Sources of Subseasonal Prediction Skill for Heatwaves over the Yangtze River Basin Revealed from Three S2S Models  

作　　者：Jiehong XIE Jinhua YU Haishan CHEN Pang-Chi HSU 

机构地区：[1]Key Laboratory of Meteorological Disaster of Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science&Technology,Nanjing 210044,China

出　　处：《Advances in Atmospheric Sciences》2020年第12期1435-1450,共16页大气科学进展（英文版）

基　　金：The authors would like to thank the anonymous reviewers for their comments,which helped improve the manuscript.This study was supported by the National Key R&D Program of China(Grant Nos.2018YFC1505804 and 2018YFC1507704);NSFC(Grant No.41625019).We appreciate the operational centers for providing their model outputs through the S2S database.

摘　　要：Based on the reforecast data(1999–2010)of three operational models[the China Meteorological Administration(CMA),the National Centers for Environmental Prediction of the U.S.(NCEP)and the European Centre for Medium-Range Weather Forecasts(ECMWF)]that participated in the Subseasonal to Seasonal Prediction(S2S)project,we identified the major sources of subseasonal prediction skill for heatwaves over the Yangtze River basin(YRB).The three models show limited prediction skills in terms of the fraction of correct predictions for heatwave days in summer;the Heidke Skill Score drops quickly after a 5-day forecast lead and falls down close to zero beyond the lead time of 15 days.The superior skill of the ECMWF model in predicting the intensity and duration of the YRB heatwave is attributable to its fidelity in capturing the phase evolution and amplitude of high-pressure anomalies associated with the intraseasonal oscillation and the dryness of soil moisture induced by less precipitation via the land–atmosphere coupling.The effects of 10–30-day and 30–90-day circulation prediction skills on heatwave predictions are comparable at shorter forecast leads(10 days),while the biases in 30–90-day circulation amplitude prediction show close connection with the degradation of heatwave prediction skill at longer forecast leads(>15–20 days).The biases of intraseasonal circulation anomalies further affect precipitation anomalies and thus land conditions,causing difficulty in capturing extremely hot days and their persistence in the S2S models.

关 键 词：subseasonal prediction HEATWAVE Yangtze River Basin subseasonal-to-seasonal models 

分 类 号：P456[天文地球—大气科学及气象学]