Seasonal prediction of East Asian monsoon precipitation: skill sensitivity to various climate variabilities

Abstract

The sensitivity of the East Asian Monsoon (EAM) precipitation prediction skill to the variabilities of the tropical Indian and Pacific sea surface temperature (SST), the North Atlantic Oscillation (NAO), and the heating and snow cover over the Tibetan Plateau is evaluated in the framework of a linear Markov model. It is found that the tropical Indo-Pacific SST helps to improve the prediction of EAM precipitation over oceanic regions and some localized areas over land, while the Indian Ocean alone does not show significant impact on prediction. The remote effects of NAO improve the prediction in the middle and lower reaches of the Yangtze and Huaihe River valleys in boreal spring, fall and winter, and over oceanic areas in boreal summer and fall. The predictive skill of our model is not sensitive to the inclusion of the sensible heating and snow cover over the Tibetan Plateau, probably because their effects are implicitly present in the original EAM model.