AGU Chapman Conference on Complexity and Extreme Events in Geosciences
National Geophysical Research Institute
15–19 February 2010
Extreme events in Earth and space sciences exhibit many features of complex systems in which many interdependent components lead to organized as well as irregular features. In complex systems the knowledge of the parts does not necessarily lead to the predictable behavior of the entire system. The coupling among the components is essentially nonlinear and this leads to a rich variety of dynamical behavior, geometrical patterns and statistical distributions.
Recent advances in nonlinear dynamical process and complexity have provided new approaches to a wide variety of problems, including the nature of extreme events and natural hazards. The main connection of extreme events to nonlinear dynamics arises from the recognition that they are not isolable phenomena but must be understood in terms of interactions among different components, within and without the specific system. Complexity science thus provides a natural framework for the understanding of sudden transitions and extreme events, based on dynamical systems theory and statistical approaches.
Nonlinear dynamics and complexity is a inter-disciplinary field of research covering all areas of geosciences, e. g., Earth, atmospheric, oceanic and space sciences. In each of these areas extreme events, most of them identified with natural hazards, are of key interest. The techniques and approaches used in many studies include nonlinear modeling and prediction, state space reconstruction, statistical self-similarity and its dynamical origins, stochastic cascade models, fractals and multifractals, network theory, self-organized criticality, etc. A common theme in these systems is long-range correlations and their role in the emergence of extreme events. Recently there has been important advances in the studies of extreme events from the viewpoint of nonlinear dynamics and complexity. An important component of extreme events research is large scale numerical simulations based on first principles as well as other approaches. The analyses of simulation and observational data are providing results leading to a new perspective on extreme events.
A. Surjalal Sharma, University of Maryland, College Park, Maryland, email@example.com
Vijay P. Dimri, National Geophysical Research Institute, Hyderabad, India, firstname.lastname@example.org
Armin Bunde, University of Giessen, Giessen, Germany, Armin.Bunde@theo.physik.uni-giessen.de
Daniel Baker, University of Colorado, Boulder, USA
Bhupen Goswami, Indian Institute of Tropical Meteorology, Pune, India
Michael Ghil, University of California, Los Angeles, USA
J.R. Kayal, Jadavpur University, Kolkata, India
Vipin Srivastava, University of Hyderabad, Hyderabad, India
Ian Main, University of Edinburgh, Edinburgh, UK
Bruce Malamud, Kings College, London, UK
Hernan Makse, City College, New York, USA
Peter Mueller, University of Hawaii, Hawaii, USA
Yosihiko Ogata, The Institute of Statistical Mathematics, Tokyo, Japan
John Rundle, University of California, Davis, USA
Daniel Schertzer, École Nationale des Ponts et Chausses, France
Abhijit Sen, Institute for Plasma Research, Gandhinagar, India
Lev Zelenyi, Institute for Space Research, Moscow, Russia
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