Detection Climate Change using Multivariable Statistical Analysis in west of Iran


The aim of this paper is detection of exist of significance climatic trend in west-half of Iran. It’s used monthly data of 16 climatic variables on 12 selected synoptic stations in period of 50 years statistic(1951-2000). The variables divided to two temperature and humid groups. The analysis methodology of the study is based on multivariable statistical analysis and Box- Jenkins forecasting models.
The results show the temperature variables such as average minimum temperature, absolute minimum temperature and dew point temperature had significant trend with different direction. Some stations such as Esfahan, Tehran, Bushehr, and Tabriz, had positive significant trend and in some stations such as Uremia, Hamadan, Khorram-abad there were negative significant trend. We didn’t find any significant trend in moisture and precipitation variables(humid group).