| 集合敏感性分析在北半球中纬度高影响天气中的应用 |
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| 作者姓名： | 郑明华 杜钧 Brian A.Colle |
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| 作者单位： | 美国加利福尼亚大学圣地亚哥分校斯克里普斯海洋研究所,美国加利福尼亚 92093;美国国家海洋和大气管理局国家环境预报中心,美国马里兰 20740;美国纽约州立大学石溪分校海洋与大气科学学院,美国纽约 11794 |
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| 摘 要： | 总结回顾了集合敏感性分析(ESA)在诊断中纬度高影响天气预报不确定性中的应用。作为一个简单高效且不需要大量计算资源的方法,集合敏感性分析主要被应用在中纬度气旋、台风或飓风的温带转换,以及在强对流过程中诊断预报误差和不确定性的来源。集合敏感性方法极有灵活性,可以根据实际需要改变不同的预报变量和初始场。在对2010年美国东岸圣诞节暴风雪的分析中,集合敏感性分析通过三种形式来诊断了预报不确定性的初值敏感性,即基于EOF分析的敏感性、预报差别的敏感性,以及基于短期预报误差的向前积分敏感性回归。三种方法证实气旋路径的不确定性主要和位于美国南部大平原的短波槽初始误差相关。此外,气旋强度的不确定性还和产生于北太平洋向下游延伸的罗斯贝波列相关。集合敏感性分析方法对于分析中纬度气旋的不确定性、诊断初值敏感性、分析误差发展机制都非常有效。集合敏感性分析也被应用于分析台风/飓风的温带气旋转换过程的不确定性。在对2019年美国首个主要登陆台风Dorian的分析中发现,加拿大CMC的集合预报主要不确定性来自于强度的不确定性,而这个不确定性与初始时刻的大尺度环流型有关,较连贯的信号可以追溯至东北太平洋的前倾槽。而NCEP和ECMWF的不确定性主要在于气旋位置的东北—西南向移动,而敏感性主要和飓风系统本身(即其北部低压区和中纬度槽)的锁相有关。分析结果进一步验证了集合敏感性分析对诊断模式之间的不一致性,以及模式成员之间不一致性的不确定性来源和发展过程的可靠性。集合敏感性分析方法综合了集合预报、资料同化和敏感性分析,因此对于资料同化技术改进、诊断模式误差(或者缺陷)、附加(目标)观测最优策略,以及评估观测对预报的影响等都有重要意义。同时可以更有效地利用集合预报信息,帮助预报员提高情景意识,最终减少高影响天气预报中的决策失误。
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| 关 键 词： | 集合预报 高影响天气 集合敏感性分析 温带气旋 台风的温带气旋转换 |
Applications of Ensemble Sensitivity Analysis to High-Impact Weather Systems in the Middle Latitudes of Northern Hemisphere |
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| Institution: | (Scripps Institution of Oceanography,University of California at San Diego,CA 92093;National Centers for Environmental Prediction,NOAA,MD 20740;School of Marine and Atmospheric Sciences,State University of New York at Stony Brook,NY 11794) |
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| Abstract: | In this article,we provide a short review on the applications of ensemble sensitivity analysis(ESA)to high-impact weather events in mid-latitude of Northern Hemisphere.As an efficient and computationally inexpensive method,ESA has been applied to diagnose the forecast uncertainties in the extratropical cyclones,typhoons/hurricanes and their extratropical transitions,convective processes,etc.This method is very flexible:one can adjust its forecast metrics and/or state vectors based on the practical needs.ESA was applied in three different ways to diagnose the uncertainty in predicting a high-impact winter storm in December 2010 based on the choice of forecast metrics:sensitivity using the EOF approach,sensitivity using run cycle difference,and forward sensitivity regression using short-range forecast errors.All these three approaches confirmed that the track’s uncertainty for this cyclone was linked to the initial uncertainty in the short-wave trough over the southern Great Plains based on the 50-member ECMWF ensemble.Moreover,the cyclone intensity uncertainty was associated with the trough and ridge systems embedded in a Rossby wave train over the Northeast Pacific and the central U.S.Therefore,the ESA method is very robust for midlatitude cyclones in analyzing their forecast uncertainty,determining initial-condition sensitive regions,and diagnosing the mechanism for the error growth.ESA has also been used to analyze the uncertainty in typhoons/hurricanes and their ET processes.Through the application to the first major landfall hurricane Dorian in 2019,Canadian CMC ensemble showed the largest uncertainty in the intensity forecast among three ensemble systems during the transition time and this uncertainty was associated with the onset large scale circulation.Coherent sensitivity signals can be traced back to the positively tilted trough over the Northeast Pacific.In contrast,the uncertainties in NCEP and ECMWF ensemble were associated with the along-track southwest(northeast)ward shifting.ESA approach found this track uncertainty was more attributed to the cyclone itself,particularly to the phasing between its northern part and its leading edge midlatitude trough.The applications to Dorian further emphasized the value of ESA in diagnosing model disagreement,member inconsistency,and the origin and development of these uncertainties for extremely high-impact weather events.To sum up,ESA combines ensemble forecasting,data assimilation,and forecast sensitivity.Therefore,it has great potential in improving data assimilation,diagnosing model deficiency,and evaluating observational impact.On the other hand,it can efficiently utilize ensemble information,help forecasters to enhance situational awareness,and contribute to benefit the decision makers. |
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| Keywords: | ensemble forecasting high-impact weather event ensemble sensitivity analysis extratropical cyclone extratropical transition |
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