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Following the extensive conclusions from the IPCC (Intergovernmental Panel on Climate Change) Fourth Assessment Report and other reports (including INPEs report 2007 – ww.cptec.inpe.br/mudancas_climaticas) we have credible evidence that the climate is changing across the world. But it is important to note that while the current versions of atmosphereocean general circulation models (AOGCMs) have the ability to simulate well the state of the global climate at the large and continental scales, there are significant variations between these models in future climate projections of precipitation and temperature changes at the regional scale, including those for South America. One of the top priorities for narrowing gaps between current knowledge and policymaking needs is the quantitative assessment of the sensitivity, adaptive capacity and vulnerability of human and natural systems to climate change. Vital for such assessments are reliable estimates of current and future climate variability at the regional scale which can be readily used to assess the sensitivity of these systems to climate change. Often an important requirement for these assessments is for the climate data to be provided at high spatial and temporal resolution, and the main method for providing these data regionally is dynamical downscaling, i.e. output from global climate models is used to drive a high resolution regional climate model. Regional models 1provide improved spatial detail, but in order to improve reliability of projections, it is essential to run multiple realizations, to take uncertainties into account. There has been much effort to quantify the range of uncertainties that are known to exist in global climate model projections and dynamical downscaling allows a detailed exploration of these. Important for the interpretation of any downscaled projections is to assess the regional-scale climate and climate changes in the global projections. This can guide the selection of suitable global models for driving the regional model where the quality of global model control simulations and the identification of global model large-scale projected changes which are considered reliable would be relevant information. As a starting point for this, in the present paper, we present the results of an ensemble simulation of the HadCM3 climate model, where each ensemble member incorporates different but plausible versions of the parameterizations of important physical processes. This is used to assess the potential impacts of climate change on precipitation and temperature over South America and explore the range in projections obtained via the modifications to the model parameterizations.