Geophysical Research Letters

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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