物理-經驗模式對臺灣梅雨季降雨年際變化預報的應用與改善

This study is a follow up study of Yim et al. (2015), who developed physical-empirical models (PEMs) to predict the GPCP (Global Precipitation Climatology Project)-estimated interannual variation of Meiyu season (May and June) rainfall amount in Taiwan. Analyses of this study focus on three scientific questions, as listed follows. (1) Is it possible to establish a useful PEM to predict the Central Weather Bureau’s station-estimated interannual variation of Meiyu season rainfall amount in Taiwan (denoted as CWB-TWRI), based on the prediction factors of 0-month lead PEM equation developed by Yim et al. (2015)? (2) Is it possible to improve the skill of PEM equation developed in the current study for predicting CWB-TWRI, through the adjustment of prediction factors? (3) Is the adjusted PEM equation in scientific question (2) has better skill than the CFSv2 (Climate Forecast System version 2) model for predicting CWB-TWRI? For scientific question (1), our analyses show that it is possible to establish a useful PEM equation for predicting CWB-TWRI, based on the prediction factors of 0-month lead PEM equation developed by Yim et al. (2015). For scientific question (2), our analyses show that through the adjustment of the prediction factor related to the “Atlantic sea surface temperature tendency”, the skill of PEM equation for predicting CWB-TWRI can be improved. For scientific question (3), our analyses show that the PEM equation developed in the current study has better skill than CFSv2 in predicting the CWB-TWRI. These findings provide a better understanding of the potential use and the further improvement of PEM in predicting CWB-TWRI.