1、9895.2112.21127a High Spatial and Temporal ResolutionJ.Chinese Journal of AtmosphericSciences(in Chinese),47(3):698-712.doi:10.3878/j.issn.1006-Shenming,SUN Jianhua,et al.2023.Three-Dimensional Objective Identification of the Tibetan Plateau Vortex Based on a Reanalysis Wind Field withTANGHuan,FU汤欢，
2、傅慎明，孙建华，等.2 0 2 3.基于高分辨率再分析风场的高原涡三维识别技术及应用 J.大气科学,47(3):698-712.May20232023年5月ChinesciencesVol.47 No.3第47 卷第3期科学基于高分辨率再分析风场的高原涡三维识别技术及应用汤欢1傅慎明3孙建华周象贤41中国科学院大气物理研究所云降水物理与强风暴重点实验室，北京10 0 0 2 92中国科学院大学，北京10 0 0 493中国科学院大气物理研究所国际气候与环境中心，北京10 0 0 2 94国网浙江省电力科学研究院，杭州310 0 14摘要高原涡（TPV）是生成于青藏高原主体的一类浅薄中尺度涡旋系
3、统，其发生频繁、影响范围广、造成灾害强，是我国最重要的致灾中尺度系统之一。全面揭示高原涡的统计特征是本领域研究的重要基础。其中，高原涡的精准识别是认识其统计特征的关键。随着高时空分辨率再分析资料的出现，高原涡的研究有了更好的数据基础，然而，无论是人工识别方法还是基于较粗分辨率的客观识别算法都难以高效地适用于当前的新再分析资料。因此，函需发展一种高精度的、适用于高时空分辨率再分析资料的高原涡客观识别方法。本文提出了一种适用于高分辨率再分析资料、基于风场的限制涡度高原涡客观识别算法（Restricted-vorticitybasedTibetan-Plateau-vortexIdentifying
4、Algorithm，简称RTIA)。该方法首先判断高原涡候选点，然后以候选点为中心，划分多个象限，通过象限平均风场限定条件和象限组逆时针旋转（北半球）条件确定高原涡中心，无需复杂计算及对各气压层分别设定阈值，即可快速实现高原涡的水平和垂直追踪。基于197 92 0 2 0 年共42 个暖季（59月）、1546 6 个高原涡（共计990 90 时次）大样本的评估表明，RTIA方法识别高原涡的平均命中率超过95%，平均空报率低于9%，平均漏报率少于5%，可以十分准确地对高原涡进行识别。此外，评估还表明RTIA方法应用于不同空间分辨率的再分析资料（如0.5或0.2 5）时，仍能保持高原涡识别的高准确
5、率，其识别结果主要受涡旋自身强度的影响，对弱涡旋的识别精度比强涡旋偏低。该方法对其他中尺度涡旋识别也具有一定的借鉴意义。关键词高原涡（TPV）涡旋识别中尺度涡旋定限制涡度RTIA方法文章编号10 0 6-98 95(2 0 2 3)0 3-0 6 98-15中图分类号P447文献标识码Adoi:10.3878/j.issn.1006-9895.2112.21127Three-Dimensional Objective Identification of the Tibetan Plateau VortexBased on a Reanalysis Wind Field with a High
6、Spatial andTemporal ResolutionTANG Huan,FU Shenming,SUN Jianhua,and ZHOU Xiangxiant收稿日期2021-07-19；网络预出版日期月2 0 2 2-0 1-0 5作者简介汤欢，女，1995年出生，博士研究生，主要从事中尺度气象学研究。E-mail:通讯作者傅慎明，E-mail:资助项目国网浙江省电力公司科技项目52 11DS19001W，国家自然科学基金项目417 7 50 46、42 0 7 50 0 2，中国科学院青年创新促进会项目，国家重大科技基础设施项目“地球系统数值模拟装置”，高原与盆地暴雨旱涝灾害四川省
7、重点实验室开放研究基金项目Funded byy State Grid Zhejiang Electric Power Company Science and Technology Project(Grant 5211DS19001W),National Natural ScienceFoundation of China(Grants 41775046,42075002),Youth Innovation Promotion Association,Chinese Academy of Sciences,theNational Key Scientific,Technological Infr
8、astructure Project Earth System Science Numerical Simulator Facility,Heavy Rain andDrought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province699No.3TANGHuanetal.cation of the Tibetan Plateau Vortex Based on a.汤欢等：基于高分辨率再分析风场的高原涡三维识别技术及应用3期1 Key Laboratory of Cloud-Precipitation
9、Physics and Severe Storms,Institute of Atmospheric Physics,Chinese Academy of Sciences,Bejing1000292Universityof ChineseAcademy of Sciences,Beijing1000493 International Center for Climate and Environment Sciences,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 1000294 State Grid
10、 Zhejiang Electric Power Research Institute,Hangzhou 310014AbstractThe Tibetan Plateau vortex(TPV)is a shallow mesoscale vortex system in the Tibetan Plateaus main body.Itoccurs regularly,affects a wide area,and causes strong disasters.It is a major disaster-causing mesoscale system in China.To full
11、y show the statistical characteristics of TPVs,a crucial basis for TPV research must be established.The accurateidentification of TPVs is the key to the statistical characteristics of TPVs.TPV research has a better data basis with theemergence of reanalysis data with a high spatial and temporal reso
12、lution.However,neither an artificial identificationapproach nor an objective identification algorithm based on a coarser resolution can be effectively used for the currentnew reanalysis data.In this study,a restricted vorticity-based TPV identifying algorithm is proposed,which is suitable forhigh-re
13、solution reanalysis data.This approach first determines the TPV candidate points,divides several octants with thecandidate points as the center,and determines the center of the TPV by restricting the conditions of the average wind fieldin the octant and counterclockwise rotation(Northern Hemisphere)
14、conditions of the octant group.This method canquickly identify the horizontal and vertical tracing of vortexes without complicated calculations and different thresholdsfor each pressure layer.A large sample evaluation of 15,466 TPVs(99,090 hours in total)in 42 warm seasons(May-September)from 1979 to
15、 2020 shows that the average hit ratio of RTIA exceeds 95%,the average false alarm ratiois below 9%,and the average missing report rate is below 5%.Thus,the RTIA can correctly identify the centers of TPVs.Furthermore,the test results show that the high accuracy of TPV identification can still be mai
16、ntained when RTIA isapplied to the reanalysis data with different spatial resolutions(e.g.,0.5or 0.25).The identification results are primarilyaffected by the strength of the vortexes themselves,and the identification accuracy of weak vortexes is lower than that ofstrong vortexes.This approach can be used as a reference for identifying other mesoscale vortexes.Keywordss Tibetan Plateau vortex(TPV),Objective vortex identification,Mesoscale vortex,Restricted vorticity,RTIAmethod1引言青藏高原（简称高原）是中国最大、
