Spatial analysis of bioclimatic patterns over Iranian cities as an important step in sustainable development

The main objective of this paper is to classify bioclimatic regions in Iran for optimal environmental planning. Mean daily meteorological data of 155 well-distributed synoptic stations during 1995-2017 were extracted from Iran's Meteorological Organization. Percentage of occurrence of each thermal sensation classes was determined over all studied stations using five bioclimatic indices including Perceived Temperature (PT), Physiological Equivalent Temperature (PET), Predicted Mean Vote (PMV), Standard Effective Temperature (SET) and Universal Thermal Climate Index (UTCI). An R-mode Principal Component Analysis (PCA) was applied to a N x M (155 x 40) matrix of N = 155 stations and M = 40 total thermal thresholds based on all used indices during the considered time period. According to the results of PCA, the five loading PCs that approximately account for 98.5% of the total variance were selected for further analysis. In addition, Ward method was used for Cluster Analysis (CA) to divide the stations into different bioclimatic groups. The results illustrated that the first Varimax-rotated loading pattern which accounts for 51.82% of total variance characterized Northwest of Iran with more than 0.8 PC scores. Furthermore, cluster analysis demonstrated that Iran can be divided into five bioclimatic regions based on the R-mode PCA.