Downscaling GCM Output with a Mesoscale Model

Policy makers, responsible for the economic well-being of regions and states, have sought a variety of tools for predicting global change. One set of tools for simulating climate change, at a global scale, are the general circulation models (GCMs). Current versions of GCMs are limited to global studies, which are spatially crude and have output that is of minimal use to decision-makers accustomed to day-to-day, synoptic-scale changes in weather events. This paper discusses the use of a mesoscale model to “downscale” GCM output to the regional and local scales desired by policy makers. It presents a “nested” dynamical modeling approach. The paper also addresses several issues associated with the dynamical linking of GCMs and mesoscale models. Issues having to do with the choice of an atmospheric system, a variable as the best indicator of climate change, or having to do with validation of mesoscale simulations, which were based on GCM output, are considered.