Estimation of precipitation by kriging in the EOF space of the sea level pressure field

The term downscaling denotes a procedure in which local climatic informatio n is derived from large-scale climate parameters. In this paper, the possib ility of using as downscaling procedure a geostatistical interpolation tech nique known as kriging is explored. The authors present an example of the m ethod by trying to reconstruct monthly winter precipitation in the Iberian Peninsula from the North Atlantic sea level pressure (SLP) field in wintert ime (December-February). The main idea consists in reducing the spatial dimension of the large-scale SLP field by means of empirical orthogonal function (EOF) analysis. Each o bserved SLP field is represented by a point in this low-dimensional space a nd this point is associated with the simultaneously observed rainfall. New values of the SLP field, for instance, those simulated by a general circula tion model with modified greenhouse gas concentrations, can be represented by a new point in the EOF space. The rainfall amount to be associated to th is point is estimated by kriging interpolation in the EOF space. The results obtained by this geostatistical approach are compared to the on es obtained by a simpler analog method by trying to reconstruct the observe d rainfall from the SLP field in an independent period. It has been found t hat, generally, kriging and the analog method reproduce realistically the l ong-term mean, that kriging is somewhat better than the analog method in re producing the rainfall evolution, but that,contrary to the analog method, i t underestimates the variance because of the well-known smoothing effect. I t is argued that there exists an intrinsic incompatibility between the esti mation of the mean and replication of the variability. Finally, both methods have been also applied to daily winter rainfall. The methods are also validated by downscaling winter precipitation from SLP. It is concluded that kriging yields a better estimation of daily rainfall tha n the analog method, but the latter better reproduces the probability distr ibution of rainfall amounts and of the length of dry periods.