Predictability of Winter Rainfall in South China as Demonstrated by the Coupled Models of ENSEMBLES

Winter rainfall over South China shows strong interannual variability, which accounts for about half of the total winter rainfall over South China. This study investigated the predictability of winter (December-January-February; DJF) rainfall over South China using the retrospective forecasts of five state-of-the-art coupled models included in the ENSEMBLES project for the period 1961-2006. It was found that the ENSEMBLES models predicted the interannual variation of rainfall over South China well, with the correlation coefficient between the observed/station-averaged rainfall and predicted/area-averaged rainfall being 0.46. In particular, above-normal South China rainfall was better predicted, and the correlation coefficient between the predicted and observed anomalies was 0.64 for these wetter winters. In addition, the models captured well the main features of SST and atmospheric circulation anomalies related to South China rainfall variation in the observation. It was further found that South China rainfall, when predicted according to predicted DJF Nio 3.4 index and the ENSO-South China rainfall relationship, shows a prediction skill almost as high as that directly predicted, indicating that ENSO is the source for the predictability of South China rainfall.