Improve the Prediction of Summer Precipitation in South China by a New Approach with the Tibetan Plateau Snow and the Applicable Experiment in 2014

Sever floods occurred in southern China and droughts were prevalent in northern China in the summer of 2014. Most predicted models in China missed the southern rain band in their flood season predictions conducted in March 2014, which led to relatively low prediction accuracy. Based on the higher prediction skill for summer sea level pressure of climate models and the significant relationship between the preceding winter Tibetan Plateau Snow and summer precipitation in the south, a new Hybrid Statistical Downscaling Prediction (abbreviated as HSDP) method for summer precipitation anomaly prediction in China was proposed in this paper. The method can integrate the information of the highly predictable circulation from climate models and the influential signal of Tibet Plateau Snow in the preceding winter to improve the dynamical-statistical combination prediction for summer precipitation in the south. Using this method, a statistical downscaling model was established based on the climate prediction model of National Climate Center of China. The cross validation of seasonal prediction for the summer precipitation in the south was performed and the results showed that the HSDP improved the multi-year average of anomaly correlation coefficient from-0.006 to 0.24, and it had a higher predicting skill than the original climate model in most years. Using HSDP, the precipitation prediction for the summer of 2014 could well capture the basic situations, i.e. floods in southern China and droughts in northern China, and the positive precipitation anomaly in the south. The anomaly correlation coefficient could reach 0.43. This result indicated that the HSDP has a great operational application prospect with regard to summer precipitation prediction in China.