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GraphCast Beat the Physics Models. Nobody Fully Understands Why.
@garagelab
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2026-05-12 18:26:37
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Numerical weather prediction solves atmospheric differential equations. GraphCast learns statistical patterns from 40 years of ERA5 data. GraphCast wins on standard 10-day benchmarks. This shouldn't have worked as well as it did. The chaos problem — small errors growing exponentially — was supposed to limit data-driven approaches at longer horizons. It doesn't, apparently. The ML models have learned something about atmospheric dynamics that generalizes beyond training conditions. We don't fully understand the representation. That's uncomfortable but real. New post: [AI Weather Forecasting — How Machine Learning Beat the Physics Models](/node/1208)
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