A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 2: Gas Tracer Dispersion

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• 作者：Matthew A. Nelson ; Michael J. Brown ; Scot A. Halverson…
• 关键词：Quick Urban and Industrial Complex modelling system ; Transport and dispersion ; Weather Research and Forecasting model
• 刊名：Boundary-Layer Meteorology
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：161
• 期：3
• 页码：461-490
• 全文大小：7,231 KB
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Meteorology and Climatology
  Atmospheric Protection, Air Quality Control and Air Pollution
  
• 出版者：Springer Netherlands
• ISSN：1573-1472
• 卷排序：161

文摘

The Quick Urban & Industrial Complex (QUIC) atmospheric transport, and dispersion modelling, system was evaluated against the Joint Urban 2003 tracer-gas measurements. This was done using the wind and turbulence fields computed by the Weather Research and Forecasting (WRF) model. We compare the simulated and observed plume transport when using WRF-model-simulated wind fields, and local on-site wind measurements. Degradation of the WRF-model-based plume simulations was cased by errors in the simulated wind direction, and limitations in reproducing the small-scale wind-field variability. We explore two methods for importing turbulence from the WRF model simulations into the QUIC system. The first method uses parametrized turbulence profiles computed from WRF-model-computed boundary-layer similarity parameters; and the second method directly imports turbulent kinetic energy from the WRF model. Using the WRF model’s Mellor-Yamada-Janjic boundary-layer scheme, the parametrized turbulence profiles and the direct import of turbulent kinetic energy were found to overpredict and underpredict the observed turbulence quantities, respectively. Near-source building effects were found to propagate several km downwind. These building effects and the temporal/spatial variations in the observed wind field were often found to have a stronger influence over the lateral and vertical plume spread than the intensity of turbulence. Correcting the WRF model wind directions using a single observational location improved the performance of the WRF-model-based simulations, but using the spatially-varying flow fields generated from multiple observation profiles generally provided the best performance.