. (1999): “Stratospheric ozone depletion: A review of concepts and history”, Rev. Geophys 37, 275 – 316. [136] Chanin M. L. (2001): “Stratospheric ozone and its impact on climate change”, WMO Bulletin 50, 41 – 45. [137] WMO (2003): “Scientific assessment of ozone depletion: 2002”, WMO Report No. 47, Geneva. [138] Fischer A. and Staehelin J. (2003): “The Antarctic ozone hole: 1996 2002”, WMO Bulletin 52, 264 – 269. [139] McFarlane N., Ravishankara A. and O‟Neill A. (2005): “From ozone hole to chemical climate prediction”, WMO Bulletin 54, 65 – 74. [140] Njau E. C. (1994): “An electronic system for predicting air temperature and wind speed patterns”, Int. J. Renewable Energy 4, 793 – 805. [141] Njau E. C. (1997): “A new analytical model for temperature predictions”, Int. J. Renewable Energy 11, 61 – 68. [142] Strahler A. N. (1971): The Earth Sciences, Harper & Row Publishers, New York.

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INDEX A

C

aerosols, 23, 52, 53, 54 Africa, 100, 110, 143, 145 age, 11, 49 agricultural sector, 4 agriculture, viii airborne particles, 1, 33, 53 Alaska, 51 amplitude, 17, 39, 41, 43, 58, 60, 61, 63, 66, 68, 76, 79, 81, 82, 86, 87, 88, 91, 97, 98, 109, 111, 112 annual rate, 12, 99 Aristotle, 48 atmospheric pressure, 2, 27 Australia, 14, 142, 146 Austria, 131, 141 authors, 16 availability, 3 averaging, 129, 137, 156 awareness, 149

cable system, 101, 108 cables, 100 calcium, 105 Canada, 6, 33, 82, 83, 89 carbon, 11, 13, 14, 16, 23, 36, 39, 40, 53, 81 carbon dioxide, 11, 13, 16, 23, 53, 81 carrier, 43 causation, 155 cell, 26, 28, 29, 77, 149, 152, 153, 154, 155, 156, 163 China, 79, 80 circulation, xi, 6, 14, 24, 26, 28, 29, 31, 51, 54, 77, 78, 92, 100, 117, 119, 129, 149, 152, 153, 154, 155, 156, 161 climate change, vii, 6, 7, 15, 31, 33, 35, 36, 40, 47, 48, 49, 50, 53, 54, 55, 57, 69, 76, 80, 84, 86, 95, 96, 99, 100, 101, 102, 105, 107, 115, 116, 117, 125, 129, 130, 131, 146, 163, 166 CO2, 11, 12, 13, 14, 15, 16, 17, 18, 33, 54, 89, 90, 96, 97 combustion, 14, 33 combustion processes, 33 communication, 34, 100, 101, 102, 108, 118 communication technologies, 34, 101, 102, 118 components, 7, 47, 51, 58, 59, 61, 62, 65, 66, 68, 70, 90, 91, 98, 118, 149 composition, 7, 30, 106

B biosphere, 7, 35, 160 Brazil, 142 bromine, 93 burning, 53

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168

Index

concentration, 11, 13, 16, 96 condensation, 52 consensus, 54 constant rate, 97 continuity, 6, 26, 153 convergence, xi, 25 cooling, 11, 14, 44, 80, 82, 83, 90, 101, 132, 136, 140, 141, 154, 156 copper, 101 correlation, 43, 62, 126 correlations, 52, 54, 71, 142 cosmic ray flux, 52 cosmic rays, 52, 76, 93 couples, 155 coupling, 51, 155 cycles, 15, 39, 50, 52, 58, 62, 65, 71, 74, 76, 78, 83, 87, 88, 96, 97, 98, 100, 103, 110, 123, 131, 142, 162, 163, 164 cyclones, 14, 78, 92

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D decisions, vii, 5 deficiencies, 51 definition, 1, 3, 7, 19, 23, 29, 30, 70 density, 1, 2, 3, 26, 37, 101, 118, 122, 131 derivatives, 150 destruction, 51, 93 differentiation, 151 diffraction, 162 distortions, 86, 87, 125 distribution, 21, 52 division, 2, 126 dominance, 62, 83 drought, 143, 145, 146 duration, 4, 61, 67, 135, 142, 143 dynamics, 7, 52

E earth, 1, 7, 11, 12, 19, 21, 24, 28, 49, 50, 54, 58, 65, 66, 69, 90, 101, 111, 115, 123, 155, 157, 159 electric conductivity, 105, 122

electric current, 51, 100, 101, 106, 107, 110, 116, 117, 118, 119, 123 electric field, 34, 100, 101, 108 electricity, 105 electromagnetic, 33, 109, 117, 118, 119 electromagnetic fields, 33 electromagnetic waves, 117, 118, 119 electronic circuits, 125 electrons, 36 emission, 14, 52 energy, 7, 21, 23, 24, 33, 34, 36, 37, 50, 52, 53, 54, 57, 58, 59, 61, 64, 65, 66, 67, 68, 69, 73, 74, 88, 90, 91, 96, 97, 98, 99, 100, 107, 109, 116, 119, 121, 122, 125, 160, 162, 163, 164 energy density, 122 energy emission, 107, 164 enforcement, 93 England, 80, 131, 132, 133, 134, 143 environment, 54 equilibrium, 15, 23, 25, 33, 44, 58, 84, 88, 89, 146 Europe, 6, 100, 102 evaporation, 21, 30, 49, 52, 58 evolution, 40 extrapolation, 44, 143

F factories, 99 farmers, 5 feedback, 52 floating, 106 fluctuations, 63, 124, 136 fluid, 37, 106, 155 forecasting, 5, 159 fossil, 14, 53 friction, 27, 78 fuel, 14

G gases, xi, 15, 33, 51, 53, 88, 93, 102 generation, 34, 52

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Index geography, viii geological history, 49, 50 geology, viii, 164 Germany, ix global climate change, 50, 146 graph, 103, 130 gravitational force, 19, 20, 149 Greece, 109 greenhouse gases, 15, 24, 33, 51, 53, 88, 95 growth, 79, 96 growth rate, 96 growth rings, 79 guidance, viii, 53

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H Hawaii, 96, 97 heat, xi, 14, 22, 23, 33, 44, 52, 53, 54, 58, 62, 70, 71, 73, 74, 76, 97, 98, 99, 100, 105, 115, 116, 119, 121, 126, 162 heating, 24, 58, 118, 154, 156 height, 2, 3, 27, 153 hemisphere, xi, 26, 27, 28, 29, 63, 80, 83, 90, 92, 124, 134 histogram, 107, 111, 112 human activity, 7, 116 humidity, 3, 4, 131, 141 hurricanes, 14, 78, 90 hydrogen, 36, 51 hypothesis, 49, 50

I Iceland, 70, 102 ideal, 3, 62 implementation, 117, 130 India, 25, 84, 165 indicators, 95 indices, 35, 43 industrial revolution, 8, 9, 30, 99 institutions, viii instruments, 4 integration, 75 interaction, 43, 86, 166

169

interactions, 51, 70 iron, 105 isotherms, 27 isotope, 8, 140 Israel, 160

J Japan, 6, 86, 107, 113, 114, 161, 164 justification, 97, 98, 153

K Kenya, 143, 144 Korea, 140, 142

L land, 7, 19, 54, 63 land use, 54 language, 6, 86 laws, 33, 54, 152, 155 line, 6, 8, 10, 11, 12, 38, 39, 42, 64, 70, 72, 79, 81, 84, 85, 96, 102, 103, 109, 112, 113, 115, 116, 126, 132, 133, 134, 135, 139, 140, 142, 143

M magnetic field, 1, 34, 36, 37, 38, 39, 100, 101, 102, 107, 108, 116, 117, 118, 119, 157 magnetosphere, xi, 1, 29, 37, 117, 118, 119, 122, 125, 155, 156, 165 maintenance, 96 mantle, 101, 105, 107, 122, 123 mass loss, 36 meanings, 123 measures, 35, 71 methodology, 43, 64, 74, 89, 96, 100, 115, 147 military, 117 Milky Way, 40

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Index

mixing, 131 model, xi, 5, 6, 51, 53, 77, 78, 129, 162, 166 modelling, 6, 165 models, 6, 14, 24, 43, 129, 138 modernisation, 53, 57 modulations, 119 moisture, 52 momentum, 37, 78, 100 Moon, 20 Moscow, ix, 31, 159 motion, 20, 40, 58, 61, 66, 68, 149

N

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Netherlands, 161 New York, iii, iv New Zealand, 146 newspapers, 165 nitrogen, 51, 93 nitrogen oxides, 93 nodes, 62, 84, 86, 87, 109, 114, 143, 146 North Africa, 25, 102

O observations, 4, 9, 50, 101, 110, 156, 165 oceans, 7, 12, 13, 14, 25, 26, 29, 32, 52, 58, 90, 136 orbit, 19, 20, 39, 84, 117, 118 order, 12, 51, 58, 89, 106, 118, 127, 131, 137 orientation, 118 oscillation, xi, 6, 9, 15, 17, 24, 53, 62, 67, 70, 71, 76, 79, 80, 82, 83, 86, 87, 88, 90, 91, 93, 96, 98, 102, 107, 109, 110, 114, 120, 122, 126, 132, 134, 135, 136, 141, 142, 143, 146 overlap, 120, 137 oxygen, 3, 8, 105, 140 ozone, 2, 21, 30, 51, 53, 78, 92, 93, 115, 166

P Pacific, 70, 90, 110, 161, 165 parallel, 26, 100, 131 parameter, 27, 42, 86, 130 parameters, 3, 7, 11, 20, 30, 35, 41, 44, 48, 54, 55, 76, 80, 88, 115, 126, 131, 150, 163 particles, 1, 21, 33, 35, 36, 51, 53, 119 passive, 33, 54 periodicity, 35, 41, 42, 49, 53, 63, 80, 82, 83, 87, 101, 109, 113, 114, 134, 141, 142, 164 permeability, 122 permission, ix, 5, 6, 8, 10, 13, 18, 22, 23, 25, 28, 31, 32, 37, 38, 40, 63, 64, 73, 79, 81, 82, 85, 86, 97, 107, 109, 111, 112, 113, 115, 116, 121, 124, 127, 133, 135, 136, 139, 140, 143, 144 Philippines, 101 philosophers, 48 photosynthesis, 21, 33, 58 physical laws, 25 physical mechanisms, 50, 51 physics, 47 polarity, 39 positive correlation, 9, 11, 126 power, 51, 99, 100, 108, 117, 118, 125, 130, 164 power lines, 100, 118 precipitation, 3, 4, 14, 49, 52, 139, 142, 144 prediction, 5, 102, 129, 131, 136, 140, 147, 165, 166 prediction models, 165 present value, 19 pressure, 1, 2, 3, 4, 25, 26, 27, 28, 51, 52, 70, 71, 78, 131, 149 Puerto Rico, 146 pulse, 8, 10, 11, 15, 16, 84, 91

R radar, 4

Modern Science of Climate Changes, Nova Science Publishers, Incorporated, 2010. ProQuest Ebook Central,

Index

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radiation, xi, 4, 15, 17, 19, 20, 21, 22, 23, 24, 33, 35, 39, 40, 48, 49, 50, 51, 52, 53, 54, 57, 65, 88, 96, 97, 98, 100, 107, 137, 160 Radiation, 159 radio, 4, 35, 117, 118, 125, 165 rainfall, 30, 78, 80, 84, 139, 140, 142, 143, 144, 145, 146, 147, 165 range, 2, 4, 6, 39, 42, 61, 101, 150 reactions, 37 reason, ix, 3, 15, 42, 47 recommendations, iv reflection, 21, 48 region, 29, 37, 78, 80, 82, 83, 110, 114, 115, 116, 126, 134, 144, 145, 146, 149, 150, 151, 152, 154 relationship, 53, 63, 76, 96, 101, 103, 107, 108, 117, 121 relevance, 83 renewable energy, 163 residues, 156 resolution, 4 respect, 24, 33, 53, 54, 64, 65, 66, 75, 81, 126, 150, 155

Spain, 114 spatial location, 149 spectrum, 58, 60, 61, 97, 98 speed, 13, 15, 27, 90, 166 stability, 67, 68, 151, 154 storms, 118, 119 strain, 119, 121 strategies, viii strength, 118, 119 students, viii submarines, 118 substitution, 76 succession, 49, 68 summer, 25, 30, 49, 79, 84, 85 Sun, 7, 19, 20, 21, 23, 25, 33, 35, 36, 37, 38, 39, 40, 42, 43, 48, 50, 51, 52, 53, 64, 99, 100, 122, 129, 137, 160, 161 supply, 3, 101, 125 surface area, 22, 23 surface layer, 52 Sweden, 131, 134, 135 switching, 130 symbols, 2, 120

T

S satellite, 4, 50 saturation, 131 scatter, 117 scientific method, 106 sea level, 2, 126, 127, 136 sea-level, 71 search, 129 seasonal component, 58 shape, 20, 98, 127 shear, 4, 27 signals, 98, 120, 125 silicon, 105 SOI, xi, 70, 71, 72 solar system, 19, 20, 40 South Africa, 142 South Korea, 142, 143 Southeast Asia, 25 space, 6, 21, 24, 54, 58, 96, 129, 161

171

tanks, 118 Tanzania, 139, 142, 165 textbooks, 42, 58, 65, 149, 153 thermal energy, 20, 33, 53, 57 thermal expansion, 106 thinking, 47 time periods, 7 timing, 44, 134, 159 trade, 28 transformation, 150, 153 transition, 86, 133, 135, 143 transmission, 118 transpiration, 21, 58 trends, 8, 81, 101, 131, 165 turbulence, 62 Turkey, 107, 109

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Index

U UN, 55 United Kingdom, ix, 6 United Nations, xii, 7, 31 UV, xii, 2, 51

V

Wales, 132, 143 waste, 33, 99, 100, 116 waste heat, 99, 100 wave number, 65, 66, 69 wavelengths, 2, 20, 23, 57, 70, 126, 128 West Africa, 159 wind, 1, 3, 4, 13, 14, 25, 27, 28, 29, 36, 37, 38, 50, 51, 52, 54, 57, 78, 90, 100, 118, 119, 122, 153, 155, 156, 159, 166 winter, 25, 30, 32, 49, 51, 70, 84, 92, 132, 166

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variability, 7, 42, 48, 50, 85, 95, 126, 127, 159 velocity, 4, 26, 27, 36, 37, 72, 74, 117, 119, 126, 149, 156

W

Modern Science of Climate Changes, Nova Science Publishers, Incorporated, 2010. ProQuest Ebook Central,