Abstract
AbstractNewtonian relaxation applied at boundaries of RCM (regional climate model) is a widely‐used technique for climate downscaling and regional weather forecasting. It allows RCM to be nested into GCM (global climate model) and to follow the evolution of the latter. An idealized framework to mimic this general practice is constructed with the LMDZ (Laboratoire de Météorologie Dynamique, Zoom) modelling platform and used to assess effects of the relaxation procedure. The assessment is on both synoptic variability and long‐term mean. LMDZ is a global atmospheric general circulation model that can be configured as a regional model when the outside domain is relaxed to a driver. It thus plays the role of both GCM and RCM. Same physical parameterization and identical dynamical configuration are used to ensure a rigorous comparison between the two models. The experimental set‐up that can be referred to as “Master (GCM) versus Slave (RCM)” considers GCM as the reference to assess the behaviour of RCM. In terms of mean climate, there are noticeable differences, not only in the border areas, but also within the domain. In terms of synoptic variability, there is a general spatial resemblance and temporal concomitance between the two models. But there is a dependence on variables, seasons, spatiotemporal scales and spatial modes of atmospheric circulation. Winter/Summer has the most/least resemblance between RCM and GCM. A better similarity occurs when atmospheric circulation manifests at large scales. Weak‐correlation cases are generally remarked when the dominant circulation of the region is at smaller scales. A further experiment with identical framework but RCM in a higher resolution allows isolating the effect of relaxation from that of mesh refinement.
Highlights
Global Climate Models (GCMs) are the most advanced tools available to study climate variation at global scale
The fact that regional climate model (RCM) deviation is dependent on seasons is certainly a revelation that the basic climate matters for RCM to reproduce the mean climate of GCM
5 Conclusion This paper was devoted to the investigation of effects of a largely-used climate downscaling procedure which uses a Newtonian relaxation in order to drive RCM with outputs from GCM
Summary
Global Climate Models (GCMs) are the most advanced tools available to study climate variation at global scale. They generally have a too-coarse spatial resolution (about hundreds of kilometers) to appropriately investigate regional climate. Climate downscaling in the so-called dynamical approach is generally carried out with a physically-based regional climate model (RCM). RCM can be driven by various driving models or datasets such as meteorological reanalyzes, GCMs and other RCMs. RCM generally provides improved climate simulations, especially with respect to statistical properties of extremes, such as cyclones, intense precipitation and strong winds (Giorgi and Mearns, 1991). Improvements can come from regionally specific empirical adjustments of the model parameterizations
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