Climatic Zoning using Multi-Variable Statistical Methods at East Azarbyjan Province

Abstract

Climate is one of the most important and effective phenomenon of human life. Today's human, in order to develop industrial and municipal centers, and to increase food resources, needs to increase its information in the context of different climatic zones. The aim of this research was to achieve cluster classification by multivariate statistical methods. In this regard, 12 climatic elements were selected from 11 synoptic stations (isometropia) inside the East Azarbaijan Province for climatic zoning of the region. The maps and diagrams (plots) were plotted using SURFER and MATLAB software and data analysis was done using SPSS and MINITAB. The principal components analysis was performed for the average temperature, water vapor pressure difference between the maximum and minimum temperature and wind data. Moreover, in factor analysis with varimax rotation, three factors were obtained: humidity, average mean temperature, and minimum absolute temperature. The intensity of the factors was portrayed from North East to East and North West to South East. In the cluster analysis, three climatic zones were obtained.

Keywords

• factor analysis
• cluster analysis
• component
• rotation