Compare The Methods Used To Estimate The Maximum And Minimum Daily Temperatures Using Regression And Geostatistical (A Case Study: Chaharmahal Va Bakhtiari)

Due to the lack of meteorological stations in Iran and the importance of the element temperature daily temperature in all the planning, estimating air temperature is very important in areas without stations. In areas that have environmental implications that are more important. The aim of this study was to evaluate univariate methods (inverse distance weighted regression) and multivariate (logistic regression) to estimate minimum and maximum air temperature is in Chaharmahal and Bakhtiari Province.
Previous studies using a variable pattern (above sea level) in multivariate interpolation methods used in this research, in addition to elevation above sea level, the covariates (independent) was another. In this regard, the potential covariates in the regression model were eligible to enter, then qualified variables in multivariate regression were used.
Comparison of interpolation methods showed that three-variable regression (longitude, latitude and altitude) with the R2 =0/98 as the best method for interpolation of daily minimum and maximum air temperature is in Chaharmahal and Bakhtiari Province. Therefore, it is recommended for a more accurate estimation of the temperature of the variables used daily minimum and maximum.