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Downscaling extreme month-long anomalies in southern South America |
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| Authors: | C G Menéndez M de Castro J-P Boulanger A D’Onofrio E Sanchez A A Sörensson J Blazquez A Elizalde D Jacob H Le Treut Z X Li M N Núñez N Pessacg S Pfeiffer M Rojas A Rolla P Samuelsson S A Solman C Teichmann |
| Institution: | 1. Centro de Investigaciones del Mar y la Atmósfera, CONICET-UBA, Pabellón 2, Piso 2, Ciudad Universitaria, 1428, Buenos Aires, Argentina 5. DCAO, FCEN, Universidad de Buenos Aires, Buenos Aires, Argentina 2. Facultad de Ciencias del Medio Ambiente, Universidad de Castilla-La Mancha, Toledo, Spain 3. Laboratoire d’Océanographie et du Climat, UMR CNRS/IRD/UPMC, Paris, France 4. DC, FCEN, Universidad de Buenos Aires, Buenos Aires, Argentina 6. Max Planck Institute for Meteorology, Hamburg, Germany 7. Laboratoire de Météorologie Dynamique, CNRS, Paris, France 8. Departamento de Geofísica, Universidad de Chile, Santiago, Chile 9. Rossby Centre, SMHI, Norrk?ping, Sweden |
| Abstract: | We investigate the performance of one stretched-grid atmospheric global model, five different regional climate models and a statistical downscaling technique in simulating 3 months (January 1971, November 1986, July 1996) characterized by anomalous climate conditions in the southern La Plata Basin. Models were driven by reanalysis (ERA-40). The analysis has emphasized on the simulation of the precipitation over land and has provided a quantification of the biases of and scatter between the different regional simulations. Most but not all dynamical models underpredict precipitation amounts in south eastern South America during the three periods. Results suggest that models have regime dependence, performing better for some conditions than others. The models’ ensemble and the statistical technique succeed in reproducing the overall observed frequency of daily precipitation for all periods. But most models tend to underestimate the frequency of dry days and overestimate the amount of light rainfall days. The number of events with strong or heavy precipitation tends to be under simulated by the models. |
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