While AI models are rapidly improving weather forecasting accuracy and efficiency, experts express concern about their reliability in predicting unprecedented "gray swan" events. These rare but plausible extremes, exacerbated by climate change, are poorly represented in AI training data, leading to potentially confident but incorrect forecasts. Although physics-based models can simulate such events, AI models struggle with extrapolation, risking silent failures and the atrophy of essential physical modeling infrastructure. AI
影响 AI models may provide faster, cheaper weather forecasts but risk silent failures on unprecedented climate events, necessitating continued reliance on physics-based models.
排序理由 Research paper discussing limitations of AI models in weather forecasting, specifically concerning 'gray swan' events.
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