Extreme Events in Nature and Society (eBook)

Sergio Albeverio: Studied mathematics and physics; professorships and research positions at several universities (in Europe, USA, Russia, Japan, China); now professor at the Department of Applied Mathematics and Director of Interdisciplinary Center for Complex Systems at the University of Bonn. Volker Jentsch: Studied physics and geophysics; worked in Max Planck Institutes, universities and scientific administration; now co-director at the Interdisciplinary Center for Complex Systems at the University of Bonn.

Preface 6
Contents 8
List of Contributors 14
1 Extreme Events: Magic, Mysteries, and Challenges 17
1.1 Why Study Xevents? 17
1.2 What are Xevents? A First Approach 18
1.3 What are Xevents? A Second Approach 19
1.4 How the Book is Organised 25
1.5 Outlook: Research Programme 33
References 34
General Considerations 35
2 Anticipating Extreme Events 36
2.1 The Representation of Extreme Events 36
2.2 From Signs to Anticipation 38
2.3 Descartes Rehabilitated 40
2.4 Time, Clocks, Rhythms 41
2.5 The Hybrid Solution 43
2.6 Can a Computer Simulate Anticipation? 50
2.7 A New Equilibrium 51
2.8 A Holistic View 55
References 58
3 Mathematical Methods and Concepts for the Analysis of Extreme Events 61
3.1 Introduction 61
3.2 Statistical Extreme Value Theory 62
3.3 Extremes in Continuous Time: Stochastic Processes, Random Fields 66
3.4 Extremes and Statistical Mechanics 75
3.5 Extremes and Dynamical Systems 76
3.6 Mapping Singularities and Catastrophe Theory: How Can They Be Related to Xevents? 77
References 79
4 Dynamical Interpretation of Extreme Events: Predictability and Predictions 83
4.1 Introduction 83
4.2 Prediction versus Predictability 86
4.3 An Example: Turbulent Wind Gusts 98
4.4 Conclusions 104
References 107
5 Endogenous versus Exogenous Origins of Crises 108
5.1 Introduction 108
5.2 Exogenous and Endogenous Shocks in Social Networks 110
5.3 Exogenous and Endogenous Shocks in Financial Markets 122
5.4 Concluding Remarks 127
References 129
Scenarios 133
6 Epilepsy: Extreme Events in the Human Brain 134
6.1 Introduction 134
6.2 Basic Mechanisms 135
6.3 EEG and Epilepsy 137
6.4 Nonlinear EEG Analysis 139
6.5 Can Epileptic Seizures Be Anticipated? 146
6.6 Can Epileptic Seizures Be Controlled? 149
6.7 Conclusions 151
References 152
7 Extreme Events in the Geological Past 155
7.1 Introduction 155
7.2 Extreme Events in the Geological Past 156
7.3 Predictions and Forecasts on the Geological Timescale 169
7.4 Research Perspectives 171
References 174
8 Wind and Precipitation Extremes in the Earth’s Atmosphere 179
8.1 Introduction 179
8.2 Atmospheric Scales 180
8.3 Wind Extremes 182
8.4 Precipitation Extremes 191
8.5 Discussion 196
References 197
9 Freak Ocean Waves and Refraction of Gaussian Seas 198
9.1 Introduction 198
9.2 Gaussian Seas 201
9.3 Refraction 203
9.4 Refraction and Gaussian Seas 206
9.5 Structure of the Density Fluctuations 209
9.6 Implications for Wave Statistics 213
9.7 Conclusions 217
References 218
10 Predicting the Lifetime of Steel 220
10.1 Introduction 220
10.2 The Search for Defects: Positrons in Solids 221
10.3 The Bonn Positron Microprobe 226
10.4 Detection of Plastic Deformation 226
10.5 Damage Prediction 231
10.6 Summary 239
References 239
11 Computer Simulations of Opinions and their Reactions to Extreme Events 242
11.1 Introduction 242
11.2 General Opinion Dynamics 243
11.3 Damage Spreading 250
11.4 Discussion 264
References 265
12 Networks of the Extreme: A Search for the Exceptional 267
12.1 Extreme Events in Complex Systems and Our Perception of Them 267
12.2 A Short Survey of Scale-Free Networks 269
12.3 Cameo Graphs 270
12.4 How Extremists Determine the Structures of Scale- Free Graphs 274
12.5 Spreading of Epidemics in Scale-Free Networks and Robustness Under Random Attack 277
12.6 Conclusions and Outlook 279
12.7 Appendix 280
References 281
Prevention, Precaution, and Avoidance 283
13 Risk Management and Physical Modelling for Mountainous Natural Hazards 284
13.1 Introduction 284
13.2 Risk Management Example for Mountain Roads 285
13.3 Physical Modelling of Alpine Surface Processes to Support Natural Hazard Forecasting 291
13.4 Conclusions 297
References 299
14 Prevention of Surprise 301
14.1 Introduction 301
14.2 Dynamic Model 304
14.3 Static Model 312
14.4 Discussion 320
References 323
15 Disasters as Extreme Events and the Importance of Network Interactions for Disaster Response Management 324
15.1 Disasters as Extreme Events 324
15.2 Examples of Causality Chains and Cascade Effects 326
15.3 Modeling Causality Networks of Disaster Spreading 339
15.4 Summary and Conclusions 350
References 351
Index 354