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  2015, Vol. 34 Issue (2): 586-595    DOI: 10.7522/j.issn.1000-0534.2014.00005
Statistical Characteristics and Automatic Detection of the Gust Front in Radar Reflectivity Data
XU Fen1, YANG Ji1, XIA Wenmei1, ZHOU Honggen2
1. Jiangsu Institute of Meteorological Sciences, Nanjing 210009, China;
2. Jiangsu Meteorological Observation Center, Nanjing 210009, China
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Abstract  The variation features, the relationship between the moving speed and the arc length, and the overall and partial characteristics in the radar reflectivity data images of the gust front along the Yangtze River in Jiangsu are analyzed using Nanjing CINRAD data combined with the AWS wind data from 2009 to 2012. The radar reflectivity data distribution features of the three kinds of NBE are also analyzed in detail. An echo flatness calculation method is designed to analyze the similarities of the three NBEs in quantity. It is also found that the radial bands belong to the gust front echo can be identified by the wave width, the number of the wave peak,the peak threshold, and the bilateral gradient waveform from the radial wave characteristics in this article. The automatic detection of the gust front echo is achieved by combining the echo flatness testing method with the gust front radial waveform detection algorithm based on the radar reflectivity data preprocessing method. Finally, the effect results of the detection algorithm show that the detection accuracy rate is about 87% or more in the independent gust front whose average reflectivity data > 5 dBZ, and the detection accuracy rate is about 89% or more in the blended gust front whose average reflectivity data > 10 dBZ. The identification rate of the weak gust front is still low.
Key words:  The gust front      Radar data      Echo flatness testing      Radial wave shape      Automatic detection     
Received:  01 July 2013      Published:  24 April 2015
Articles by authors
XU Fen
XIA Wenmei
ZHOU Honggen

Cite this article: 

XU Fen, YANG Ji, XIA Wenmei, ZHOU Honggen. Statistical Characteristics and Automatic Detection of the Gust Front in Radar Reflectivity Data. , 2015, 34(2): 586-595.

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[1] 张培昌, 杜秉玉, 戴铁丕编著. 雷达气象学[M]. 北京: 气象出版社, 2001: 280-341, 402-409, 418.
[2] Bedard A J J R, Hooke W H, Beran D W. The dulles airport pressure jump detector array for gust front detection[J]. Bull Amer Meteor Soc, 1977, 58: 920-926.
[3] 徐芬, 王博妮, 夏文梅, 等. 长江中下游地区一次春季暴雨过程的多普勒雷达速度特征分析与研究[J]. 高原气象, 2014, 33(2): 548-556, doi: 10.7522/j.issn. 1000-0534. 2012. 00195.
[4] 徐学义, 赵振东, 梁红新. 三次非超级单体龙卷风暴多普勒雷达特征对比分析[J]. 高原气象, 2014, 33(4): 1164-1172, doi: 10.7522/j.issn.1000-0534.2013.00036.
[5] 廖向花, 周毓荃, 唐余学, 等. 重庆一次超级单体风暴的综合分析[J]. 高原气象, 2010, 29(6): 1556-1564.
[6] 俞小鼎, 郑媛媛, 廖玉芳, 等. 一次伴随强烈龙卷的强降水超级单体风暴研究[J]. 大气科学, 2008, 32: 508-522.
[7] 王秀明, 俞小鼎, 周小刚. "6·3"区域致灾雷暴大风形成及维持原因分析[J]. 高原气象, 2012, 31(2): 504-514.
[8] 王福侠, 裴宇杰, 杨晓亮, 等. "090723"强降水超级单体风暴特征及强风原因分析[J]. 高原气象, 2011, 30(6): 1690-1700.
[9] 徐珺, 毕宝贵, 谌芸. 济南7·18 大暴雨中尺度分析研究[J]. 高原气象, 2010, 29(5): 1218-1229.
[10] 肖艳姣, 万玉发, 吴涛, 等. 基于多普勒天气雷达的两种垂直风廓线反演方法的对比分析[J]. 高原气象, 2015, 34(1): 288-297, doi: 10.7522/j.issn.1000-0534.2013.00136.
[11] Delanoy R L, Troxel S W. Machine intelligent gust front algorithm[R]. MIT Lincoln Laboratory, Project Report ATC, 1993: 1-196.
[12] Smally D J, Bennett B J, Frankel R, et al. MIGFA: The machine intelligent gust front algorithm for NEXRAD[C]. Preprints, 32nd Conference on Radar Meteorology, Albuquerque, NM, Amer Meteor Soc, 2005.
[13] Aurie G, Hermes, Arthur W. The gust-front detection and wind-shift algorithms for the terminal doppler weather radar sysem[J]. J Atmos Ocean Technol, 1993, 10: 693-709.
[14] Troxel S, Frankel B, Echels B, et al. An Improved gust front detection capability for the ASR-9 WSP[C]. 10th Conference on Aviation, Range, and Aerospace Meteorology, Portland, OR, 2002: 379-382.
[15] Andrew C N, Sun Juanzhen. Analysis and forecasting of the low-level wind during the Sydney 2000 forecast demonstration project[J]. Wea Forecasting, 2004, 2(19): 151- 167.
[16] 陈钢. 阵风锋的检测与识别[D]. 西安: 西安电子科技大学, 2009.
[17] 夏文梅, 慕熙昱, 徐芬, 等. 南京地区初夏一次阵风锋过程的分析与识别[J]. 高原气象, 2009, 28(4): 836-845.
[18] 李劲, 徐芬, 顾松山. 基于雷达反射率的阵风锋自动识别算法研究[C]. 第28届中国气象学会年会, 2011.
[19] 程浩, 刘国庆. 基于熵函式模板的阵风锋自动识别与实现[J]. 计算机工程与设计, 2011, 32(6): 2173-2175.
[20] 王彦, 于莉莉, 朱男男, 等. 渤海海湾海风锋与雷暴天气[J]. 高原气象, 2011, 30(1): 245-251.
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