Zhang Bingxiang, Li Guocui, Liu Liping, et al. Identification method of hail weather based on fuzzy-logical principle. J Appl Meteor Sci, 2014, 25(4): 415-426.
Citation: Zhang Bingxiang, Li Guocui, Liu Liping, et al. Identification method of hail weather based on fuzzy-logical principle. J Appl Meteor Sci, 2014, 25(4): 415-426.

Identification Method of Hail Weather Based on Fuzzy-logical Principle

  • Received Date: 2013-07-16
  • Rev Recd Date: 2014-04-08
  • Publish Date: 2014-07-31
  • 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.

  • Fig. 1  Distribution of hail stations in North China

    Fig. 2  Membership functions of each identification index in different months for hail

    Fig. 3  The identified thunderstorms and stations of hail from 1300 BT to 1800 BT on 23 June 2008

    Fig. 4  The radar CR, identified thunderstorm and stations of hail

    (a)1600 BT 23 June 2008, (b)1230 BT 17 May 2008, (c)2048 BT 26 July 2011

    Fig. 5  Scatter diagram between maximum diameter of hail and RM, MVIL, TE, P

    Fig. 6  The radar CR and identified hail (▲ denotos identified hail)

    (a)1600 BT 23 June 2008, (b)1230 BT 17 May 2008, (c)2048 BT 26 July 2011

    Table  1  Average height of 0℃ and-20℃ at Xingtai Sounding Station from May to September during 2008-2012

    月份H0℃/kmH-20℃/km
    53.96.8
    64.27.3
    74.88.1
    84.78.0
    94.07.0
    DownLoad: Download CSV

    Table  2  Standard values of identified indices from May to September

    雷达识别指标5月与9月6—8月
    阈值下限阈值上限阈值下限阈值上限
    RM/dBZ45555060
    MVIL/(kg·m-2)10203555
    TE/km681012
    DVIL/(g·m-3)3.24.03.24.0
    HMH0℃H-20℃H0℃H-20℃
    DownLoad: Download CSV

    Table  3  The regional hail weather processes in North China

    出现时间冰雹站数命中率/%虚警率/%临界成功指数/%冰雹影响区域
    2008-05-11T18:00—21:00850.033.340.0石家庄、邢台、保定、张家口、承德
    2008-06-23T13:00—18:001291.731.364.7北京、石家庄、廊坊、承德、保定
    2009-07-23T14:00—19:00785.733.360.0北京、石家庄、廊坊、张家口、承德
    2009-08-27T16:00—18:00810038.561.5石家庄、邢台
    2008-05-03T09:00—16:00610060.040.0北京、天津、邯郸、保定、沧州
    2008-06-25T14:00—20:00988.938.557.1天津、邯郸、张家口、承德
    2010-06-17T11:00—21:001040.033.333.3天津、廊坊、沧州、唐山、承德
    2011-06-11T10:00—18:001758.816.752.6北京、保定、廊坊、沧州、张家口、承德
    2011-06-23T13:00—18:00785.725.066.7北京、保定、张家口、承德
    2012-09-27T11:00—18:00862.544.441.7保定、衡水、张家口、秦皇岛
    DownLoad: Download CSV

    Table  4  The scattered hail and identified indices of thunderstorm

    冰雹出现时间站名冰雹直
    径/mm
    风暴单体识别提前
    量/min
    PRM/dBZMVIL/(kg·m-2)DVIL/(g·m-3)TE/kmHM/km
    2008-05-17T12:04灵寿20.6058.8213.472.716
    2008-05-17T12:31正定60.8063.8374.493.543
    2008-05-17T14:01新河60.8060.4303.8104.160
    2011-07-26T20:52石家庄150.8859.0565.6125.852
    2012-05-25T15:22新乐50.8058.4333.4103.716
    2012-06-01T16:28涉县50.7055.0284.0127.84
    2012-06-01T18:05平山60.4060.8325.273.160
    2012-06-21T16:03栾城60.6256.6443.3146.215
    2012-06-21T16:06曲阳40.5061.2353.1124.136
    2012-06-21T17:43怀安60.4959.4304.3105.27
    2012-07-03T20:06赞皇80.5355.8363.6125.430
    DownLoad: Download CSV
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    • Received : 2013-07-16
    • Accepted : 2014-04-08
    • Published : 2014-07-31

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