中国农业气象 ›› 2013, Vol. 34 ›› Issue (02): 249-254.doi: 10.3969/j.issn.1000-6362.2013.02.019

• 论文 • 上一篇    下一篇

冰雹数据库扩容前后对比分析——以安徽省为例

唐为安1,田红1,莫伟强2,温华洋1   

  1. 1安徽省气候中心,合肥230031;2东莞市气象局,东莞523086
  • 收稿日期:2012-05-07 出版日期:2013-04-20 发布日期:2013-04-16
  • 作者简介:唐为安(1980-),江苏阜宁人,硕士,工程师,主要从事气候变化及其对农业影响评估研究.Email:twa_1980@163.com
  • 基金资助:
    2009年公益性行业(气象)科研专项“全球变化背景下中国气象灾害风险区划研究”(GYHY200906019)

Comparative Analysis on Hail Database Expansion——A Case Study of Anhui Province

TANG Wei an1,TIAN Hong1,MO Wei qiang2,WEN Hua yang1   

  • Received:2012-05-07 Online:2013-04-20 Published:2013-04-16

摘要: 以安徽省为例,通过信息化气象记录报表和查阅相关资料等方式,对全省冰雹数据库进行扩容,并对扩容前后冰雹资料的样本信息及其时空分布特征的差异进行分析,旨在为相关冰雹灾害研究提供借鉴与参考。结果表明,安徽省冰雹数据库扩容后,冰雹记录从793条增至2079条。扩容前后的冰雹数据分析均显示安徽省冰雹年发生次数存在年代际变化,M-K检验表明分别在1974年和1972年前呈显著增加趋势(P<0.01),其后呈微弱下降趋势;冰雹多发于春夏两季,而少发于秋、冬季;冰雹高发时段集中在15:00-17:00。扩容后安徽冰雹发生次数增加和下降两个阶段的变化速率均大于扩容前,年内冰雹发生次数最大值扩容前出现在3月,扩容后在6月。冰雹数据扩容后的冰雹空间分布覆盖了全省冰雹主要影响路径,减少了研究结果的不确定性,更符合实际情况,对进一步提高冰雹灾害评估与应对能力具有重要意义。

关键词: 冰雹日, 观测资料, 数据库扩容, 对比分析

Abstract: In order to provide references to hail disaster research,a new hail database in Anhui province was expended by using of information meteorological records and meteorological dictionaries literature,the spatial temporal distribution differences between new database and previous database was analyzed. The results showed that the hail records increased from 793 to 2079 after expansion. The annual occurrence frequency of hail presented decadal variation in both two databases,and increased significantly before the year of 1974 and 1972 by using of the Mann-Kendall trend test(P<0.01). The hail occurred frequently in spring and summer,rarely in autumn and winter. The hail occurred typically from 15:00 to 17:00. However,the variation rate of hail occurrence from previous database was smaller than from the new database. The peak number of monthly hail occurrence appeared in March in old database,and in June after expansion. In general,the hail spatial distribution of expansion database included the main paths,which reduced research uncertainties

Key words: Hail days, Observation data, Database expansion, Comparative analysis