A skillful prediction scheme for April precipitation over central East China

Abstract

Central East China (30°N–42°N, 105°E–122°E), around the lower and middle reaches of the Yangtze River valley to north China, is one of the main agricultural bases over East Asia. Spring precipitation can significantly influence the regional agricultural activity and production, such as the crop planting and winter wheat growing over the region. Here, we find that different from the March and May precipitation over central East China, the April precipitation there shows relatively weak relationships with the preceding El Niño-Southern Oscillation (ENSO) and Indian Ocean basin mode (IOB) which are usually used as the prediction signals. Therefore, in this study, from the perspective of the prediction, we identify two predictors in the preceding months for the variability in the April precipitation over central East China: (1) the sea surface temperature (SST) over the subtropical North Atlantic in January and (2) the snow cover around the region to the east of Lake Baikal in March. The anomalous SST signal shows a good persistence from January to April, and further stimulates a wave train propagating from the subtropical North Atlantic eastward to East Asia during April, which could contribute to an anomalous East Asian trough and thereby the precipitation anomalies over central East China. The anomalous snow cover signal in March also tends to persist to the following April, and the associated anomalous cooling/warming could exert an impact on the East Asian trough, consequently influencing the April precipitation over central East China. Based on the two predictors, we establish a statistical prediction scheme and further evaluate its predictive skills. The results suggest the potential of the scheme for the prediction of the April central East China precipitation.