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Meteorological hazard assessment based on trends and abrupt changes in rainfall characteristics on the Korean peninsula

机译:基于趋势和朝鲜半岛降雨特征突变的气象灾害评估

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摘要

This study presents a statistical approach for assessing meteorological hazards based on trends and abrupt changes in precipitation characteristics. Daily rainfall data from 64 stations in South Korea (SK) and 27 stations in North Korea (NK) were used to identify temporal patterns in the rainfall characteristics of both regions using seven rainfall indices, such as the total annual rainfall and annual number of wet days. This study suggests the use of three steps in identifying meteorological hazards based on two statistical analyses. In step 1, we conducted a trend analysis of a 10-year moving average of the rainfall index using the Mann-Kendall (MK) trend test. Most stations (65.6 %) in SK exhibit clear increasing trends in five indices, whereas far fewer have data indicating any trends in five of the indices in NK (25.9 %). In step 2, abrupt changes in all rainfall indices were identified using a Bayesian Change Point (BCP) approach. The results contradict those from the MK trend analysis. The proportion of stations in NK where trends were identified is much higher than that in SK. In step 3, the results from the two previous steps were integrated to identify the meteorological hazards based on the identified trend and change point. The BCP approach can be used to identify meteorological hazards that MK cannot, as the former approach focuses on the change point during the entire period. As a result, meteorological stability at the sites of weather stations can be identified, and then the meteorological hazards across the entire Korean peninsula can be spatially interpolated. Although SK and NK are located on the same peninsula, distinct differences in the trends were observed.
机译:这项研究提出了一种基于趋势和降水特征突变的评估气象灾害的统计方法。利用韩国(SK)的64个站点和朝鲜(NK)的27个站点的每日降雨量数据,使用七个降雨指数(例如年总降雨量和年湿润次数)来识别两个地区的降雨特征的时间模式。天。这项研究建议根据两个统计分析,使用三个步骤来确定气象灾害。在第1步中,我们使用Mann-Kendall(MK)趋势测试对降雨指数的10年移动平均值进行了趋势分析。 SK的大多数台站(65.6%)在五个指数中均显示出明显的增长趋势,而几乎没有数据表明NK中五个指数中的任何趋势(25.9%)。在第2步中,使用贝叶斯变化点(BCP)方法确定所有降雨指数的突变。结果与MK趋势分析的结果相矛盾。可以确定趋势的NK站的比例远高于SK。在第3步中,将前两个步骤的结果集成在一起,以便根据确定的趋势和变化点确定气象灾害。 BCP方法可用于识别MK无法识别的气象灾害,因为前一种方法侧重于整个时期的变化点。结果,可以确定气象站所在地的气象稳定性,然后可以在空间上插值整个朝鲜半岛的气象灾害。尽管SK和NK位于同一半岛上,但观察到趋势上存在明显差异。

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  • 来源
    《Theoretical and applied climatology》 |2017年第2期|305-326|共22页
  • 作者单位

    Minist Land Infrastruct & Transport, Geum River Flood Control Off, Gongju Si, Chungcheongnam, South Korea;

    Seoul Natl Univ Sci & Technol, Dept Civil Engn, Seoul, South Korea;

    Yonsei Univ, Dept Civil & Environm Engn, Seoul, South Korea;

    Seoul Natl Univ Sci & Technol, Dept Civil Engn, Seoul, South Korea|Natl Disaster Management Inst, Seoul, South Korea;

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