Seasonal prediction skill of East Asian summer monsoon in CMIP5 models

Abstract

The East Asian summer monsoon (EASM) is an important part of the global climate system and plays a vital role in the Asian climate. Its seasonal predictability is a long-standing issue within the monsoon scientist community. In this study, we analyse the seasonal (the leading time is at least 6 months) prediction skill of the EASM rainfall and its associated general circulation in non-initialised and initialised simulations for the years 1979–2005, which are performed by six prediction systems (i.e. the BCC-CSM1-1, the CanCM4, the GFDL-CM2p1, the HadCM3, the MIROC5, and the MPI-ESM-LR) from the Coupled Model Intercomparison Project phase 5 (CMIP 5). We find that most prediction systems of simulated zonal wind over 850 and 200hPa are significantly improved in the initialised simulations compared to non-initialised simulations. Based on the knowledge that zonal wind indices can be used as potential predictors for the EASM, we select an EASM index based upon the zonal wind over 850hPa for further analysis. This assessment shows that the GFDL-CM2p1 and the MIROC5 added prediction skill in simulating the EASM index with initialisation, the BCC-CSM1-1, the CanCM4, and the MPI-ESM-LR changed the skill insignificantly, and the HadCM3 indicates a decreased skill score. The different responses to initialisation can be traced back to the ability of the models to capture the ENSO (El Niño–Southern Oscillation) and EASM coupled mode, particularly the Southern Oscillation–EASM coupled mode. As is known from observation studies, this mode links the oceanic circulation and the EASM rainfall. Overall, the GFDL-CM2p1 and the MIROC5 are capable of predicting the EASM on a seasonal timescale under the current initialisation strategy.