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To provide long-term simulations of climate change at higher resolution, Regional Climate Models (RCMs) are nested in global climate models (GCMs). The objective of this work is to evaluate the Eta RCM simulations driven by three global models, the HadGEM2-ES, BESM, and MIROC5, for the present period, 1961-1990. The RCM domain covers South America, Central America, and Caribbean. These simulations will be used for assessment of climate change projections in the region. 439Eta Model

of uncertainty, compared with that due to the choice of the driving model and the RCM. Moreover, the level of uncertainty is larger for longer horizon projections for both temperature and precipitation. The uncertainty in the temperature changes is larger for the subtropical than for the tropical ones. The current analysis allows identification of the common climate change signals and their associated uncertainties for several subregions within the South American continent.

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The performance of seven regional climate models in simulating the radiation and heat fluxes at the surface over South America (SA) is evaluated. Sources of uncertainty and errors are identified. All simulations have been performed in the context of the CLARIS-LPB Project for the period 1990–2008 and are compared with the GEWEX-SRB, CRU, and GLDAS2 dataset and NCEP-NOAA reanalysis. Results showed that most of the models overestimate the net surface short-wave radiation over tropical SA and La Plata Basin and underestimate it over oceanic regions. Errors in the short-wave radiation are mainly associated with uncertainties in the representation of surface albedo and cloud fraction. For the net surface long-wave radiation, model biases are diverse. However, the ensemble mean showed a good agreement with the GEWEX-SRB dataset due to the compensation of individual model biases. Errors in the net surface long-wave radiation can be explained, in a large proportion, by errors in cloud fraction. For some particular models, errors in temperature also contribute to errors in the net long-wave radiation. Analysis of the annual cycle of each component of the energy budget indicates that the RCMs reproduce generally well the main characteristics of the short- and long-wave radiations in terms of timing and amplitude. However, a large spread among models over tropical SA is apparent. The annual cycle of the sensible heat flux showed a strong overestimation in comparison with the reanalysis and GLDAS2 dataset. For the latent heat flux, strong differences between the reanalysis and GLDAS2 are calculated particularly over tropical S

The meteorological characteristics of the drought of 2005 in Amazonia, one of the most severe in the last 100 years were assessed using a suite of seven regional models obtained from the CLARIS LPB project. The models were forced with the ERA-Interim reanalyses as boundary conditions. We used a combination of rainfall and temperature observations and the low-level circulation and evaporation fields from the reanalyses to determine the climatic and meteorological characteristics of this particular drought. The models reproduce in some degree the observed annual cycle of precipitation and the geographical distribution of negative rainfall anomalies during the rainfall and temperature anomalies in DJF and MAM 2005 shows biases that are different among models. While some models simulated the observed negative rainfall anomalies over parts of western and southern Amazonia during DJF, others simulated positive rainfall departures over central Amazonia. The simulated circulation patterns indicate a weaker northeasterly flow from the tropical North Atlantic into Amazonia, and reduced flows from southern Amazonia into the La Plata basin in DJF, which is consistent with observations. In general, we can say that in some degree the regional models are able to capture the response to the forcing from the tropical Atlantic during the drought of 2005 in Amazonia. Moreover, extreme climatic conditions in response to anomalous low-level circulation features are also well captured, since the boundary conditions come from reanalysis and the models are largely constrained by the information provided at the boundaries. The analysis of the 2005 drought suggests that when the forcing leading to extreme anomalous conditions is associated with both local and non-local mechanisms (soil moisture feedbacks and remote SST anomalies, respectively) the models are not fully capable of representing these feedbacks and hence, the associated anomalies. The reason may be a deficient reproduction of the land-atmosphere interactions.

Regional Climate Models are important tools, which are increasingly being used in studies of impacts and adaptation to climate change at local scale. The goal of this work is to assess the climate change over the La Plata Basin, using the Eta Regional model with a resolution of 10 km.

Uno de los desafíos de la ciencia de los desastres es encontrar puntos de contacto entre las áreas de conocimiento –enfoque interdisciplinario– y ser transdisciplinario, esto es, involucrar actores no académicos en la creación y ejecución de la investigación científica, en la coproducción del conocimiento. La formulación de los sistemas de alerta centrados en la población es uno de los desafíos de investigación propuestos por las Naciones Unidas en el Marco de Sendai para la Reducción de Riesgo de Desastre 2015-2030. El objetivo de este trabajo es presentar aspectos teóricos y metodológicos interdisciplinarios para la formulación de sistemas comunitarios de alerta temprana asociados al riesgo de desastre por inundaciones y deslizamientos de tierra. A partir de una investigación bibliográfica y de investigación en terreno desde un abordaje cualitativo en Nova Friburgo, Rio de Janeiro, Brasil, compartimos algunos resultados de un taller sobre sistemas comunitarios de alerta. Los resultados destacan ciertas lagunas de conocimiento para el mejor entendimiento sobre lo que significa un sistema comunitario de alerta, los elementos del sistema, y como formular propuestas de implementación, entre otros.