Improvements of the Sub-Seasonal Precipitation Predicted by the BCC_S2S Forecast System Over Eastern China in Summer Using the Singular Value Decomposition Bias Correction Method

Abstract

A bias correction scheme has been developed based on the singular value decomposition (SVD) analysis in this study, and it is further validated and used to improve the skill of sub-seasonal precipitation over Eastern China in summer predicted by the Beijing Climate Center sub-seasonal to seasonal forecast system (BCC_S2SFS). Results show that the BCC_S2SFS prediction skill of summer precipitation over Eastern China at the sub-seasonal scale is up to 1 days in advance and exhibits clear regional and inter-annual differences. Further adopting the bias correction scheme can significantly improve the skill of BCC_S2SFS in predicting the sub-seasonal precipitation over Eastern China in summer with different lead time especially longer than 10 days. Compared to the original prediction of BCC_S2SFS, the temporal (spatial) correlation coefficient between the bias corrected predictions and observations over Eastern China can be increased by 0.15, 0.55, and 0.56 (0.14, 0.17, and 0.19) during the forecast lead time of 0–10, 11–20, and 21–30 days, respectively. The bias correction scheme developed in this study shows large potential application prospects in the operational forecast.