Accelerating climate models

Physical constraints are key ingredients for different components of climate models, including cloud parametrization, convection schemes, aerosols, dynamic vegetation changes, among many other components of GCMs. Traditional solutions to representation of these processes in GCMs are computationally expensive, and sometimes need to be approximated (i.e., parametrized). ML can help with emulating some of these sub-grid processes, such as vegetation changes , and clouds parametrization and convection.

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