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Significant architectural differences in machine learning models only emerge during active sudden stratospheric warming events, revealing the crucial role of vertical coupling in accurate predictions.
AI weather models don't just parrot data; stable ones can generate unique, plausible year-long weather trajectories, but only if they properly handle high-frequency noise.
