Prediction Experiment for the South China Sea Summer Monsoon Strength by Physical-statistic Integrated Model

The South China Sea summer monsoon(SCSSM) is a tropical system that plays a key role during the flood season of South China. However, the prediction of the SCSSM strength is difficult by no matter dynamic or statistic methods. Statistic methods are used in practice rather than dynamic model, but empirical-statistic models always have good hindcasting results during the period of building model, while the forecasting skills decrease evidently in practice. Physical-statistic methods have relatively stable predictive skill when the persistence of physical processes is taken into account. Therefore, an integrated technique is introduced based on associated physical processes to establish a predictive model for SCSSM. It is well known that the rainfall of SCSSM has multi-scale climate variability, for example, quasi-biennial and quasi-quadrennial time scale, which are mainly related to TBO(Tropospheric Biennial Oscillation) and ENSO(El Nino-Southern Oscillation), respectively. Based on the corresponding climatic f