a cluster analysis of thermal seasons of iran

the main objective of this study was to investigate how months cluster in any thermal regions based on temperature. for this purpose, the mean of daily temperature data have been provided using 620 synoptic and climatology stations. then, mean temperature was converted for any station, based on solar calendar, and maps of mean daily temperature have been interpolated using kriging method. spatial resolution of these maps was 18*18km. so that 5214 pixels covered the country and temporal and spatial behavior of mean temperature could be represented by a 5214*366 matrix. an agglomerative hierarchical cluster analysis with ward's linkage applied on this matrix and six different thermal regions were detected. in creating thermal regions topography spatial configuration and latitude have been involved. for diagnosing thermal seasons in iran, mean matrix of monthly temperature was calculated. a repeated agglomerative hierarchical cluster analysis applied on data of transpose matrix showed that there were three thermal seasons cold, moderate and warm with four months in iran, which was similar in all six thermal regions. recognition of thermal seasons is important for energy consumption and tourism timing management.