Extreme Events

Observations, Modeling, and Economics

Mario Chavez, Michael Ghil, Jaime Urrutia-Fucugauchi, Mario Chavez, Michael Ghil, Jaime Urrutia-Fucugauchi

• Publisher: Wiley-Blackwell
• Year: 2015
• Print ISBN: 9781119157014
• eBook ISBN: 9781119157038
• Edition: 1
• Topic: Politics & International Relations
• Subtopic: Environment & Energy Policy
• Index: Politics & International Relations

The monograph covers the fundamentals and the consequences of extreme geophysical phenomena like asteroid impacts, climatic change, earthquakes, tsunamis, hurricanes, landslides, volcanic eruptions, flooding, and space weather. This monograph also addresses their associated, local and worldwide socio-economic impacts. The understanding and modeling of these phenomena is critical to the development of timely worldwide strategies for the prediction of natural and anthropogenic extreme events, in order to mitigate their adverse consequences.

This monograph is unique in as much as it is dedicated to recent theoretical, numerical and empirical developments that aim to improve:

(i) the understanding, modeling and prediction of extreme events in the geosciences, and, (ii) the quantitative evaluation of their economic consequences. The emphasis is on coupled, integrative assessment of the physical phenomena and their socio-economic impacts.

With its overarching theme, Extreme Events: Observations, Modeling and Economics will be relevant to and become an important tool for researchers and practitioners in the fields of hazard and risk analysis in general, as well as to those with a special interest in climate change, atmospheric and oceanic sciences, seismo-tectonics, hydrology, and space weather.

1
Introduction

Mario Chavez,¹ Michael Ghil,^2,3 and Jaime Urrutia-Fucugauchi⁴

¹Instituto de Ingeniería, Universidad Nacional Autónoma de México (UNAM), México, DF, México

²Geosciences Department, Environmental Research & Teaching Institute (CERES-ERTI), and Laboratoire de Meteorologie Dynamique (CNRS and IPSL), Ecole Normale Supérieure, Paris, France

³Department of Atmospheric & Oceanic Sciences and Institute of Geophysics & Planetary Physics, University of California, Los Angeles, CA, USA

⁴Instituto de Geofísica, Universidad, Nacional Autónoma de México, (UNAM), México, DF, México

The recent occurrence of events like the European 2003 heat wave, the Sumatra 2004 earthquake, the 2005 Hurricane Katrina, the Tohoku 2011 earthquake, the 2012 Hurricane Sandy, and the Nepal 2015 earthquake represented not only climatic or geophysical extremes, but they have had or will have large and long-lasting consequences in large segments of the world population. In each case, these events impacted systemic, structural, and socioeconomic weaknesses in the societies found in their path. The common characteristic of these events is that they reached larger intensities, durations or both, when compared with previous observations of the same phenomena; they also had or still have an impact on health, infrastructures, ecosystems, or the economy of the world region where they occurred. It is relevant, moreover, to mention that high-impact geophysical events may be qualified as being extreme by a society, although a similar event occurring in a different region or under different conditions would not have the same impact and thus would not be qualified as an extreme event by the same or a different society.

Taking into account the characteristics of geophysical extreme events, this book focuses on the aspects that are related to their observation and their modeling, as well as to estimating their socioeconomic impacts. The book brings together different communities of researchers and practitioners in the fields of the climate sciences and geophysics, mathematics and statistics, economy, and sociology; it gathers, in a unified setting, 21 representative related to extreme events research, many of which include applications to their impact on society or the environment.

Most of the 21 chapters included deal with novel methodologies and their applications for the study of extreme events and their impacts. The chapters are grouped into six themes. Part I is composed of five chapters on fundamentals and theory, one covering the statistical analysis of environmental and temperature data, two on dynamical system approaches to the analysis of extreme events, another one on climate tipping points, and the fifth one on a delay differential equation study of the El Niño–Southern Oscillation (ENSO). Part II has two chapters related to extreme events in Earth's space environment: one chapter analyzes extreme events in space weather, and the other the Chicxulub asteroid impact associated with the mass extinction at the K/T boundary.

Part III deals with climate and weather extremes, and it contains four chapters: one on extreme flooding in the midwest of the United States, the second one on the impacts of the 2005 Hurricane Wilma, the third on observations and modeling of damages caused by the 2004 Indian Ocean tsunami, and the fourth chapter on rogue wave events in a laboratory setting of capillary waves. Part IV is dedicated to extreme events in the solid earth and it includes three chapters, the first on a multiproxy approach for great magnitude earthquakes and tsunamis, the second on landslide risks in Italy, and the third one on an extreme event approach to volcanic eruptions.

Part V addresses, in four chapters, the socioeconomic impacts of extreme events: the first of these uses classical extreme value theory to study the economic impact of extreme events and in particular of hurricanes, the second chapter relies on a hybrid approach to assess the direct economic impacts of extreme-magnitude earthquakes, the third chapter is on tropical cyclones and their socioeconomic impacts, and the fourth one is on natural disasters and their impacts on a dynamic, nonequilibrium economy. Finally, in Part VI, three chapters deal with the very difficult and controversial issue of predicting extreme events and with the closely related one of preparedness: the first chapter treats extreme tsunami events in the Mediterranean region and their impact on the Algerian coasts, the second analyzes the complexity surrounding high-technology extreme events, in particular, the 2011 failure of the Fukushima nuclear power plant, while the third paper reviews a group effort on the predictive understanding of extreme events and its applications to disaster preparedness. We summarize here the main contributions of each of these chapters.

1.1. PART I: FUNDAMENTALS AND THEORY

In Chapter 2, G. Toulemonde and colleagues argue that the classical statistical assumption in analyzing extreme events, namely that of independence in space, time, or both, may not be valid in the geosciences in most cases. Furthermore, the statistical modeling of such dependences is complex and different modeling roads should be explored. First, the authors present some basic concepts of univariate and multivariate extreme value theory (EVT), followed by a series of examples on how this theory can help the practitioner to make inferences about extreme quantiles in a multivariate context.

In Chapter 3, C. Nicolis and G. Nicolis propose a deterministic dynamical systems approach to identify the principal signatures of the statistical properties of extremes. Then, the authors derive analytical expressions for n-fold cumulative distributions and their associated densities, for the exceedance probabilities and for the spatial propagation of extremes. Numerical simulations that exhibit substantial differences from classical EVT theory complement these analytical results. These differences are illustrated for dynamical systems giving rise to quasi-periodic behavior, intermittent chaos, and fully developed chaos, respectively.

In Chapter 4, S. Siegert and associates discuss the application of a physical weather model and a simple data-based model to probabilistic predictions of extreme temperature anomalies; the comparison between the two uses the concept of skill scores. The authors found that, although the result confirms the expectation that the computationally much more expensive weather model outperforms the simple data-based model, the performance of the latter is surprisingly good. Furthermore, they assert that over a certain parameter range, the simple data-based model is even better than the uncalibrated weather model. They propose the use of receiver operating characteristic (ROC) statistics to measure the performance of the predictors, and find that using this type of scoring, the conclusions about model performance partly change, which illustrates that predictive power depends on its exact definition.

In Chapter 5, T. Lenton and V. Livina apply concepts from dynamical systems theory to study extreme events in the climate system. In particular, they focus on “tipping points” or discontinuities, previously known as bifurcations in a system's large-scale behavior, and on the prospects for providing early warning for their imminent occurrence. The authors describe general methods for detecting and anticipating tipping points, for systems with a high level of internal variability that sample multiple states in time, as well as for systems with less variability that reside in a single state. They apply those methods to the ice-core record of abrupt climate changes in Greenland during the last ice age. Finally, they discuss the limitations of the general methods, and suggest combining them with system-specific vulnerability indicators and process-based models, to help assess the future vulnerability of different tipping elements in the climate system.

In Chapter 6, M. Ghil and I. Zaliapin study a delay differential equation (DDE) for ENSO in the relatively novel setting of non-autonomous dynamical systems and of their pullback attractors. This setting provides deeper insights into the variability of the sea surface temperature T in the Tropical Pacific. Their model includes three essential ENSO mechanisms: the seasonal forcing, the negative feedback due to the oceanic waves, and the delay caused by their propagation across the Tropical Pacific. Two regimes of model variability, stable and unstable, are analyzed. In the unstable regime and in the presence of a given, purely periodic, seasonal forcing, spontaneous transitions occur in the mean T, in the period, and in the extreme annual values. They conclude, among other findings, that the model's behavior exhibits phase locking to the seasonal cycle, namely the local maxima and minima of T tend to occur at the same time of year, which is a characteristic feature of the observed El Niño (warm) and La Niña (cold) events.

1.2. PART II: EXTREME EVENTS IN EARTH'S SPACE ENVIRONMENT

In Chapter 7, A. Ruzmaikin and co-authors apply the Max Spectrum statistical method, which is based on the scaling properties of speed maxima, to study the Sun's fast coronal mass ejections (CMEs). This kind of extreme space weather event is a disturbance in the space environment that presents hazards to the operation of spacecraft systems, instruments, or lives of astronauts. Empirical studies have shown that the speed distribution of CMEs is non-Gaussian. By applying the Max Spectrum technique to CMEs observations, the authors identified the range of speeds, of about 700–2000 km/s, that separates extreme CMEs from typical events. From their investigation of the temporal behavior of fast CMEs, it was concluded that they were not independent, but arrived in clusters and thus can be described by a compound Poisson process.

In Chapter 8, J. Urrutia-Fucugauchi and L. Pérez-Cruz analyzed the highly exceptional Chicxulub asteroid impact event at the Cretaceous/Paleogene boundary, and its effects on the Earth's climate, environment and life-support systems. This boundary marks one of the major extinction events in the Phanerozoic, which affected about 75% of species on Earth. First, the authors examined the impact event and the cratering in Mexico's Yucatán Peninsula and the waters off it, the timescales involved and the energy released. Then, they assessed the impact's regional and global effects, which involved major perturbations in the ocean and atmosphere. Finally, the authors discussed how and to what extent life-support systems are affected by extremely large impact events, and what the fossil record reveals about the extinction event and biotic turnover. In particular, they examined how sudden and extended the processes involved are, as well as the temporal records of extinction and recovery.

1.3. PART III: CLIMATE AND WEATHER EXTREMES

In Chapter 9, A. W. Robertson and colleagues studied Midwestern floods and, in particular, the April 2011 flooding event in the Ohio River Basin. The authors used a K-means clustering algorithm for daily circulation types during the March–May spring season to infer relationships between flooding events and circulation types, as well as relationships between these types and climate drivers; the drivers in this study included the interannual ENSO and the intraseasonal Madden-Julian oscillation (MJO). Their results suggest that anomalous southerly fluxes of moisture from the Gulf of Mexico are associated with weather types that occur in connection with the floods, while two of these circulation types are preferentially associated with La Niña. Statistically significant lagged relationships between the frequency of occurrence of these regimes and the MJO were also identified, and they are associated with convection propagating from the Indian Ocean to the Maritime Continent. Implications for prediction across timescales are also discussed.

In Chapter 10, E. Mendoza and associates analy...

Table of contents

• Cover
• Title Page
• Table of Contents
• CONTRIBUTORS
• PREFACE
• ACKNOWLEDGMENTS
• 1 Introduction
• Part I: Fundamentals and Theory
• Part II: Extreme Events in Earth’s Space Environment
• Part III: Climate and Weather Extremes
• Part IV: Extreme Events in the Solid Earth
• Part V: Socioeconomic Impacts of Extreme Events
• Part VI: Prediction and Preparedness
• INDEX
• End User License Agreement