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Solving the storm split-merge problem-A combined storm identification, tracking algorithm

文献类型：期刊论文

作者Zan, Beilei1,2; Yu, Ye1,3; Li, Jianglin1,3; Zhao, Guo1,3; Zhang, Tong1,3; Ge, Jun4,5,6
刊名ATMOSPHERIC RESEARCH
出版日期2019-04-01
卷号218页码:335-346
ISSN号0169-8095
关键词Storm identification Storm tracking Split-merge Algorithm evaluation
DOI10.1016/j.atmosres.2018.12.007
通讯作者Yu, Ye(yyu@lzb.ac.cn)
英文摘要Many storm identification and tracking algorithms based on radar data have been designed and widely used in weather forecasting. However, most of these algorithms have concentrated on storm cells. As a convective storm splits (merges), many storm cells will be generated (disappeared) within close proximity to each other resulting in errors in storm tracking and analysis of storm evolution. To resolve this, a new combined storm identification tracking algorithm (referred as CSIT) is devised after detailed testing of various existing convective storm identification and tracking methods. The connected neighborhoods labeling and a lower radar reflectivity threshold(30dBz) is used in CSIT, which ensures that newly formed storms can be detected. Moreover, with a lower reflectivity threshold, merger of convective cells is regarded as one convective storm, thus reducing the occurrence of storm split-merge. In terms of storm tracking, five tracking algorithms with different storm motion estimation, search radius calculation, and matching principles are designed and quantitatively evaluated using the contingency table approach and objective method. The best-performing algorithm that considers different situations of storm splitting and merging is selected to devise CSIT and the optimal thresholds for two parameters in the algorithm (i.e. maximum matching distance and search radius adjust factor) is determined through a series of sensitivity tests and objective evaluation using six years of warm season (JJA) radar data from 2012 to 2017. The devised storm identification and tracking algorithm has the potential to be applied to other data, such as cloud top brightness temperature from satellites, lightning frequency and other model output variables. The objective evaluation method does not rely on manual tracking results and thus can be used to improve and adapt automatic tracking algorithms for different situations (different storm types, regions etc).
收录类别SCI
WOS关键词RADAR CHARACTERISTICS ; CELL-TRACKING ; CLIMATOLOGY ; THUNDERSTORMS ; REFLECTIVITY ; SIMULATIONS ; CONVECTION ; FREQUENCY ; HAIL
WOS研究方向Meteorology & Atmospheric Sciences
WOS类目Meteorology & Atmospheric Sciences
语种英语
出版者ELSEVIER SCIENCE INC
WOS记录号WOS:000457814600027
URI标识http://www.irgrid.ac.cn/handle/1471x/2558166
专题寒区旱区环境与工程研究所
通讯作者Yu, Ye
作者单位1.Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Land Surface Proc & Climate Change Cold &, 320 Donggang West Rd, Lanzhou 730000, Gansu, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Pingliang Land Surface Proc & Severe Weather Res, Pingliang 744015, Gansu, Peoples R China
4.Nanjing Univ, Inst Climate & Global Change Res, Sch Atmospher Sci, Nanjing, Jiangsu, Peoples R China
5.Univ New South Wales, ARC Ctr Excellence Climate Extremes, Sydney, NSW, Australia
6.Univ New South Wales, Climate Change Res Ctr, Sydney, NSW, Australia
推荐引用方式
GB/T 7714		 Zan, Beilei,Yu, Ye,Li, Jianglin,et al. Solving the storm split-merge problem-A combined storm identification, tracking algorithm[J]. ATMOSPHERIC RESEARCH,2019,218:335-346.
APA Zan, Beilei,Yu, Ye,Li, Jianglin,Zhao, Guo,Zhang, Tong,&Ge, Jun.(2019).Solving the storm split-merge problem-A combined storm identification, tracking algorithm.ATMOSPHERIC RESEARCH,218,335-346.
MLA Zan, Beilei,et al."Solving the storm split-merge problem-A combined storm identification, tracking algorithm".ATMOSPHERIC RESEARCH 218(2019):335-346.

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