本文已被:浏览 499次 下载 1323次
投稿时间:2021-03-31 修订日期:2022-02-07
投稿时间:2021-03-31 修订日期:2022-02-07
中文摘要: 全球业务数值模式存在偶发的中期预报时效误差极端大的问题,对其溯源可为模式和同化系统改进提供重要参考。分析2020年1—2月中国气象局高分辨率全球同化预报系统(CMA-GFS)和较低分辨率全球集合预报系统(CMA-GEPS)业务预报在中期时效(6 d)的预报误差,利用集合敏感性分析方法,对东亚地区具有极端中期预报误差的一个个例(2020年2月8日12 UTC起报)进行了预报误差溯源研究。由CMA-GFS预报误差的时空演变特征及基于CMA-GEPS系统的集合敏感性分析结果得到了一个关于预报误差关键源区的初步推断,即为位于东亚上游地区的大西洋及欧洲西部地区(20°~90°N、90°W~60°E)。进而,将CMA-GEPS系统控制预报位于上述误差关键源区的初值替换为最优集合成员初值后,预报结果显示东亚地区500 hPa位势高度中期预报误差显著减小,不到原预报误差的50%,这进一步验证了识别出的关键误差源区的有效性。
中文关键词: 中期预报,误差溯源,集合预报,集合敏感性
Abstract:Global operational numerical models have the problem of occasional occurrences of extreme large medium-range forecast errors, and tracing these error sources could provide important references for improving the model itself and data assimilation system. In this study, errors of the operational forecasts in medium range (6 days) from the China Meteorological Administration high-resolution global assimilation and forecast system (CMA-GFS) and global ensemble prediction system (CMA-GEPS) with a lower resolution are analyzed during the period spanning from January to February 2020. The error origin for a particular case (initialized on 12 UTC 8 February 2020) with extreme large medium-range forecast errors over East Asia is investigated by employing the method of ensemble sensitivity analysis. From the spatial-temporal evolution characteristics of forecast errors in CMA-GFS and results from ensemble sensitivity analysis based on CMA-GEPS, a preliminary deduction was acquired about the key forecast error source region, i.e., an up-stream region of East Asia located in the Atlantic Ocean and western Europe (20°-90°N, 90°W-60°E). When the initial conditions of the control forecast of CMA-GEPS are replaced with that of the best ensemble member but confined to the above-mentioned key error source region, the medium-range forecast error of 500 hPa potential height was reduced greatly over East Asia, less than 50% of the original control forecast error. This further confirms the effectiveness of the identified key error source region.
文章编号: 中图分类号: 文献标志码:
基金项目:国家自然科学基金项目(41905090、41875181)、国家重点研发计划(2017YFA0604502)共同资助
引用文本:
彭飞,李晓莉,赵滨,陈静,2022.CMA全球数值预报系统东亚地区中期大尺度预报误差溯源初步探究:个例分析[J].气象,48(6):665-676.
PENG Fei,LI Xiaoli,ZHAO Bin,CHEN Jing,2022.Preliminary Exploration on the Origin of Large-Scale Medium-Range Forecast Errors over East Asia in the CMA Global Numerical Prediction System: A Case Study[J].Meteor Mon,48(6):665-676.
彭飞,李晓莉,赵滨,陈静,2022.CMA全球数值预报系统东亚地区中期大尺度预报误差溯源初步探究:个例分析[J].气象,48(6):665-676.
PENG Fei,LI Xiaoli,ZHAO Bin,CHEN Jing,2022.Preliminary Exploration on the Origin of Large-Scale Medium-Range Forecast Errors over East Asia in the CMA Global Numerical Prediction System: A Case Study[J].Meteor Mon,48(6):665-676.