Description

Book Synopsis

Under certain scenarios on the subject of CO2 emissions, by the end of the century the atmospheric concentration could triple its pre-industrial level.

The very large numerical models intended to anticipate the corresponding climate evolutions are designed and quantified from the laws of physics. However, little is generally known about these: genesis of clouds, terms of the greenhouse effect, solar activity intervention, etc.

This book deals with the issue of climate modeling in a different way: using proven techniques for identifying black box-type models. Taking climate observations from throughout the millennia, the global models obtained are validated statistically and confirmed by the resulting simulations.

This book thus brings constructive elements that can be reproduced by anyone adept at numerical simulation, whether an expert climatologist or not. It is accessible to any reader interested in the issues of climate change.



Table of Contents

CHAPTER 1. INTRODUCTION 1

1.1. Context 1

1.2. Identification 3

1.3. Expectations and results 5

1.4. Contents of the work 6

CHAPTER 2. CLIMATIC DATA 11

2.1. Sources 11

2.2. Global temperature 12

2.2.1. Modern temperatures 12

2.2.2. Pre-industrial temperature 13

2.2.3. Paleotemperatures 14

2.3. Concentration of CO2 in the atmosphere 17

2.4. Solar activity 18

2.5. Volcanic activity 26

CHAPTER 3. THE WAR OF THE GRAPHS 29

3.1. History 29

3.2. Inconsistent controversies 35

3.3. Usable data 38

CHAPTER 4. FORMULATING AN ENERGY BALANCE MODEL 41

4.1. State models and transmittance 41

4.2. Structure of an energy balance model 44

4.3. Specificity of EBMs 47

4.4. Dynamic parametrization 49

CHAPTER 5. PRESUMED PARAMETERS 55

5.1. Terminology 55

5.2. Climate sensitivity Sclim 57

5.3. Coefficient of radiative forcing ?Ñ1 58

5.4. The climate feedback coefficient ?ÜG 58

5.5. Sensitivity to irradiance S2 59

5.6. Sensitivity to volcanic activity S3 61

5.7. Climate or anthropogenic sensitivity 61

5.8. Review of uncertainties 63

CHAPTER 6. IDENTIFICATION METHOD 67

6.1. The current state of affairs 67

6.2. Output error method 69

6.3. Estimating the error variance 70

6.4. Hypothesis test and confidence regions 72

6.5. Conditions of application 73

CHAPTER 7. PARTIAL RESULTS 75

7.1. A selection of data 75

7.2. Free identification 77

7.3. Forced identifications 81

7.4. Statistical analysis 86

CHAPTER 8. OVERALL RESULTS 91

8.1. Preliminary comments 91

8.2. Regions and intervals of confidence 93

8.3. Hypothesis test 96

8.4. Comments 97

CHAPTER 9. HISTORIC MINUSCULE SIMULATIONS 99

9.1. Overview of IPCC simulations 99

9.2. Comparative simulations 100

9.3. Representative concentration pathways (RCPs) 102

9.4. Comparative radiative forcing 105

CHAPTER 10. LONG-TERM CLIMATE PROJECTIONS 107

10.1. IPCC scenarios and projections 107

10.2. EBM compatible scenarios 109

10.3. Long-term projections 110

10.4. A disaster scenario 113

CHAPTER 11. SHORT-TERM PREDICTIONS 115

11.1. Decadal time scale predictions by GCM 115

11.2. The climate’s natural variability 117

11.3. State estimate and prediction 120

11.4. Decadal time scale predictions by EBM 123

11.5. A posteriori predictions 124

CHAPTER 12. CONCLUSIONS 129

12.1. On the identification 129

12.2. Climate sensitivity 130

12.3. Solar activity 131

12.4. Predictive capacity 132

12.5. The climate change in question 133

12.6. Prospects 133

BIBLIOGRAPHY 135

INDEX 141

Climate Change: Identification and Projections

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      Publisher: ISTE Ltd and John Wiley & Sons Inc
      Publication Date: 21/11/2014
      ISBN13: 9781848217775, 978-1848217775
      ISBN10: 1848217773
      Also in:
      Climate change

      Description

      Book Synopsis

      Under certain scenarios on the subject of CO2 emissions, by the end of the century the atmospheric concentration could triple its pre-industrial level.

      The very large numerical models intended to anticipate the corresponding climate evolutions are designed and quantified from the laws of physics. However, little is generally known about these: genesis of clouds, terms of the greenhouse effect, solar activity intervention, etc.

      This book deals with the issue of climate modeling in a different way: using proven techniques for identifying black box-type models. Taking climate observations from throughout the millennia, the global models obtained are validated statistically and confirmed by the resulting simulations.

      This book thus brings constructive elements that can be reproduced by anyone adept at numerical simulation, whether an expert climatologist or not. It is accessible to any reader interested in the issues of climate change.



      Table of Contents

      CHAPTER 1. INTRODUCTION 1

      1.1. Context 1

      1.2. Identification 3

      1.3. Expectations and results 5

      1.4. Contents of the work 6

      CHAPTER 2. CLIMATIC DATA 11

      2.1. Sources 11

      2.2. Global temperature 12

      2.2.1. Modern temperatures 12

      2.2.2. Pre-industrial temperature 13

      2.2.3. Paleotemperatures 14

      2.3. Concentration of CO2 in the atmosphere 17

      2.4. Solar activity 18

      2.5. Volcanic activity 26

      CHAPTER 3. THE WAR OF THE GRAPHS 29

      3.1. History 29

      3.2. Inconsistent controversies 35

      3.3. Usable data 38

      CHAPTER 4. FORMULATING AN ENERGY BALANCE MODEL 41

      4.1. State models and transmittance 41

      4.2. Structure of an energy balance model 44

      4.3. Specificity of EBMs 47

      4.4. Dynamic parametrization 49

      CHAPTER 5. PRESUMED PARAMETERS 55

      5.1. Terminology 55

      5.2. Climate sensitivity Sclim 57

      5.3. Coefficient of radiative forcing ?Ñ1 58

      5.4. The climate feedback coefficient ?ÜG 58

      5.5. Sensitivity to irradiance S2 59

      5.6. Sensitivity to volcanic activity S3 61

      5.7. Climate or anthropogenic sensitivity 61

      5.8. Review of uncertainties 63

      CHAPTER 6. IDENTIFICATION METHOD 67

      6.1. The current state of affairs 67

      6.2. Output error method 69

      6.3. Estimating the error variance 70

      6.4. Hypothesis test and confidence regions 72

      6.5. Conditions of application 73

      CHAPTER 7. PARTIAL RESULTS 75

      7.1. A selection of data 75

      7.2. Free identification 77

      7.3. Forced identifications 81

      7.4. Statistical analysis 86

      CHAPTER 8. OVERALL RESULTS 91

      8.1. Preliminary comments 91

      8.2. Regions and intervals of confidence 93

      8.3. Hypothesis test 96

      8.4. Comments 97

      CHAPTER 9. HISTORIC MINUSCULE SIMULATIONS 99

      9.1. Overview of IPCC simulations 99

      9.2. Comparative simulations 100

      9.3. Representative concentration pathways (RCPs) 102

      9.4. Comparative radiative forcing 105

      CHAPTER 10. LONG-TERM CLIMATE PROJECTIONS 107

      10.1. IPCC scenarios and projections 107

      10.2. EBM compatible scenarios 109

      10.3. Long-term projections 110

      10.4. A disaster scenario 113

      CHAPTER 11. SHORT-TERM PREDICTIONS 115

      11.1. Decadal time scale predictions by GCM 115

      11.2. The climate’s natural variability 117

      11.3. State estimate and prediction 120

      11.4. Decadal time scale predictions by EBM 123

      11.5. A posteriori predictions 124

      CHAPTER 12. CONCLUSIONS 129

      12.1. On the identification 129

      12.2. Climate sensitivity 130

      12.3. Solar activity 131

      12.4. Predictive capacity 132

      12.5. The climate change in question 133

      12.6. Prospects 133

      BIBLIOGRAPHY 135

      INDEX 141

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