CONICET | Buscador de Institutos y Recursos Humanos

La Plata Basin spreads over 3200000 square km and is one of the most important agriculture and hydropower producing regions worldwide. In this region, extreme rainfall situations often occur, sometimes persistent and with a significant socio-economic impact. Empirical downscaling is a widely used technique for exploring the regional and local-scale response to large-scale circulation. In this study, the chosen method for downscaling precipitation is a two step statistical method based on the identification of analogues. In order to estimate daily precipitation in La Plata basin, six-hourly ERA 40 reanalysis dataset was used. Series of daily rainfall of stations within the target area were used as predictants. Both reference (surface and atmospheric) datasets expand over the period 1960-2000 (14.974 days). In the first step, the analogue technique was used in order to select the n most similar days to each day. The second step involves the estimation of daily rainfall. Rainfall distributions, considering the n analogues and their weights were built for each day in order to estimate rainfall occurrence and extreme precipitation values. The results show the great potentialities of the method, that is able to diagnose daily precipitation with a high level of accuracy and that would also be competitive in an operative forecasting framework. The performance of the method is also very good at estimating distribution parameters (mean and standard deviation values), seasonal cycles and temporal variability. Validation results show that the downscaling performance is good enough to allow its confident application over General Circulation Model outputs, in order to prospect possible climate evolution.

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