Evaluating RCM Added Value in Climate Change Projections

When a regional climate model is used to investigate and understand an issue related to climate change, in principle, an understanding of that issue will already be available from the global GCM simulations that provided the RCM driving data. From this perspective, the downscaling exercise is essentially one of adding understanding, or value, to an existing GCM result and so, it would seem sensible that statements regarding the value added by RCM downscaling be put into the context of the driving GCM's results. While such added value is central to the downscaling exercise, its evaluation is an intrinsically difficult undertaking for a variety of reasons - not least of which is the lack of a consensus on how added value should be defined. Irrespective of the definition of added value, however, progress can still be made on this issue. In the present study, we develop a methodology for an appreciable difference analysis of the climate change results in RCMs relative to their driving GCMs.  Since added value can only exist where appreciable differences occur in the climate change results of the global and regional models, the present approach provides a useful tool to direct attention to areas where added value potentially exist and conversely rule out areas where it does not.  The approach is illustrated on an ensemble of CMIP5 climate change experiments using the Canadian Earth-system model CanESM2 and its downscaled counterpart CanRCM4.