Non-Linear Dynamics in Geophysics Jacques Dubois Although initiated in the 1960s by the studies of Richardson and Mandelbrot, the study of natural phenomena using the mathematical tools employed for the understanding of ‘chaos’ is comparatively recent. Indeed the field of applications for such techniques is very large because many natural phenomena exhibit chaotic dynamics. In Non-Linear Dynamics in Geophysics, Jacques Dubois presents a new approach to the study of complex, time-dependent natural systems, which are of considerable importance for understanding the solid Earth. He discusses the results of more than ten years’ of studies into the applications of non-linear dynamics theory to a wide range of geophysical systems in areas such as geomorphology, vulcanology, seismology, geomagnetism and natural hazard assessment. The book is divided into four parts, and represents the state-of-the-art in this discipline. The first part is devoted to general theoretical notions and tools: measures, dimensions, fractal sets, dynamic systems, limit cycles and attractors, multi-fractals and wavelet transforms. It is here that the notion of chaos is introduced, and where paths to chaos and chaos control are discussed. Part two describes the applications of these powerful techniques to geophysics: geomorphology, fragmentation, tectonics, seismicity, volcanic eruptions, seismic forecasting algorithms, and geomagnetism. The third part aims at a synthesis and a list of the perspectives offered by this approach. The book concludes with a few traditional illustrations of non-linear dynamics and several theoretical appendices. Readership: Final year undergraduate and postgraduate students of geology, geophysics and the Earth sciences, and scientists studying in these and related areas such as tectonics, seismology and geomagnetism. Industrial experts working on natural hazard and risk assessment, namely fracturing of rocks, earthquakes and volcanic eruptions and self-organised criticality applied to natural catastrophes. Mathematicians and mathematical physicists interested in applications of non-linear dynamics theory.

Geophysical fluid dynamics illustrates the rich interplay between mathematical analysis, nonlinear dynamics, statistical theories, qualitative models and numerical simulations. This self-contained introduction will suit a multi-disciplinary audience ranging from beginning graduate students to senior researchers. It is the first book following this approach and contains many recent ideas and results.

This work comprises the proceedings of a conference held last year in Rhodes, Greece, to assess developments during the last 20 years in the field of nonlinear dynamics in geosciences. The volume has its own authority as part of the Aegean Conferences cycle, but it also brings together the most up-to-date research from the atmospheric sciences, hydrology, geology, and other areas of geosciences, and discusses the advances made and the future directions of nonlinear dynamics.

How nonlinear dynamics and statistical mechanics can be applied to geophysical fluid dynamics.

The general area of geophysical fluid mechanics is truly interdisciplinary. Now ideas from statistical physics are being applied in novel ways to inhomogeneous complex systems such as atmospheres and oceans. In this book, the basic ideas of geophysics, probability theory, information theory, nonlinear dynamics and equilibrium statistical mechanics are introduced and applied to large time-selective decay, the effect of large scale forcing, nonlinear stability, fluid flow on a sphere and Jupiter's Great Red Spot. The book is the first to adopt this approach and it contains many recent ideas and results. Its audience ranges from graduate students and researchers in both applied mathematics and the geophysical sciences. It illustrates the richness of the interplay of mathematical analysis, qualitative models and numerical simulations which combine in the emerging area of computational science.

It is now widely recognized that the climate system is governed by nonlinear, multi-scale processes, whereby memory effects and stochastic forcing by fast processes, such as weather and convective systems, can induce regime behavior. Motivated by present difficulties in understanding the climate system and to aid the improvement of numerical weather and climate models, this book gathers contributions from mathematics, physics and climate science to highlight the latest developments and current research questions in nonlinear and stochastic climate dynamics. Leading researchers discuss some of the most challenging and exciting areas of research in the mathematical geosciences, such as the theory of tipping points and of extreme events including spatial extremes, climate networks, data assimilation and dynamical systems. This book provides graduate students and researchers with a broad overview of the physical climate system and introduces powerful data analysis and modeling methods for climate scientists and applied mathematicians.

This book introduces stochastic dynamical systems theory in order to synthesize our current knowledge of climate variability. Nonlinear processes, such as advection, radiation and turbulent mixing, play a central role in climate variability. These processes can give rise to transition phenomena, associated with tipping or bifurcation points, once external conditions are changed. The theory of dynamical systems provides a systematic way to study these transition phenomena. Its stochastic extension also forms the basis of modern (nonlinear) data analysis techniques, predictability studies and data assimilation methods. Early chapters apply the stochastic dynamical systems framework to a hierarchy of climate models to synthesize current knowledge of climate variability. Later chapters analyse phenomena such as the North Atlantic Oscillation, El Niño/Southern Oscillation, Atlantic Multidecadal Variability, Dansgaard–Oeschger events, Pleistocene ice ages and climate predictability. This book will prove invaluable for graduate students and researchers in climate dynamics, physical oceanography, meteorology and paleoclimatology.