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More widely used geostatistical methods for modeling distributed phenomena requires the evaluation of the quality of the product (maps) obtained by their application. The method of evaluation of uncertainty i.e. quality of the map was described on the example of a map of mean annual air temperature in Serbia for the period from the years 1991 to 2009 that was obtained from a relatively small number of samples for the whole country area (110 meteorological stations). The uncertainty of the map, obtained by kriging interpolation was evaluated by applying a Monte Carlo simulation modeling method. [Projekat Ministarstva nauke Republike Srbije, br. III47014, br. III43007 i br. TR 36009]

The appearence of geostatistics and geographical information systems has made it possible to analyze complex spatial patterns of meteorological elements over large areas in the applied climatology. The objective of this study is to use geostatistics to characterize the spatial structure and map the spatial variation of average values of precipitation for a 30-year period in Serbia. New, recently introduced, geostatistical algorithms facilitate utilization of auxiliary variables especially remote sensing data or freely available global datasets. The data from Advanced Spaceborn Thermal Emission and Reflection Radiometer global digital elevation model are incorporated as ancillary variables into spatial prediction of average annual precipitation using geostatistical method known as regression kriging. The R value of 0.842 proves high performance result of the prediction of the proposed method. [ABSTRACT FROM AUTHOR]