Neural general circulation models for weather and climate - Nature
Briefly

Recent advances in machine learning offer efficient weather predictions using historical data, outperforming GCMs in terms of computational cost and deterministic forecasting for short-term weather events.
Machine learning atmospheric models, like GraphCast, require significantly less code compared to traditional models like FV3, showing a promising path for future weather prediction technologies.
Read at Nature
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