Tuesday, 11 September 2007: 11:00 AM
Toucan (Catamaran Resort Hotel)
William Coirier, CFD Research Corporation, Huntsville, AL; and S. Kim, S. Marella, J. Mayes, F. Chen, J. Michalakes, M. Bettencourt, and S. Miao
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In this paper we present progress towards a coupled Mesoscale-to-Microscale modeling capability for the urban regime in which we loosely couple the Weather Research and Forecasting (WRF) model to a high-resolution Computational Fluid Dynamics model using the Model Coupling Environmental Library (MCEL). The client/server, dataflow software model of MCEL provides the data transfer and data filter capability that both models may use to perform both upscale (CFD to WRF) and downscale (WRF to CFD) data transfer. Potential benefits of this coupling include improved high-resolution wind, turbulence and contaminant fields in the urban area through the use of downscaled data, as well as potential improvements at the mesoscale by using an improved urban characterization through upscaled data. Previous studies [Coirier, et al., 2006] have shown a quantifiably improved accuracy of urban area transport and dispersion modeling by the use of a file-based coupling to downscale data from WRF to a high-resolution CFD model. The work being undertaken here will provide a more useful capability by coupling the models loosely in the MCEL environment, whereupon we may evaluate the potential improvements at both scales, as well as evaluate different techniques to perform the upscale and downscale data.
In order to achieve this coupled capability, modifications to both WRF and the MCEL library are being made, and a new CFD, special-purpose model is being developed to be run within this coupled environment. In this paper we outline the coupling approach using the MCEL library and describe the integration of WRF into this environment. The new, high-resolution urban CFD model being developed for this study is described in detail, and model validation study results using the new model are shown. This CFD model is designed to be run in a parallel computing environment using the PETSc parallel sparse matrix library, and solves the low-Mach number preconditioned, Reynolds-Averaged Navier-Stokes (RANS) equations using a Finite-Volume scheme. Details behind the numerics and overall approach are shown. In the final coupling, downscaled data obtained from WRF through the MCEL filters will be used to apply boundary conditions for the CFD model, which then cycles to a new, quasi-steady state, upon which it performs an upscale data transfer through MCEL. We show results of testing the downscaling capability using WRF computations corresponding to a particular Intensive Operating Period (IOP) of the Joint Urban 2003 (JU2003) field test conducted in Oklahoma City and present progress towards to coupled model capability.
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