DOI: 10.1007/s11069-020-04018-4
论文题名: Forewarning method of downburst based on feature recognition and extrapolation
作者: Wang X. ; Wang J. ; Miao C. ; Zeng K.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2020
卷: 103, 期: 1 起始页码: 903
结束页码: 921
语种: 英语
中文关键词: Downburst
; Extrapolation
; Feature recognition
; Forewarning
; Microburst
英文关键词: algorithm
; Doppler radar
; optical method
; pattern recognition
; statistical analysis
; thunderstorm
英文摘要: Currently, using common meteorological data for downburst identification and early warning lacks feasibility. Therefore, a method based on the Doppler weather radar is proposed in this paper to identify, track and predict the downburst. The method is outlined as follows. Firstly, by using the optical flow method, optical flow fields of the reflectivity factors in vertical section are analyzed. The temporal evolution rule of the thunderstorm core is found. Secondly, the Lagrangian mechanical model is used for function fitting of the thunderstorm-core top’s sinking process. Lastly, by adopting histogram and the Bhattacharyya coefficient (BC), the statistical analysis is carried out to match and identify the positive and negative velocity pairs in the middle-level radial velocity field of the thunderstorm core. Moreover, a series of thresholds are also analyzed to achieve the intelligent forewarning of the downburst. In this paper, the local constraint algorithm featuring multi-layer iteration is introduced, which effectively improves the inapplicability issue in the traditional method of analyzing non-rigid moving targets such as echo. Furthermore, the measure based on the histogram and the BC are proposed to solve the image matching problem due to the asymmetric structure of positive and negative velocity pair images in the radial direction. The experiment results show that the method is able to identify the potential downburst at the early stage of the thunderstorm-core rising or sinking processes. Meanwhile, the descent velocity and time of the thunderstorm core reaching near surface can be estimated, and then, the intelligent identification and early warning of downbursts can be realized. © 2020, Springer Nature B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168790
Appears in Collections: 气候变化与战略
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作者单位: National Demonstration Center for Experimental Atmospheric Science and Environmental Meteorology Education, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Recommended Citation:
Wang X.,Wang J.,Miao C.,et al. Forewarning method of downburst based on feature recognition and extrapolation[J]. Natural Hazards,2020-01-01,103(1)