The ability of four regional climate models to reproduce the present-day South American climate is examined with emphasis on La Plata Basin. Models were integrated for the period 1991-2000 with initial and lateral boundary conditions from ERA-40 Reanalysis. The ensemble sea level pressure, maximum and minimum temperatures and precipitation are evaluated in terms of seasonal means and extreme indices based on a percentile approach. Dispersion among the individual models and uncertainties when comparing the ensemble mean with different climatologies are also discussed. The ensemble mean is warmer than the observations in South Eastern South America (SESA), especially for minimum winter temperatures with errors increasing in magnitude towards the tails of the distributions. The ensemble mean reproduces the broad spatial pattern of precipitation, but overestimates the convective precipitation in the tropics and the orographic precipitation along the Andes and over the Brazilian Highlands, and underestimates the precipitation near the monsoon core region. The models overestimate the number of wet days and underestimate the daily intensity of rainfall for both seasons suggesting a premature triggering of convection. The skill of models to simulate the intensity of convective precipitation in summer in SESA and the variability associated with heavy precipitation events (the upper quartile daily precipitation) is far from satisfactory. Owing to the sparseness of the observing network, ensemble and observations uncertainties in seasonal means are comparable for some regions and seasons. © 2012 Springer-Verlag Berlin Heidelberg

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A new set of CORDEX simulations over South America, together with their coarserresolution driving Global Climate Models (GCMs) are used to investigate added value of Regional Climate Models (RCMs) in reproducing mean climate conditions over the continent. There are two types of simulations with different lateral boundary conditions: five hindcast simulations use re-analysis as boundary conditions, and five other historical simulations use GCMs outputs. Multi-model ensemble means and individual simulations are evaluated against two or three observation-based gridded datasets for 2-meter surface air temperature and total precipitation. The analysis is performed for summer and winter, over a common period from 1990 to 2004. Results indicate that added value of RCMs is dependent on driving fields, surface properties of the area, season and variable considered. A robust added value for RCMs driven by ERA-Interim is obtained in reproducing the summer climatology of surface air temperature over tropical and subtropical latitudes. Mixed results can be seen, however, for summer precipitation climatology in both hindcast and historical experiments. For winter, there is no noticeable improvement by the RCMs for the large-scale precipitation and surface air temperature climatology. To further understand the added value of RCMs, models deviations from observation are decomposed according to different terms that reflect the observational uncertainty, the representativeness error, the interpolation error, and the actual performance of the model. Regions where these errors are