Error analysis of dynamical seasonal predictions of summer precipitation over the East Asian-western Pacific region

In the East Asian-western Pacific ( EAWP) region, six climate prediction models which are currently used in APEC Climate Center ( APCC) Multi- Model Ensemble ( MME) prediction system show low skill in predicting summer precipitation. In order to diagnose the dominant error in the prediction, an error decomposition method is developed. Using this method, the total error is decomposed into three parts: errors due to conditional bias, unconditional bias and atmospheric internal processes ( AIP). The biaserror can be corrected while the AIP error cannot. It is found that the sum of both bias- errors is about 3 to 20 times larger than the AIP error over the EAWP region for these models. This suggests that the AIP error is not the main cause for the loss of predictability, therefore there is potential to improve the predictions by correcting the bias- errors.