气象学报（英文版）2026，Vol.40Issue(1)：254-272,19.DOI:10.1007/s13351-026-5109-6
Improving S2S Precipitation Forecast over China via a Deep Learning Model with Multi-Sphere Causality-Linked Predictors
Improving S2S Precipitation Forecast over China via a Deep Learning Model with Multi-Sphere Causality-Linked Predictors
摘要
关键词
precipitation/subseasonal-to-seasonal(S2S)/bias correction/causal discovery/artificial intelligenceKey words
precipitation/subseasonal-to-seasonal(S2S)/bias correction/causal discovery/artificial intelligence引用本文复制引用
穆斌,郭好,袁时金,陈宇轩,崔悦涵,黄岩军..Improving S2S Precipitation Forecast over China via a Deep Learning Model with Multi-Sphere Causality-Linked Predictors[J].气象学报（英文版）,2026,40(1):254-272,19.基金项目
Supported by the Meteorological Joint Funds of National Natural Science Foundation of China(U2542211 and U2542212),Original Exploration Project of National Natural Science Foundation of China(42450163),and National Natural Science Foundation of China(42405147). （U2542211 and U2542212）
