Abstract The exploitation of the renewable energy sources plays a key role for achieving the CO 2 emissions reduction targets established by the Kyoto Protocol, as well as for facing the shortage of world fossil fuels reserves. In countries like Italy, with an high potential in terms of wind power generation, an efficient energy planning based on renewables is a very complex task. It encompasses many aspects: the resource availability assessment, the compliance with environmental and legislative constraints and last, but not least, the technical aspects linked to the safe integration to the grid of the intermittent power generated by the wind farms. This paper is the first part of a study addressing the first of the aforementioned issues. The wind measurements recorded in several stations of Sicily (Italy) were used for the spatial modelling of the wind fields over the region. A statistical analysis of the wind data has allowed the estimation of the parameters of the wind probability distribution function, that is a Weibull, as predicted by theory. In the last sections of the paper the results of some traditional deterministic and geostatistical interpolation techniques are shown. In the companion paper the maps of the estimated wind fields have been obtained by using the results of the statistical investigation accomplished here and coupling neural and geostatistical techniques. For a comprehensive evaluation of the forecasting accuracy of this neural kriging approach, those maps have to be compared with the maps showed in this paper.