The variable-resolution stretched-grid (SG) GCMs have been developed and successfully tested in the straightforward simulation mode (like that used for a typical atmospheric GCM) during the mid-late 90s. The SG-GCMs are the variable-resolution versions of the basic GCMs of the following four major meteorological centers/groups: the Meteo-France, ARPEGE model, the RPN/Canadian Meteorological Centre, GEM model, the Australian CSIRO C-CAM model, and the U.S. NASA/GSFC GEOS model. The regional climate simulation results obtained with the SG-GCMs have shown the maturity of the SG-approach. There is a consensus among the groups involved in the SG-GCM developments on the necessity of the model intercomparison at this stage of experimentation with the models. The intercomparison is focused on addressing the following major scientific and computational issues: stretching strategies; approximations of model dynamics; treatment of model physics including its calculation on intermediate uniform resolution or directly on stretched grids; multi-model ensemble calculations; optimal performance on parallel supercomputers.
The total number of global grid points for the SG-GCMs is (or close to) that of the 1º x 1º uniform grid. The area of interest is (or close to) the major part of North America: 20º – 60º N and 130º – 60º W. The regional resolution is about 0.5º. The surface boundary forcing (SST and sea ice) is used at 2º x 2.5º or 1º x 1º resolution. The 12-year period chosen for model simulations includes the recent ENSO cycles.
The existing reanalysis data as well as independent data like high resolution gauge precipitation and high resolution satellite data, are used for the SG-GCMs validation.
The 12-year SG-GCM simulations are analyzed in terms of studying: the impact of resolution on efficient/realistic downscaling to mesoscales; ENSO related and other anomalous regional climate events (floods, droughts, etc.) and major monsoonal circulations at mesoscale resolution; water and energy cycles; the impact of surface boundary forcing.
Analyzing multi-model ensemble integrations is one of the focal points of SGMIP.
The experience obtained will allow us to make a meaningful connection to AMIP-2 with a better understanding what could be contributed to regional climate studies.
Our joint SGMIP effort, focused on a better understanding of the SG-approach, is beneficial to all the participants as well as to a broader regional (and eventually global) climate modeling community.
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