Avances en el pronóstico climático de las anomalías de lluvia en la Región Pampeana

atmospheric general circulation models (agcm) are able to simulate statistically significant climate anomalies of seasonal or larger time-scales, associated with anomalies in the sea surface temperature. agcms can effectively estimate the sign and probability of such climate anomalies whenever their extent is several times greater than the spatial resolution of the model. some progress attained in the estimation of rainfall anomalies in 22 sites of the pampa region, argentina, by means of statistical downscaling of the output from an agcm are presented in this work. downscaling models were based in the multiple lineal regression method. climatic anomalies of the atmospheric independent variables required in the rainfall downscaling procedure were obtained from the ensemble average of twenty simulations carried out with the agcm csiro-9, prescribing the sea surface temperature according to observed daily values in the period 1987-1998. the statistical downscaling of rainfall produced greater correlation with local observation than the agcm rainfall data interpolated over each location. the results of a principal component analysis applied to the observed and estimated data reveal that this downscaling approach is able to distinguish areas with different rainfall behavior within the study region.