Studies of the seasonal prediction of heavy late spring rainfall over southeastern China

Shouwen Zhang,Wentao Ma,Hui Wang,Hua Jiang

doi:10.1007/s00382-021-05786-w

Abstract

The 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.

Highlights

The precipitation over China exhibits prominent variability on both interannual and decadal time scales (Kosaka et al 2011; Li et al 2004)
The statistics of the observation data show that the precipitation in May can account for 15% of the annual precipitation in southeastern China, with two centers of precipitation
It should be noted that when heavy May rainfall occurred over the MLYZR, the tropical eastern Indian Ocean always contained significant warm sea surface temperature anomalies (SSTA), while only scattered areas in the central Pacific contained warm SSTAs

Summary

Introduction

The precipitation over China exhibits prominent variability on both interannual and decadal time scales (Kosaka et al 2011; Li et al 2004). Based on the above results, while the fact that the El Niño teleconnection causes warming of the tropical Indian Ocean and results in an abnormally large summer rainfall in the MLYZR is conclusive, whether the mechanisms are the same in late spring and the performances of the climate models are still unclear. In spring, a season when climate models generally exhibit a spring predictability barrier associated with ENSO (Torrence and Webster 1998), outstanding questions remain concerning the predictability in the late spring, the seasonal prediction of the anomalous robust rainfall over southeastern China, and its controlling mechanisms.

Hindcast data

Observations and reanalysis data

Ability to forecast the late spring rainfall in China

Major sources of heavy rainfall

Findings

Summary and discussion