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Machine Learning our Way to More Accurate Weather Forecasts and More Interactive Climate Projections

Mike Pritchard, University of California, Irvine & NVIDIA Corporation

Contributions from industry over the past year have seen fully data driven methods for weather prediction dramatically increase in accuracy and ambition, rivaling and in some cases outperforming deterministic state of the art. I will review NVIDIA’s own contributions in this regard, including the challenges associated with making predictions that extend beyond weather to the climate timescale, in the context of “Earth-2” – a digital twin envisioned for climate impacts planning, and associated research at the interface of hybrid physics/machine learning methods for atmospheric simulation.