Geophysical Research Letters
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Key Points

  • The Subseasonal-to-Seasonal prediction of summer precipitation over southern China is improved with a U-Net based deep learning method

  • The U-Net demonstrated promising performance in both general statistics and extreme events and shows superiority to the quantile mapping benchmark

  • The model skills arise from precipitation itself at the early stage, while atmospheric factors play important roles at longer lead times

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New US Academic Alliance for the IPCC opens critical nomination access

  AGU contact: Josh Weinberg, [email protected]   WASHINGTON — The American Geophysical Union and the U.S. Academic Alliance for the IPCC today open calls for U.S. researchers...

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Unusual Drainages of the Americas

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While most rivers and lakes follow predictable principles of hydrology and geology, a few seem to defy the rules. Some rivers diverge rather than converge; some rivers flow...

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