Regionalizing Mean Air Temperature in Iran by Multivariate Analysis and L-Moment Methods
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Volume 21, Issue 2
Abstract
This 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 regions, four months of June through September showed the highest mean air temperature in Iran; while December, January, and February indicated the lowest ones.
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Acknowledgments
We do acknowledge the constructive comments of three anonymous referees to promote the quality of this research.
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Journal of Hydrologic Engineering
Volume 21 • Issue 2 • February 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Aug 25, 2014
Accepted: Jun 26, 2015
Published online: Aug 5, 2015
Discussion open until: Jan 5, 2016
Published in print: Feb 1, 2016
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