Sri Lanka,a small island country located near the southernmost end of the Indian subcontinent,is controlled by the southwest monsoon(SWM)during May to September,when it suffers the most accumulated rainfall in a year.Compared with extensive studies on the intraseasonal oscillation(ISO)of the Indian monsoon,less attention has been paid to the ISO of the SWM over Sri Lanka.Based on observational data,this study reveals that the leading mode of SWM rainfall shows a significant variability on a 10-35-day time scale,and it accounts for 66％of the fractional variance.The development of the intraseasonal rainfall anomaly is associated with a westward propagating anomalous cyclonic circulation.Furthermore,the skill of current dynamic models in simulating the SWM on the subseasonal time scale was evaluated by using the ECMWF(European center for Medium-Range Weather Forecasts)reforecast data from S2S(the Subseasonal to Seasonal Prediction project).In general,the model is more skillful in predicting the monsoonal wind index than the monsoonal rainfall index,with the skill for the former being beyond 30 days and the latter about two weeks.The forecast skills exhibit prominent interannual differences for both indices.It is suggested that a correct simulation of the large-scale circulation response to tropical convection is crucial for the subseasonal prediction of monsoonal rainfall over Sri Lanka.
Key Laboratory of Meteorological Disaster,Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environmental Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD),Nanjing University of Information Science and Technology,Nanjing,China
Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and Technology,Qingdao,China
季节内振荡 斯里兰卡 西南季风 次季节预测
This work was jointly supported by the National Key Research and Development Program of ChinaNational Natural Science Foundation of China(NSFC)[grant number 41975108],and the NSFC-Shandong Joint Fund for Marine Scienc
国家科技期刊平台
NSTL
万方数据
维普
