CONICET | Buscador de Institutos y Recursos Humanos

AbstractThis work aimsto identify those regions within the South American continent where theRegional Climate Models (RCMs) have the potential to add value compared totheir coarser-resolution global forcing. For this, we distinguished themesoscale climatic signal present in atmospheric surface fields from observeddata and 6 RCM simulations belonging to the CORDEX Project. We used aspatial-scale filtering method based on the wavelet theory and kept thosescales that can be explicitly simulated by the RCM and not by its driver. Oncethe longer wavelengths were filtered, we focused on analyzing the spatialvariability of extreme rainfall and the spatiotemporal variability of maximumand minimum surface air temperature on a daily basis. The results obtained suggestessential differences in the spatial distribution of the mesoscale signal ofextreme precipitation between TRMM and regional models, together with a largedispersion between models. While TRMM registers a large signal throughout thecontinent, the RCMs place it over regions with complex topography or areaswhere convective systems dominate. Surface air temperature has a largemesoscale stationary component over regions characterized by complextopography, such as the Andes Cordillera and the Brazilian Highlands, and thecoasts of the continent. The transient part is much smaller than the stationaryone, except over la Plata Basin where they are of the same order of magnitude.Also, the RCMs and CRU showed a large spread between them in representing this variability.The results confirm that RCMs have the potential to add value in therepresentation of extreme precipitation and the mean surface temperature inSouth America. However, this condition is not applicable throughout the wholecontinent but is particularly relevant in those terrestrial regions where thesurface forcing is strong, such as the Andes Cordillera or the coasts of thecontinent.