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