气象2017，Vol.43Issue(10)：1176-1185,10.DOI:10.7519/j.issn.1000-0526.2017.10.002
2016年1月寒潮天气过程极端性分析及集合预报检验
Extreme Analysis and Ensemble Prediction Verification on Cold Wave Process in January 2016
摘要
Abstract
Based on European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis datasets and extreme forecast index (EFI) of ensemble prediction system,this paper analyzes the anomalous atmospheric circulation and verifies the EFI's forecasts for extreme cold event that happened from 21 to 25 January 2016.It is found that an anomalous strong high-pressure ridge maintained in central Asia and the standardized anomaly of high-pressure ridge was more than 3 standard deviations and the cold vortex nearby Lake Baikal was continuously developed and enhanced.As the revising of the transverse trough,the cold vortex moved southward abnormally and extreme cold wave broke out in the East China.The verifica tion shows the EFI can predict minimum temperature signal 7 days in advance.With the lead time exten sion of EFI forecast,the corresponding maximum TS score decreases,and there are different EFI thresholds for different lead time forecasts.Researches also show that the critical threshold of minimum temperature EFI for 5％ percentile of the low temperature events (1-3 days) is-0.6 and for 4-7 days the criti cal threshold of minimum temperature EFI is-0.5.Besides,the critical threshold of minimum temperature EFI for 1％ percentile of the low temperature events is-0.7.Moreover,the different lead time per formance of minimum temperature EFI for 5％ percentile of the low temperature events in Jiangnan,Huanghuai,Jianghuai and Jianghan Regions is the best,followed by the performance for the events in Huabei,Huanan,Southwest and Northwest,and the performance in Northeast is poor relatively.关键词
寒潮/标准化异常度/集合预报/极端天气预报指数(EFI)/极端低温事件Key words
cold wave/standardized anomaly (SA)/ensemble prediction/extreme forecast index (EFI)/extreme cold event分类
天文与地球科学引用本文复制引用
陶亦为,代刊,董全..2016年1月寒潮天气过程极端性分析及集合预报检验[J].气象,2017,43(10):1176-1185,10.基金项目
公益性行业(气象)科研专项(GYHY201306002)、国家科技支撑计划项目(2015BAC03B01)和国家气象中心预报员专项(Y201601)共同资助 （气象）
