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投稿时间:2017-04-04 修订日期:2017-07-13
投稿时间:2017-04-04 修订日期:2017-07-13
中文摘要: 利用欧洲中期天气预报中心(ECMWF)再分析资料和集合预报极端天气预报指数(extreme forecast index,EFI),对2016年1月21—25日强寒潮天气环流异常性和EFI对极端低温事件的预报进行了分析和检验。中亚地区一直维持标准化异常度在3个标准差以上的高压脊,冷涡系统不断发展增强,随着横槽转竖,冷空气爆发南下使得我国中东部出现极端低温。最低温度EFI可以提前7 d预报出低温信号,随着EFI预报时效的延长所对应的最大TS评分随之降低,对不同时效预报需选取合适的EFI阈值。对5%百分位的低温事件短期时效(1~3 d)最低温度EFI临界阈值为-0.6,中期时效(4~7 d)临界阈值为-0.5;对1%百分位的低温事件临界阈值则为-0.7。5%百分位的低温事件各时效最低温度EFI在江南、黄淮、江淮、江汉等地表现最好,华北、华南、西南、西北地区表现次之,在东北地区表现相对较差。
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 verification shows the EFI can predict minimum temperature signal 7 days in advance. With the lead time extension 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 critical 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 performance 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.
文章编号: 中图分类号:P458 文献标志码:
基金项目:气象关键技术集成与应用项目(CMAGJ2015Z06)、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
Author Name | Affiliation |
TAO Yiwei | National Meteorological Centre, Beijing 100081 |
DAI Kan | National Meteorological Centre, Beijing 100081 |
DONG Quan | National Meteorological Centre, Beijing 100081 |
引用文本:
陶亦为,代刊,董全,2017.2016年1月寒潮天气过程极端性分析及集合预报检验[J].气象,43(10):1176-1185.
TAO Yiwei,DAI Kan,DONG Quan,2017.Extreme Analysis and Ensemble Prediction Verification on Cold Wave Process in January 2016[J].Meteor Mon,43(10):1176-1185.
陶亦为,代刊,董全,2017.2016年1月寒潮天气过程极端性分析及集合预报检验[J].气象,43(10):1176-1185.
TAO Yiwei,DAI Kan,DONG Quan,2017.Extreme Analysis and Ensemble Prediction Verification on Cold Wave Process in January 2016[J].Meteor Mon,43(10):1176-1185.