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Complexity in Geosciences: from chaotic-stochastic dynamics to ecology and sustainability
Convener: Christian Franzke  | Co-Conveners: Daniel Schertzer , Petra Friederichs , Paul Williams , Balasubramanya Nadiga , Ioulia Tchiguirinskaia , K. Fraedrich , Andràs Bàrdossy , Witold Krajewski , Anastasios Tsonis 
 / Fri, 28 Apr, 15:30–19:00  / Room M2
 / Attendance Fri, 28 Apr, 13:30–15:00  / Hall X4
There are presently a number of pressing socio-economical issues - sustainable development, ecological transition, and resilience to extreme weather, water and climate change, to quote a few- that cannot be addressed in reliable manner with the help of classical approaches, e.g. quasi-linear or scale truncated models, quasi-Gaussian statistics. Indeed, myriads of physical processes occur over a wide range of spatial and temporal scales in geophysical systems and give rise to complex multi-scale behavior like atmospheric and oceanic low-frequency variability.

There is indeed huge gaps between the often used ad hoc indicators and the recent developments in nonlinear geophysics and complex systems, including random dynamical systems, complex networks, multifractals, copulas, etc. Given the unpredictability of the unresolved, small-scale components for observed values of the large-scale ones, stochastic approaches can provide more realistic representations of the multi-scale variability and allow transitions between chaotic attractors, as well as interactions among the scales (e.g., between climate and weather).

We invite contributions spanning fundamental studies of chaotic and stochastic approaches, nonlinear and stochastic modeling of geophysical systems, uncertainty quantification, stochastic parameterizations, data assimilation using nonlinear and stochastic methods, and extreme-value studies using a nonlinear and stochastic framework. This session also intends to be a forum for paradigm shifts, to pinpoint success stories as well as dead ends, and to draw a road map from nonlinear geophysics to complex environment for reliable decision making.