Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2017.10.027 |
Enhanced object-based tracking algorithm for convective rain storms and cells | |
Munoz, Carlos1; Wang, Li-Pen1,2; Willems, Patrick1 | |
2018-03-01 | |
发表期刊 | ATMOSPHERIC RESEARCH
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ISSN | 0169-8095 |
EISSN | 1873-2895 |
出版年 | 2018 |
卷号 | 201页码:144-158 |
文章类型 | Article |
语种 | 英语 |
国家 | Belgium; England |
英文摘要 | This paper proposes a new object-based storm tracking algorithm, based upon TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting). TITAN is a widely-used convective storm tracking algorithm but has limitations in handling small-scale yet high-intensity storm entities due to its single-threshold identification approach. It also has difficulties to effectively track fast-moving storms because of the employed matching approach that largely relies on the overlapping areas between successive storm entities. To address these deficiencies, a number of modifications are proposed and tested in this paper. These include a two-stage multi threshold storm identification, a new formulation for characterizing storm's physical features, and an enhanced matching technique in synergy with an optical-flow storm field tracker, as well as, according to these modifications, a more complex merging and splitting scheme. High-resolution (5-min and 529-m) radar reflectivity data for 18 storm events over Belgium are used to calibrate and evaluate the algorithm. The performance of the proposed algorithm.is compared with that of the original TITAN. The results suggest that the proposed algorithm can better isolate and match convective rainfall entities, as well as to provide more reliable and detailed motion estimates. Furthermore, the improvement is found to be more significant for higher rainfall intensities. The new algorithm has the potential to serve as a basis for further applications, such as storm nowcasting and long-term stochastic spatial and temporal rainfall generation. |
英文关键词 | Storm tracking Convective Weather radar Image segmentation Optical flow Nowcasting |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000418981500011 |
WOS关键词 | CONTINENTAL RADAR IMAGES ; SINGLE DOPPLER RADAR ; WEATHER RADAR ; VARIATIONAL ANALYSIS ; NOWCASTING SYSTEM ; URBAN HYDROLOGY ; HEAVY RAINFALL ; TIME-SERIES ; PRECIPITATION ; IDENTIFICATION |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/15188 |
专题 | 地球科学 |
作者单位 | 1.Katholieke Univ Leuven, Dept Civil Engn, Hydraul Sect, B-3001 Heverlee, Belgium; 2.RainPlusPlus Ltd, Derby DE1 3RL, England |
推荐引用方式 GB/T 7714 | Munoz, Carlos,Wang, Li-Pen,Willems, Patrick. Enhanced object-based tracking algorithm for convective rain storms and cells[J]. ATMOSPHERIC RESEARCH,2018,201:144-158. |
APA | Munoz, Carlos,Wang, Li-Pen,&Willems, Patrick.(2018).Enhanced object-based tracking algorithm for convective rain storms and cells.ATMOSPHERIC RESEARCH,201,144-158. |
MLA | Munoz, Carlos,et al."Enhanced object-based tracking algorithm for convective rain storms and cells".ATMOSPHERIC RESEARCH 201(2018):144-158. |
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