Critical challenges to Earth-system science include process understanding and probabilistic predictions of the atmosphere, ocean, cryosphere, and land at different timescales in the face of uncertainty. Noisy initial and boundary conditions, model imperfection, and chaos affect the predictability and understanding of the geophysical system. Stochastic methods address uncertainty at all levels of model complexity, from conceptual models to General Circulation and Earth-System models. While progress has been made in modeling stochastically many geophysical processes, we are far from having a complete understanding of the optimal strategies to deploy.

This session welcomes submissions related to stochastic processes in meteorology, oceanography, and climate science, including new modeling techniques, stochastic parameterization schemes, and data-driven stochastic modeling. It aims at bringing together studies involving chaos, turbulence, and stochasticity in the atmosphere-ocean-ice-land system from the mathematical, statistical, and geophysical communities. Numerical simulations, theories, and experiments that investigate stochastic parameterizations and associated predictability are especially relevant.

• A - Atmospheric Sciences

• AMS: American Meteorological Society -
• AOGS: Asia Oceania Geosciences Society -
• EGU: European Geosciences Union -
• WCRP: World Climate Research Programme -