Comparison of Different Interpolation Techniques for Modelling Temperatures in Middle Black Sea Region
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Objective of this study was to determine the best method for modelling and mapping monthly and annual temperatures (minimum, maximum, mean) of Middle Black Sea Region by geographical information systems (GIS). Data from 72 different meteorological observation stations were used for modelling and mapping. Inverse Distance Weighting (IDW), Thin-plate Smoothing Spline (TPS), Simple Kriging (SK), Cokriging (CK) and Multiple Linear Regression (MLR) methods were used to analyze spatial distribution of temperature data. Correlation coefficients among the estimated and measured monthly mean temperatures varied between 0.80 and 0.95. Correlation coefficients for all months were found to be significant (P < 0.01). In general, MLR yielded the best results for monthly mean temperatures. While TPS was identified as the best method for monthly minimum temperatures for most of the months, MLR, IDW, and CK methods yielded best results for other months. All methods yielded unsatisfactory results for maximum temperatures, especially for summer months.