Production of climatic and bioclimatic maps by Universal Kriging with external drift: theory and examples for Italy

In this paper GIS-based maps of climatic and bioclimatic data for Italy have been obtained by interpolating values observed at measurement stations. Long-term (1961-1990) average monthly data were obtained from weather stations measuring precipitation (1102 sites) and temperature (321 sites). We analysed twelve climatic variables (temperature and precipitation) and nine bioclimatic indexes. Terrain variables and geographical location have been used as predictors of climate variables: longitude, latitude, elevation, aspect, slope, continentality and estimated solar radiation. Universal kriging (i.e., simple kriging with trend function defined on the basis of a set of covariates), which is optimal (i.e., BLUP, best linear unbiased predictor) if spatial association is present, has been used as spatial interpolator. Based on the root mean square errors from cross-validation tests, we ranked the best search radius for each variable data set. A 15 km search radius has been demonstrated to be the best one to model precipitation variables and precipitation-based bioclimatic indexes, while temperature variables were modelled using a 30 km radius.