تحليل ساختار دماي ماهانه ايران

A Spatial Analysis of Monthly Temperature in Iran

Detecting temporal and spatial structure of climatic variables may be considered as a basis for any genetic climatological study. In this paper we try to approach the spatial characteristics of monthly temperature in Iran using Geographic Information System (GIS) techniques such as densification and interpolation. Estimations produced by these techniques were used as an input to a multivariable regression model. These significant statistical models enable us to predict mean monthly temperature for any given point within Iran. In fact, such models may be used for sensitivity analysis. For instance, the models show that in Iran height of snowline is sensitive to mean annual temperature of the country by a factor of about 160 mm; in other words, one degree Celsius warming will result into 160 m upward migration of snowline.