Considerations of Domain Size and Large-Scale Driving for Nested Regional Climate Models: Impact on Internal Variability and Ability at Developing Small-Scale Details
The premise of dynamical downscaling is that a high-resolution, nested Regional Climate Model (RCM), driven by large-scale atmospheric fields at its lateral boundary, generates fine scales that are dynamically consistent with the large scales. An RCM is hence expected to act as a kind of magnifying glass that will reveal details that could not be resolved on a coarse mesh. The small scales represent the main potential added value of a high-resolution RCM.
Several issues remain with respect to nested RCMs: are the large scales perfectly replicated, degraded or improved by an RCM? For a given set of lateral boundary conditions, is the course of an RCM simulation uniquely defined? Is lateral-boundary driving sufficient to control RCM simulations? What domain size and location should be used for a given application? Almost 20 years after the inception of RCMs, and despite recognition that RCMs’ results are sensitive to the choice of domain and driving technique, these questions have still not been fully answered.
A series of methodical investigations spread over the course of several years have been performed to address these issues in an unambiguous manner, following a strict experimental protocol: the Big-Brother Experiment. The results to date point to the advantage of using rather large domains that permit the full spin-up of small scales, acknowledging however that such configuration permits the intermittent occurrence of divergence in phase space and large internal variability in RCM simulations. Alternative driving techniques to the traditional imposition of lateral boundary conditions, which allow forcing the large scales throughout the domain, appear to offer definite advantages.
KeywordsRegional Climate Model Internal Variability Lateral Boundary Condition Dynamical Downscaling Weather Regime
The authors benefited greatly from constructive comments made by Dr Hans von Storch on an earlier paper (Laprise et al. 2008) that discussed related issues. This research was achieved as part of the scientific research programmes of the Canadian Regional Climate Modelling and Diagnostics Network (CRCMD; http://www.mrcc.uqam.ca/)—funded by the Canadian Foundation for Climate and Atmospheric Sciences (CFCAS; http://www.cfcas.org/) and the Ouranos Consortium on Regional Climatology and Adaptation to Climate Change (http://www.ouranos.ca/), as well as the Canadian Climate Variability Network (CLIVAR)—funded by CFCAS and the Natural Sciences and Engineering Research Council of Canada (NSERC; http://www.nserc-crsng.gc.ca/). The authors thank Georges Huard, Mourad Labassi, Abderrahim Khaled and Nadjet Labassi for maintaining an efficient and user-friendly local computing facility.
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