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基于模糊逻辑的冰雹天气雷达识别算法
引用本文:张秉祥,李国翠,刘黎平,李 哲,王丛梅,王丽萍. 基于模糊逻辑的冰雹天气雷达识别算法[J]. 应用气象学报, 2014, 25(4): 415-426
作者姓名:张秉祥  李国翠  刘黎平  李 哲  王丛梅  王丽萍
作者单位:1.河北省石家庄市气象局,石家庄 050081
基金项目:中国气象局“新一代天气雷达建设业务软件系统开发项目”,河北省气象局科研项目(13ky24),河北暴雨和强对流创新团队项目
摘    要:该文确定了冰雹天气的5个雷达识别指标和不同季节识别指标对应的隶属函数,采用等权重系数法建立了基于模糊逻辑原理的冰雹天气识别算法。应用雷达回波拼图数据、冰雹灾害报告和常规探空资料,对2008—2012年华北地区103个冰雹样本进行了识别效果检验,给出了识别评分结果、识别提前量和冰雹位置等。结果表明:华北区域性冰雹的识别命中率、虚警率和临界成功指数分别为73.9%,36.4%和51.9%,其中石家庄地区的零散冰雹能够被完全识别,最大直径超过30 mm冰雹对应风暴单体综合识别判据在0.85以上;在空间分布上,被识别到可能出现冰雹的风暴单体区域和实况有冰雹的测站空间分布基本一致,冰雹出现位置一般位于强风暴单体的周边区域;相对单要素识别,综合识别算法识别准确率有所提高,识别范围得到改善,自动化程度也较高;冰雹被识别到的最早时间普遍早于冰雹出现时间,平均提前量为30 min。

关 键 词:冰雹   识别方法   雷达拼图数据   模糊逻辑
收稿时间:2013-07-16
修稿时间:2014-04-08

Identification Method of Hail Weather Based on Fuzzy logical Principle
Zhang Bingxiang,Li Guocui,Liu Liping,Li Zhe,Wang Congmei and Wang Liping. Identification Method of Hail Weather Based on Fuzzy logical Principle[J]. Journal of Applied Meteorological Science, 2014, 25(4): 415-426
Authors:Zhang Bingxiang  Li Guocui  Liu Liping  Li Zhe  Wang Congmei  Wang Liping
Affiliation:1.Shijiazhuang Meteorological Bureau of Hebei Province, Shijiazhuang 0500812.State Key Lab of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 1000813.Electric Power Research Institute, Henan Electric Power Company, Zhengzhou 4500524.Xingtai Meteorological Bureau of Hebei Province, Xingtai 0540005.Hengshui Meteorological Bureau of Hebei Province, Hengshui 053000
Abstract:Based on previous researches and hail warning indexes in Hebei Province, five main radar identification indices for hail detection are given: Storm maximum reflectivity, storm maximum vertical integrated liquid water content, echo top, vertical integrated liquid (VIL) density and storm center height. The corresponding membership functions of each identification index in different seasons are also calculated. Identification method of hail on fuzzy-logical principles is established adopting the equal weight coefficient method.Based on radar mosaic data, disaster report of hail and route sounding data, 103 hail cases from 2008 to 2012 in North China are statistically analyzed and tested. The hitting rate of hail, the leading time and position of hail are given.The hitting rate, the false alarm rate and the critical success index of regional hail in North China are 73.9%, 36.4% and 51.9%, respectively, and all the scattered hail in Shijiazhuang can be identified. When the radar identification index is greater, the corresponding probability and the maximum diameter of hail is also bigger. The identification index is above 0.85 when the maximum diameter is more than 30 mm. On the spatial distribution, the area of identified storm and hail station is consistent. The hail station is nearby and around the corresponding storm monomer. The omission of hail occurs mostly in Zhangjiakou and Chengde, which may be caused by radar band range and regional characteristics. In contrast of single factor identification, the accuracy rate of comprehensive recognition is improved, and it also has a high degree of automation. The first time when the recognition criterion continuous is greater than the threshold value is always ahead of the epoch of hail, and the mean leading time is 30 minutes. By the recognition of hail in Shijiazhuang, the hitting rate, the false alarm rate and the critical success index of radar own recognition software are 100%, 78.2% and 21.8%, respectively, while the result of identification method on fuzzy-logical principles reaches 100%, 44.4% and 55.6%. Obviously, all hails are correctly identified, while the false alarm rate is significantly reduced, and the critical success index is increased.In summary, the automatic identification method based on fuzzy-logical principles is efficient and feasible, with more automatic algorithm. It can reduce the forecaster workload and has important practical guiding significance for short-term forecasting, nowcast warning and system development.
Keywords:hail   identification method   radar mosaic data   fuzzy logical principle
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