CL5.7/NP8.1Stochasticity and Statistical Physics in Climate Dynamics (co-organized)
|Convener: Michael Ghil | Co-Convener: Valerio Lucarini|
Understanding more deeply climate dynamics is of fundamental importance in attempting to estimate future climate evolution over the next decades and centuries. This session invites contributions from scientists who try to understand the dynamics based on past and current observations - whether from instrumental, historical or proxy records - as well as on a full hierarchy of models. This understanding can be rooted in a theoretical and numerical framework that relies on dynamical system theory, both deterministic and stochastic. Contributions based on chaotic and/or stochastic models from the simplest ones ("toy models") that describe in depth a small number of fundamental mechanisms to more elaborate ones that include a greater variety of physical, chemical and biological processes, are encouraged; so are contributions that carry out a comparison between the properties of data sets and model simulations. Furthermore, the session invites contributions dealing with the application of tools borrowed from non-equilibrium statistical mechanics (response theory, attractors and Sinai-Ruelle-Bowen measures, fluctuation-dissipation relations) and non-equilibrium thermodynamics (analysis of entropy production, efficiency, irrevsersibility) to geophysical fluid models and climate models of various degrees of complexity. This session proposes to advance and communicate our knowledge on the use of concepts and tools from stochastic dynamics and statistical physics in climate modeling, by combining state-of-the art research in climate dynamics with modern mathematical theories.