Improvement of Multimodel Ensemble Seasonal Prediction Skills over East Asian Summer Monsoon Region Using a Climate Filter Concept

Abstract

he authors propose the use of a ?climate filter? concept to enhance prediction skill of a multimodel ensemble (MME) suite for the East Asian summer monsoon (EASM) precipitation and temperature at 850 hPa. The method envisages grading models on the basis of the degree of reproducibility of the association of EASM variability with a few relevant climate drivers with the respective model hindcasts for the period 1981?2003. The analysis identifies the previous winter Niño-3.4 and spring North Atlantic Oscillation indices as the most suitable climate drivers in designing a climate filter for evaluating models that replicate the observed teleconnections to EASM well. The results show that the hindcast skills of a new MME with the better-performing models are significantly higher than those from the nonperforming models or from an all-inclusive operational MME.