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This paper proposes TSSM, a triaxial state space model for global station weather forecasting that incorporates historical data aligned by period to improve long-horizon and extreme event prediction. It achieves state-of-the-art performance on the large-scale Weather-5K dataset and demonstrates strong robustness under missing observations.
Researchers developed an AI-boosted rare-event sampling framework that combines AI with physical climate modeling to more accurately predict the frequency of extreme weather events such as heatwaves.
A climate scientist describes Europe's recurring heat waves as a 'sad inevitability' due to human-induced global warming, with experts warning that extreme heat events will keep intensifying until net-zero emissions are reached.