Predicting Western Pacific Subtropical High Using a Combined Tropical Indian Ocean Sea Surface Temperature Forecast  

作　　者：WANG Li-Wei ZHENG Fei ZHU Jiang 

机构地区：[1]International Center for Climate and Environment Science (ICCES), Institute of Atmospheric Physics, Chinese Academy of Sci-ences [2]Graduate University of Chinese Academy of Sciences [3]Beijing Institute of Applied Meteorology

出　　处：《Atmospheric and Oceanic Science Letters》2013年第6期405-409,共5页大气和海洋科学快报（英文版）

基　　金：supported by the National Basic Research Program of China(Grant No.2012CB417404);the National Natural Science Foundation of China(Grant Nos.41075064 and41176014)

摘　　要：Weather and climate in East China are closely related to the variability of the western Pacific subtropical high(WPSH), which is an important part of the Asian monsoon system. The WPSH prediction in spring and summer is a critical component of rainfall forecasting during the summer flood season in China. Although many attempts have been made to predict WPSH variability, its predictability remains limited in practice due to the complexity of the WPSH evolution. Many studies have indicated that the sea surface temperature(SST) over the tropical Indian Ocean has a significant effect on WPSH variability. In this paper, a statistical model is developed to forecast the monthly variation in the WPSH during the spring and summer seasons on the basis of its relationship with SST over the tropical Indian Ocean. The forecasted SST over the tropical Indian Ocean is the predictor in this model, which differs significantly from other WPSH prediction methods. A 26-year independent hindcast experiment from 1983 to 2008 is conducted and validated in which the WPSH prediction driven by the combined forecasted SST is compared with that driven by the persisted SST. Results indicate that the skill score of the WPSH prediction driven by the combined forecasted SST is substantial.Weather and climate in East China are closely related to the variability of the western Pacific subtropical high（WPSH）, which is an important part of the Asian monsoon system. The WPSH prediction in spring and summer is a critical component of rainfall forecasting during the summer flood season in China. Although many attempts have been made to predict WPSH variability, its predictability remains limited in practice due to the complexity of the WPSH evolution. Many studies have indicated that the sea surface temperature（SST） over the tropical Indian Ocean has a significant effect on WPSH variability. In this paper, a statistical model is developed to forecast the monthly variation in the WPSH during the spring and summer seasons on the basis of its relationship with SST over the tropical Indian Ocean. The forecasted SST over the tropical Indian Ocean is the predictor in this model, which differs significantly from other WPSH prediction methods. A 26-year independent hindcast experiment from 1983 to 2008 is conducted and validated in which the WPSH prediction driven by the combined forecasted SST is compared with that driven by the persisted SST. Results indicate that the skill score of the WPSH prediction driven by the combined forecasted SST is substantial.

关 键 词：western Pacific subtropical high SST tropical Indian Ocean statistical prediction 

分 类 号：P732.6[天文地球—海洋科学]