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Delineation of precipitation regions using location and atmospheric variables in two Canadian climate regions: the role of attribute selection

机译:使用位置和大气变量在两个加拿大气候区中描述降水区:属性选择的作用

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The identification of homogeneous precipitation regions is essential in the planning, design and management of water resources systems. Regions are identified using a technique that partitions climate sites into groups based on the similarity of their attributes; the procedure is known as regionalization. In this paper the ability of four attribute sets to form large, coherent precipitation zones is assessed in terms of the regional homogeneity of precipitation statistics and computational efficiency. The outcomes provide guidance for effective attribute selection for future studies in Canada. The attributes under consideration include location parameters (latitude, longitude), distance to major water bodies, site elevation and atmospheric variables modelled at different pressure levels. The analysis is conducted in two diverse climate regions within Canada including the Prairie and the Great Lakes-St Lawrence lowlands regions. The method consists of four main steps: (i) formation of the attribute sets; (ii) determination of the preferred number of regions (selection of the c-value) into which the sites are partitioned; (iii) regionalization of climate sites using the fuzzy c-means clustering algorithm; and (iv) validation of regional homogeneity using L-moment statistics. The results of the attribute formation, c-value selection, regionalization and validation processes are presented and discussed in a comparative analysis. Based on the results it is recommended for both regions to use location parameters including latitude, longitude and distance to water bodies (in the Great Lakes region) to form precipitation regions and to consider atmospheric variables for future (climate change) applications of the regionalization procedure.
机译:在水资源系统的规划,设计和管理中,均质降水区的识别至关重要。使用一种技术可以识别区域,根据其属性的相似性将气候站点分为几类;该过程称为区域化。本文根据降水统计数据的区域均匀性和计算效率,评估了四个属性集形成大的,连贯的降水区的能力。结果为将来在加拿大进行有效的属性选择提供了指导。所考虑的属性包括位置参数(纬度,经度),到主要水体的距离,站点海拔和在不同压力水平下建模的大气变量。该分析是在加拿大的两个不同气候区域进行的,其中包括大草原和大湖区-圣劳伦斯低地地区。该方法包括四个主要步骤:(i)形成属性集; (ii)确定将位点划分为的优选区域数(选择c值); (iii)使用模糊c均值聚类算法对气候站点进行区域划分; (iv)使用L矩统计资料验证区域同质性。在比较分析中介绍并讨论了属性形成,c值选择,区域化和验证过程的结果。根据结果​​,建议两个地区都使用位置参数,包括纬度,经度和与水体的距离(在大湖区中)以形成降水区,并考虑将大气变量用于分区程序的未来(气候变化)应用。

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