AbstractThe late spring rainfall may account for 15% of the annual total rainfall, which is crucial to early planting in southeastern China. A better understanding of the precipitation variations in the late spring and its predictability not only greatly increase our knowledge of related mechanisms, but it also benefits society and the economy. Four models participating in the North American Multi-Model Ensemble (NMME) were selected to study their abilities to forecast the late spring rainfall over southeastern China and the major sources of heavy rainfall from the perspective of the sea surface temperature (SST) field. We found that the models have better abilities to forecast the heavy rainfall over the middle and lower reaches of the Yangtze River region (MLYZR) with only a 1-month lead time, but they failed for a 3-month lead time since the occurrence of the heavy rainfall was inconsistent with the observations. The observations indicate that the warm SST anomalies in the tropical eastern Indian Ocean are vital to the simultaneously heavy rainfall in the MLYZR in May, but an El Niño event is not a necessary condition for determining the heavy rainfall over the MLYZR. The heavy rainfall over the MLYZR in May is always accompanied by warming of the northeastern Indian Ocean and of the northeastern South China Sea (NSCS) from April to May in the models and observations, respectively. In the models, El Niño events may promote the warming processes over the northeastern Indian Ocean, which leads to heavy rainfall in the MLYZR. However, in the real world, El Niño events are not the main reason for the warming of the NSCS, and further research on the causes of this warming is still needed.
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