Organizations: Department of Earth System Science, Tsinghua University, Beijing 100084, China · Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing 101408, China · College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China · State Key Laboratory of Climate System Prediction and Risk Management, National Climate Centre, China Meteorological Administration, Beijing 100081, China · China Meteorological Administration Key Laboratory for Climate Prediction Studies, National Climate Centre, China Meteorological Administration, Beijing 100081, China · Microsoft, Beijing 100080, China
Seasonal precipitation anomalies are largely regulated by atmospheric circulation, which dynamical models predict with greater reliability than precipitation itself. Here, we employ a deep learning model that translates dynamical circulation predictions into precipitation estimates. Predictions initialized from March to May consistently indicate a dry anomaly over central China in summer 2026. Retrospective evaluations revealed higher predictive skill in the analogue years, which also tended to feature central equatorial Pacific warming persisting from the preceding winter into summer. This warming favors an anomalous cyclonic circulation over the western North Pacific-South China Sea-South China region, which induces northerly winds and moisture divergence that jointly suppress rainfall over central China. Supporting this mechanism, layer-wise relevance propagation (LRP) independently identifies these northerly winds as the dominant driver of the prediction among all model inputs. Perturbation tests supported this attribution: removing LRP-identified features effectively eliminates the dry anomaly. Our framework thus provides physically interpretable explanations for AI-derived regional climate projections, facilitating evidence-based assessment before observational data become available.
Center for Hydrometeorology and Remote Sensing (CHRS), The Henry Samueli School of Engineering, Department of Civil and Environmental Engineering, University of California, Irvine, USA · Center for Western Weather and Water Extremes (CW3E), Scripps Institution of Oceanography, University of California, San Diego, USA
X, The Moonshot Factory, Google LLC, Mountain View, CA, USA · Google, Google LLC, Mountain View, CA, USA · Environmental Science and Engineering, California Institute of Technology, Pasadena, CA, USA +1