Multi-Scale Physical Statistic Prediction Model for Rain Season Onset Date in Guangdong Province

In order to do better short-term climate prediction for the rain season onset date(RSOD) in Guangdong Province in each year,the multi-scale optimal subset regression prediction model for RSOD have already developed and tested through its multi-scale variation characteristics and relationship with the antecedent SST and 500 hPa height in different time scales using the wavelet transform,Lanczos filter,correlation analysis,optimal subset regression and cross-validation.The results show that the RSOD in Guangdong Provincehas significant early trend,and exhibits interdecadal variation with 17.1-year period and interannual variation with 6.2-year period(after detrending).There are twenty regions with significant correlation between RSOD and SST and 500 hPa heightfield in interannual and interdecadal time scales.The prediction models for interannual and interdecadal time scales are respectively constructed by optimal subset regression of RSOD in corresponding time scale with predictors defined by the mean of significant correlation region.The addition of interannual predictive value and interdecadal one is RSOD prediction.The model produces good regression effect.The percentage of hits of difference less than 5 days between regression and observation is 41.5%,and that less than 10 days is 60.4%.The result of cross-validation analysis shows that the correlation coefficient between prediction and observation of RSOD is 0.33,which has passed the confident level of 99%.The percentage of hits of predictive error less than 5 days is 26.7%,and that less than 10 days is 45%.So the predictive model of multi-scales optimal subset regression has good predictive ability for RSOD in Guangdong Province.