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Advancing Subseasonal Forecasting with Machine Learning

Guan, Hannah et al.
arXiv (All) · Papers
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Decision-makers rely on weather forecasts to plant crops, manage wildfires, allocate water and energy, and prepare for weather extremes. Today, such forecasts enjoy unprecedented accuracy out to two weeks thanks to steady advances in physics-based dynamical models and data-driven artificial intellig
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