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Automatic Identification and Alert of Gust Fronts
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摘要: 根据阵风锋的回波特征, 该文设计了阵风锋自动识别算法。在速度场中，考虑辐合线识别；在强度场中，考虑窄带回波识别；根据窄带与辐合线的空间一致性，综合二者识别出阵风锋。基于该算法，以锋线闪烁和物理量输出两种方式实现了预警功能。最后利用地面自动气象站资料和2009年6月3日河南商丘、郑州及2009年6月5日安徽阜阳3个雷达站探测的阵风锋98个体扫样本资料检验了识别效果，并采用临界成功指数进行评估。结果表明：双向梯度法能有效滤除大范围降水回波而保留窄带回波；该算法只需考虑较低仰角层，大大提高识别效率。在速度场中采用的算法能有效识别出径向辐合线，同时也适用于低空径向风切变和辐合线的识别；利用临界成功指数对98个体扫样本进行识别率评估，识别率达到68.4%。Abstract: Gust fronts often cause serious ground gale and strong wind shear. Therefore, the short-term forecast, nowcasting and civil aviation department pay high attention to the research of gust fronts. Based on the echo characteristics of gust fronts in reflectivity field and velocity field of Doppler radar, an identification algorithm for gust fronts is designed. In the velocity field, the convergence line is identified by finding the consistent decreasing radial velocity and inspected by using a convergence parameter threshold, a grads threshold and a flux threshold. In the reflectivity field, the reflectivity data are classified into different levels. Then, the narrowband is identified by an algorithm called bilateral grads, which is designed by fully using the narrowband geometrical characteristic, the interval between narrowband and echo matrix. The bilateral grads algorithm can effectively filter out the wide range of precipitation echoes and reserve the narrowband in reflectivity image. Meanwhile, in order to filter out the remainder noise, length calculated and image thinning technique are used during above processes. According to the consistency of narrowband and the convergence line in the space, the gust front can be identified. The achievement of alert function uses an image flicker and some physical quantities output to represent the strength of the gust front. Finally, 98 volume-scanning data from 3 radar stations and the automatic weather station data and ICS are used to evaluate the identification effect. The bilateral grads algorithm can effectively filter out the big range precipitation echo and keep the narrowband signal, it has an important relationship with the distance between the narrowband and maternal storm echo. Combined with the composite reflectivity to contrast all-layer reflectivity, the narrowband or the stronger reflectivity doesn't exist at the higher elevation, therefore, the algorithm simply handles the low elevation, which can improve the identification efficiency. The convergence line can be identified effectively by this method, and at the same time, it can also identify the low-level wind shear. The identification rate evaluated by ICS from 98 volume-scanning data reaches 68.4%, indicating that the identification algorithm has the capacity of identifying gust fronts.
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图 1 2009年6月3日14:15商丘雷达速度场锋线上的辐合段选取(仰角为0.5°, 方位角为160°)
Fig. 1 Convergence segment search across the front line of Shangqiu radar at 1415 UTC 3 June 2009(elevation:0.5°; azimuth:160°)
图 3 2009年6月3日郑州雷达阵风锋识别图
Fig. 3 Identification image of gust front of Zhengzhou radar on 3 June 2009
图 4 2009年6月3日商丘雷达阵风锋识别图
Fig. 4 Identification image of gust front of Shangqiu radar on 3 June 2009
图 5 2009年6月5日阜阳雷达阵风锋识别图
Fig. 5 Identification image of gust front of Fuyang radar on 3 June 2009
表 1 反射率因子分级表
Table 1 The reflectivity classification table
反射率因子区间/dBZ 所归级别/dBZ (-5, 0] 0 (0, 5] 5 (5, 10] 10 (10, 15] 15 (15, 20] 20 (20, 25] 25 (25, 30] 30 (30, 35] 35 (35, 40] 40 (40, 45] 45 (45, 50] 50 (50, 55] 55 (55, 60] 60 (60, 65] 65 (65, 70] 70 (70, +∞) -999 
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表 2 阵风锋过程样本数和识别情况
Table 2 The number of gust front processes, samples and identification
雷达站点 样本数 成功识别
样本数未能识别
样本数误识别
样本数商丘 33 26 7 0 郑州 25 17 8 0 阜阳 40 24 16 0
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表 3 总样本的临界成功指数ICS、命中率RH、漏报率RM和虚警率RFA
Table 3 ICS, RH, RM and RFA of total samples
总样本数 ICS RH RM RFA 98 0.684 0.684 0.316 0
下载: 导出CSV
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[1] Simpson J E A. Comparison between laboratory and atmospheric density currents. Quart J Roy Meteor Soc, 1969, 95: 578-765. doi: 10.1002/qj.49709540609/full [2] Wakimoto R M.The life cycle of thunderstorm gust front as viewed with Doppler Radar and Rawinsonde Data. Mon Wea Rev, 1982, 110: 1060-1082. doi: 10.1175/1520-0493(1982)110<1060:TLCOTG>2.0.CO;2 [3] Wilson J W, Schreiber W E. Initiation of convective storms at radar observer boundary layer convergence lines. Mon Wea Rev, 1986, 114: 2516-2536. doi: 10.1175/1520-0493(1986)114<2516:IOCSAR>2.0.CO;2 [4] 葛润生.阵风锋的雷达探测和研究.气象科学研究院院刊, 1986, 1(2):113-121. http://www.cnki.com.cn/Article/CJFDTOTAL-YYQX198602000.htm [5] 陈明轩, 愈小鼎, 谭晓光, 等.对流天气临近预报系统技术的发展与研究进展.应用气象学报, 2004, 15(6):754-766. http://www.cnki.com.cn/Article/CJFDTotal-YYQX200406015.htm [6] 陈明轩, 高峰, 孔荣, 等.自动临近预报系统及其在北京奥运期间的应用.应用气象学报, 2010, 21(4):394-404. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20100402&flag=1 [7] 王彦, 于莉莉, 李艳伟, 等.边界层辐合线对强对流系统形成和发展的作用.应用气象学报, 2011, 22(6):724-731. doi: 10.11898/1001-7313.20110610 [8] 黄旋旋, 何彩芬, 徐迪峰, 等.阵风锋过程形成机制探讨.气象, 2008, 34(7):380-387. http://www.cnki.com.cn/Article/CJFDTOTAL-QXXX200807005.htm [9] 毕旭, 刘慧敏, 赵榆飞.陕北系列阵风锋天气过程分析.陕西气象, 2008(2):23-26. http://www.cnki.com.cn/Article/CJFDTOTAL-SXQI200802008.htm [10] 刘勇, 王楠, 刘黎平.陕西两次阵风锋的多普勒雷达和自动气象站资料分析.高原气象, 2007, 26(2):380-387. http://www.cnki.com.cn/Article/CJFDTOTAL-GYQX200702020.htm [11] 何彩芬, 姚秀萍, 胡春蕾, 等.一次台风前部龙卷的多普勒天气雷达分析.应用气象学报, 2006, 17(3):370-375. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20060363&flag=1 [12] 姚建群, 戴建华, 姚祖庆.一次强飑线的成因及维持和加强机制分析.应用气象学报, 2005, 16(6):746-753. doi: 10.11898/1001-7313.20050615 [13] Uyeda H, D Zrnic S. Automatic detection of gust front. J Atmos Oceanic Technol, 1985, 3: 36-50. https://www.researchgate.net/publication/235056850_Automatic_Detection_of_Gust_Fronts [14] Delanoy R L, Troxel S W. The Machine Intelligent Gust Front Algorithm. MIT Lincoln Laboratory Project Report ATC-196, 1993. https://www.ll.mit.edu/mission/aviation/publications/publication-files/atc-reports/Delanoy_1993_ATC-196_WW-15318.pdf [15] Troxel S W, DelanoyR L, Pmorgan J P, et al. Machine Intelligent Gust Front Algorithm for the Terminal Doppler Weather Radar (TDWR) and Integrated Terminal Weather System (ITWS). AMS Workshop on Wind Shear and Wind Shear Alert Systems, 1996: 70-79. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.89.4239 [16] 宗蓉. 多普勒天气雷达的阵风锋识别方法探索. 南京: 南京信息工程大学, 2009. [17] 李劲. 利用多普勒天气雷达自动识别阵风锋方法研究. 南京: 南京信息工程大学, 2010. [18] 陈刚. 阵风锋的检测与识别. 西安: 西安电子科技大学, 2009. [19] 王楠, 刘黎平, 徐宝祥, 等.利用多普勒雷达资料识别低空风切变和辐合线方法研究.应用气象学报, 2007, 18(3):314-320. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20070353&flag=1 -
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