Uncertainty, Random Dynamical Systems, Climate Trends and Stochastic Modeling in Geophysics (co-organized)
Convener: I. Pavlyukevich  | Co-Conveners: D. Schertzer , J. Duan , Penland , X. Wang 
Oral Programme
 / Wed, 22 Apr, 17:30–19:00  / Room 27
Poster Programme
 / Attendance Thu, 23 Apr, 10:30–12:00  / Halls X/Y
Understanding and modelling of geophysical phenomena is a still unsolved challenging task. Methods of nonlinear dynamics constitute the core of modern Geophysics and prove to be the most effective tool for making quantitative and qualitative predictions.

In recent decades, deterministic geophysical models have been improved to incorporate uncertainty and randomness. For example, models of complex multi-scale climate systems include fast weather components in form of small random noise. The treatment of such random models require expertise in non-linear stochastic dynamics, statistics and time series analysis. One of the central questions in this field is the proper choice of the art of random input (e.g. Gaussian or non-Gaussian, red or white etc).

Another approach to stochastic modelling of geosystems is based on the study of statistical (scale) symmetries of the generating equations and is focused on the study of multifractals.

This session will be devoted to the latest studies of the geophysical phenomena with methods of nonlinear random dynamical systems.