Prediction skill of NCEP CFSv2 for seasonal precipitation and surface air temperature forecast over Southeast Asia

Abstract

Climate Forecast System version 2 (CFSv2) is the ocean-atmosphere-land coupled model and the latest version of seasonal climate forecast from National Centers for Environmental Prediction (NCEP). This study presents the prediction skill of seasonal precipitation and surface air temperature forecasting from CFSv2 over Southeast Asia. The objective of the study was to verify the prediction accuracy of CFSv2 by quantifying the deterministic quantities in term of correlation coefficients with respect to different lead times and target seasons based on a the 28-year ensemble means (1983/84 - 2010/11) for each variables. Additionally, the prediction skill of 20 sub-regions over Southeast Asia are verified with observation for regional assessment of the accuracy of seasonal precipitation and surface air temperature forecasted by CFSv2. In general, the result showed that the prediction skill of CFSv2 for seasonal precipitation and surface air temperature forecasting is reasonable, especially prediction skill after lead month-0 for all target seasons compared to other lead months. The lowest prediction skill is after lead month-6. Overall, the prediction skill of seasonal surface air temperature forecasting is better than precipitation. Moreover, the result obtained in this study highlights the advantages of using an ensemble technique for seasonal forecasting in Southeast Asia.