One-Way Coupling of the WRF–QUIC Urban Dispersion Modeling System

A. K. Kochanski Department of Atmospheric Sciences, University of Utah, Salt Lake City, Utah

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E. R. Pardyjak Department of Mechanical Engineering, University of Utah, Salt Lake City, Utah

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R. Stoll Department of Mechanical Engineering, University of Utah, Salt Lake City, Utah

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A. Gowardhan Lawrence Livermore National Laboratory, Livermore, California

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M. J. Brown Los Alamos National Laboratory, Los Alamos, New Mexico

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W. J. Steenburgh Department of Atmospheric Sciences, University of Utah, Salt Lake City, Utah

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Abstract

Simulations of local weather and air quality in urban areas must account for processes spanning from meso- to microscales, including turbulence and transport within the urban canopy layer. Here, the authors investigate the performance of the building-resolving Quick Urban Industrial Complex (QUIC) Dispersion Modeling System driven with mean wind profiles from the mesoscale Weather Research and Forecasting (WRF) Model. Dispersion simulations are performed for intensive observation periods 2 and 8 of the Joint Urban 2003 field experiment conducted in Oklahoma City, Oklahoma, using an ensemble of expert-derived wind profiles from observational data as well as profiles derived from WRF runs. The results suggest that WRF can be used successfully as a source of inflow boundary conditions for urban simulations, without the collection and processing of intensive field observations needed to produce expert-derived wind profiles. Detailed statistical analysis of tracer concentration fields suggests that, for the purpose of the urban dispersion, WRF simulations provide wind forcing as good as individual or ensemble expert-derived profiles. Despite problems capturing the strength and the elevation of the Great Plains low-level jet, the WRF-simulated near-surface wind speed and direction were close to observations, thus assuring realistic forcing for urban dispersion estimates. Tests performed with multilayer and bulk urban parameterizations embedded in WRF did not provide any conclusive evidence of the superiority of one scheme over the other, although the dispersion simulations driven by the latter showed slightly better results.

Corresponding author address: E. R. Pardyjak, Department of Mechanical Engineering, University of Utah, 1495 East 100 South, 1550 MEK, Salt Lake City, UT 84112. E-mail: pardyjak@eng.utah.edu

Abstract

Simulations of local weather and air quality in urban areas must account for processes spanning from meso- to microscales, including turbulence and transport within the urban canopy layer. Here, the authors investigate the performance of the building-resolving Quick Urban Industrial Complex (QUIC) Dispersion Modeling System driven with mean wind profiles from the mesoscale Weather Research and Forecasting (WRF) Model. Dispersion simulations are performed for intensive observation periods 2 and 8 of the Joint Urban 2003 field experiment conducted in Oklahoma City, Oklahoma, using an ensemble of expert-derived wind profiles from observational data as well as profiles derived from WRF runs. The results suggest that WRF can be used successfully as a source of inflow boundary conditions for urban simulations, without the collection and processing of intensive field observations needed to produce expert-derived wind profiles. Detailed statistical analysis of tracer concentration fields suggests that, for the purpose of the urban dispersion, WRF simulations provide wind forcing as good as individual or ensemble expert-derived profiles. Despite problems capturing the strength and the elevation of the Great Plains low-level jet, the WRF-simulated near-surface wind speed and direction were close to observations, thus assuring realistic forcing for urban dispersion estimates. Tests performed with multilayer and bulk urban parameterizations embedded in WRF did not provide any conclusive evidence of the superiority of one scheme over the other, although the dispersion simulations driven by the latter showed slightly better results.

Corresponding author address: E. R. Pardyjak, Department of Mechanical Engineering, University of Utah, 1495 East 100 South, 1550 MEK, Salt Lake City, UT 84112. E-mail: pardyjak@eng.utah.edu
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