M.Sc. Tezi Görüntüleme

      In this study, 9 spatial interpolation methods were applied to daily mean temperature datafrom 1981 to 2012 of 52 meteorological stations located in Blacksea region. In the study, 5 non geostatistical methods were used. Two of them are Inverse Distance Method IDW using Original Shaperd and Modified Shaperd derived weights. Within Lapse Rate Method as a third method in this study, daily lapse rates were calculated. The last two methods applied as Simple Linear Regression Model and Multiple Linear Regression Model. The simple linear regresion model focused on the relationship between a dependent variable as temperature and one independent variable as point elevation. On the other hand, multiple regression model concentrated on relationship between a dependent variable as temperature and three independent variable as point longitude, latitude and elevation. Hypothesis tests were conducted to determine whether there is a significant linear relationship between an independent variable s and a dependent variable. Three methods as Combined Simple Linear Regression and IDW, Combined Multiple Linear Regression and IDW and Combined Lapse Rate and IDW were performed as combined methods. Ordinary Kriging were as geostatistical methods were performed the 9. Method. In order to determine how interpolation results differ due to seasons, positions of either inperpolation point s or fixed points, different error criteria were used. The results were compared by looking at monhtly minimum and maximum error, mean square error MSQ, absolute mean error AME of which are calculated out of differences between real value and interpolation value.