Regional climate information is increasingly being demanded by vulnerability, impact and adaptation (VIA) research communities. This information is required to feed impact models for specific sectors (health, energy, food availability, risk management, water resources) and for decision-making processes at different levels. Different global and regional climate change projections for the 21st century have been produced over the last decades using both dynamical regional climate models (RCMs) and statistical downscaling methods (SDMs) in a series of international and national initiatives. As a result, large ensembles of future global (e.g. CMIP3, CMIP5) and regional (e.g. ENSEMBLES, CORDEX) climate projections are available, sampling most of the uncertainties affecting climate change. Nowadays, users are confronted with the technical and ethical (distillation) dilemma of deciding which information out of the large amount of available data is best suited for their application.
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