Traditional classification approaches tend to classify climates in terms of one or a few climatic variables given the specific circumstances. However, climate incorporates wide varieties of variables and serves as a cumulative process. In the present research, the number of 197 climatic parameters were selected and evaluated drawing upon data from the Iranian Meteorological Organization at 164 selected stations during the period of 1981 to 2018. After accuracy verification (by statistics of reliable synoptic stations in the area), such parameters were applied to develop a database. Then, upon reviewing of the library documents while considering the effective climatic elements in the formation and distribution of vegetation in different regions of Iran, finally 137 climatic variables were identified, in turn used as input data to perform factor analysis in SPSS software. Such variables greatly affect the climate of each region, and in fact, are determinant factors of the climate in each area. Subsequently, cluster analysis was performed on climatic factors obtained from the factor analysis method. According to the results, throughout the Iran, nine factors of temperature, relative humidity, cold season rainfall, warm-season rainfall, wind speed, semi-cloudy days, thunderstorm and snowy day with eigenvalues greater than one were 29.71, 22.32, 9.58, 7.52, 6.22, 6.80, 4.25, 3.69, 2.22%, respectively and totally accounted for 92.35% of the variance the data. Cluster analysis was an important step in determining the number of homogeneous clusters in this study. For this, the wards method was applied. First, by GIS software, the whole of Iran was divided into two climatic zones, and the climatic factors separating Iran into two zones were identified. Then two areas were divided into three sub-areas and this was continued until the final stage and at each stage, the factors separating the climatic zones were identified. By the final stage, it means stage at which the number of suitable and final zones is obtained. Subsequently, we reached from the climatic zone of 25 to zone of 26, so that all suitable climate zones of Iran were obtained by cluster analysis. While we proceeded from the zoning phase of 26 to 27 and up, it had no effect on climate factors, and no factor was identified as a separating factor of climatic zones. Eventually, based on the multivariate statistical methods, 26 bio-climatic zones for Iran was obtained. Then, the overall vegetation map of Iran was networked by the kriging method and matched to the Iranian map of climatic zones. And exactly the dominant vegetation types were studied and introduced within each climatic zones. Finally, the results of the multivariate statistical method were compared with those of the traditional Pabout method and the weaknesses and strengths of the Pabout method and also multivariate statistical methods used in the bio-climatic zonation of Iran were investigated.
