HR: 16:30h
AN: NG34A-03    [Abstracts]
TI: Predictability of extreme events in spatially distributed driven hierarchical systems
AU: Keilis-Borok, V
EM: vkb@ess.ucla.edu
AF: Institute of Geophysics and Planetary Physics, University of California, Los Angeles, CA 90095, United States
AU: Keilis-Borok, V
EM: vkb@ess.ucla.edu
AF: Department of Earth and Space Sciences, University of California, Los Angeles, CA 90095, United States
AU: Gabrielov, A
EM: agabriel@math.purdue.edu
AF: Departments of Mathematics and Earth and Atmospheric Sciences, Purdue University, West Lafayette, IN 47907, United States
AU: * Zaliapin, I
EM: zal@unr.edu
AF: Department of Mathematics and Statistics, University of Nevada, Reno, NV 89557, United States
AB: We propose a framework for studying predictability of extreme events in complex systems. Major conceptual elements --- hierarchical organization, spatial dynamics, and external driving --- are combined in a classical age- dependent multi-type branching diffusion process with immigration. A complete analytic description of the size- and space-dependent distributions of particles is derived. We then formulate an extreme event prediction problem and determine characteristic patterns of the system behavior as an extreme event approaches. In particular, our results imply specific premonitory deviations from self-similarity, which have been heuristically observed in real-world and modeled complex systems. Our results suggest a simple universal mechanism of such premonitory patterns and natural framework for their analytic study.
DE: 3238 Prediction (3245, 4263)
DE: 3265 Stochastic processes (3235, 4468, 4475, 7857)
DE: 4415 Cascades
DE: 4435 Emergent phenomena
DE: 4445 Nonlinear differential equations
SC: Nonlinear Geophysics [NG]
MN: 2007 Fall Meeting