Regionalizing Mean Air Temperature in Iran by Multivariate Analysis and L-Moment Methods

Abstract

AbstractThis research presents a spatial clustering of mean air temperature in Iran based on monthly data of 44 synoptic and climatologic stations from 1951 to 2010 via multivariate and L-moment methods. After standardizing the data, two multivariate methods of factor analysis (FA) and cluster analysis (CA) were used to derive primary homogeneous regions. Then, two L-moment based indices were applied to examine the homogeneity of the derived clusters along with the discordancy of each cluster’s member(s). Next, considering geographical similarities of different parts of Iran as well as local weather regimes, discordant stations were moved to other clusters. The two latter steps were repeated (a trial-and-error process) to derive final homogeneous clusters. The optimum status, in terms of air temperature, resulted in a grouping of eight homogeneous regions in Iran for which there were reasonable relationships between clusters and the natural geography of the country. Considering the results, in most of the...