宿州雷暴氣候特征及其災變GANN預測模型研究
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Characteristics of Thunderstorm Weather and GANN Predicting Model Based on the Thunderstorm Disaster Variation in Suzhou
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    摘要:

    根據宿州市5個氣象站1957~2008年雷暴日觀測資料,利用數理統計方法分析了宿州雷暴的時空分布規律,以及雷暴與降水、溫度的關系。結果顯示:宿州屬于多雷區,南部多于北部,南北相差3.21~4.65天;年際變化大,年累計雷暴日最多相差37天,初終雷及無雷期年際間振蕩的幅度較為劇烈,52年來累計雷暴日線性減少的趨勢明顯,減少幅度為1.61~2.89天/10a;季分布以夏季最多,冬季最少;月分布呈單峰型,雷暴多集中在4~9月,以7月最多,12月最少;日分布呈單峰型,以16:00~18:00頻率最大;多年平均月雷暴日數序列與相應的氣溫、降水量之間呈顯著正相關。為了進一步預測雷暴的長期演變趨勢,以埇橋為例建立了雷暴多發年份灰色人工神經網絡組合預測模型,預測下一個雷暴多發年將發生在2025年。

    Abstract:

    According to the data of thunderstorm days of five weather stations in Suzhou from 1957 to 2008, the timespace distribution of thunderstorms and the relationship of thunderstorms to rainfall and temperature in Suzhou are analyzed. The results show that Suzhou is an area attacked frequently by Lightning, and more lightning activities happen in the south part than in the north, with maximum difference being 3.21 to 4.65 days. There is great interannual variability of thunderstorm weather in Suzhou, and the annual cumulative number of thunderstorm days is up to 37 days. There is a linear decreasing trend in thunderstorm days with the range being 1.61 to 2.89 days per 10 years. Thunderstorm days exhibit a singlepeak type seasonal distribution, occur mostly in summer and least in winter, and centralized in the period from April to September, with maximum in July and minimum in December. The daily distribution is also the singlepeak type, with the maximum frequency from 16:00 to 18:00. The longrange mean series of average thunderstorm days has significantly positive correlation with rainfall and temperature. In order to predict the trend of thunderstorms, taking Yongqiao as an example, the greyBP combined model is built, and the results show that the year of 2025 is the next year of thunderstorms occurring most frequently.

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汪順勤,孫惠合,張丙振.宿州雷暴氣候特征及其災變GANN預測模型研究[J].氣象科技,2009,37(6):753~758

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  • 收稿日期:2009-04-02
  • 定稿日期:2009-07-10
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