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Deep learning has made rapid advances in weather forecasting: autoregressive models trained on atmospheric reanalyses now rival dynamical models across nowcasting, medium-range, and subseasonal-to-seasonal lead times, producing well-calibrated ensemble forecasts at reduced cost. We review these advances and consider th...
California and adjacent regions received record-breaking precipitation in the winters of 2016–2017 and 2022–2023, causing extraordinary damage and severe societal impacts. However, subseasonal to seasonal predictive skill for Californian winter precipitation has remained persistently low. Furthermore, these extreme hyd...
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