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Statistically-based regionalization of rainfall climates of Iran

机译:基于统计的伊朗降雨气候区域化

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Iran is a large country with diverse geophysical and climatic conditions which are influenced by both large atmospheric circulation patterns and local effects. The density of rainfall station network of Iran is not enough for rainfall estimation at ungauged regions. Therefore, rainfall regionalization should be used to extend rainfall data to regions where rainfall data are not available. The aim of this study is to use cluster analysis and L-moment methods together to quantify regional rainfall patterns of Iran using annual rainfall of 137 stations for the period of 1952-2003. The cluster analysis follows "Ward's method" and shows eight regions of rainfall in Iran. The homogeneity test of L-moments shows that most of these regions are homogeneous. Using the goodness-of-fit test, Z~(Dist), the regional frequency distribution functions for each group are then selected The 3-parameter Log Normal (LN3), Generalized Extreme Value (GEV) and generalize logistic (GLOG) distributions are selected for the first, second and the remaining 6 regions of rainfall over Iran, respectively. However, because of different rainfall generating mechanisms in Iran such as elevation, sea neighborhood and large atmospheric circulation systems, no parent distribution could be found for the entire country.
机译:伊朗是一个大国,地球物理和气候条件各不相同,受大气环流模式和局部影响的影响很大。伊朗降雨站网的密度不足以估算未开垦地区的降雨量。因此,应使用降雨分区将降雨数据扩展到没有降雨数据的区域。这项研究的目的是结合使用聚类分析和L矩方法,利用1952-2003年间137个站点的年降雨量来量化伊朗的区域降雨模式。聚类分析遵循“沃德方法”,显示了伊朗的八个降雨区域。 L矩的均匀性测试表明,这些区域大多数都是均匀的。然后,使用拟合优度检验Z〜(Dist),选择每个组的区域频率分布函数。三参数对数正态(LN3),广义极值(GEV)和广义对数(GLOG)分布为分别为伊朗的第一,第二和其余六个降雨区选择。但是,由于伊朗不同的降雨产生机制,例如海拔,海洋邻里和大型大气环流系统,在整个国家都找不到母系分布。

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