Regional Climate Modelling: Probing the strengths and limitations of dynamical downscaling with nested models

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Several sectors of economy, environment and health are sensitive to weather vagaries, climate variations and anticipated changes. A technologically advanced society needs to use the best information to design a coping strategy to reduce vulnerability, based on a quantitative assessment of anticipated impacts. This requires accurate projections of future climate that are obtained with climate simulators issued from research in the physics of climate. Training and academic research in the Physics of climate are therefore the very foundation for climate impacts and adaptation studies. The objective of the proposed research programme is to further our understanding of the strengths and (specially) the limitations of dynamical downscaling with nested Regional Climate Models (RCMs). RCMs' projections need to be driven by boundary conditions (BC) from Global Climate Models (GCMs). But GCMs provide only imperfect large-scale information. The added value of RCMs is thus to resolve fine scales that are absent in GCMs. The limited area of an RCM implies that fine scales must develop entirely within the regional domain, with implications on the resolution jump from the GCM to the RCM and RCM domain size to allow proper spin up, while maintaining control of the RCM simulation. Carefully designed experiments, some following idealised approaches such as the "Big-Brother Experiment" I designed a few years ago and which is now used by several research centres around the world, and other experiments using more realistic and complex context, will be realised to estimate the limits of confidence and the potential and real added value of high-resolution RCM simulations and projections on regional processes.