The term downscaling denotes a procedure in which local climatic informat ion is derived from large-scale climate parameters. In this paper, we explore th e possibility to use as downscaling procedure a geostatistical interpolation tec hnique known as kriging. We present an example of the method by trying to reconstruct monthly winter precipitation in the Iberian peninsula from the Nor th Atlantic Sea Level Pressure (SLP) field in wintertime (December, January and February). The main idea consists in reducing the spatial dimension of the large-scale SLP field by means of Empirical Orthogonal Function Analysis (EOF). Each observed SL P field is represented by a point in this low-dimensional space and this point i s associated to the simultaneously observed rainfall. New values of the SLP field, for instance simulated by a General Circulation Mod el (GCM) with modified greenhouse gas concentrations, can be represented by a ne w point in the EOF space. The rainfall amount to be associated to this new point is estimated by kriging interpolation in the EOF-space. The results obtained by this geostatistical approach are compared to the ones ob tained by a simpler analog method, by trying to reconstruct the observed rainfal l from the SLP field in an independent period. It has been found that generally kriging and the analog method reproduce realistically the long-term mean, that kriging is somewhat better than the analog method in reproducing the rainfall e volution, but that, contrary to the analog method, underestimates the variance b ecause of the well-known smoothing effect. It is argued that there exists an intrinsic dichotomy between the estimation of the mean and replication of the variability. Finally both methods have been also applied to daily winter rainfall. The method s are also validated by downscaling winter precipitation from SLP. It is conclud ed that kriging yields a better estimation of daily rainfall than the analog met hod, but the latter reproduces better the probability distribution of rainfall a mounts and of the length of dry periods.