Numerical Prediction of Cold Season Fog Events over Complex Terrain: the Performance of the WRF Model During MATERHORN-Fog and Early Evaluation

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• 作者：Zhaoxia Pu ; Catherine N. Chachere ; Sebastian W. Hoch…
• 关键词：Fog ; numerical prediction ; WRF model ; MATERHORN ; boundary layer
• 刊名：Pure and Applied Geophysics
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：173
• 期：9
• 页码：3165-3186
• 全文大小：19,615 KB
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Geophysics and Geodesy
  
• 出版者：Birkh盲user Basel
• ISSN：1420-9136
• 卷排序：173

文摘

A field campaign to study cold season fog in complex terrain was conducted as a component of the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program from 07 January to 01 February 2015 in Salt Lake City and Heber City, Utah, United States. To support the field campaign, an advanced research version of the Weather Research and Forecasting (WRF) model was used to produce real-time forecasts and model evaluation. This paper summarizes the model performance and preliminary evaluation of the model against the observations. Results indicate that accurately forecasting fog is challenging for the WRF model, which produces large errors in the near-surface variables, such as relative humidity, temperature, and wind fields in the model forecasts. Specifically, compared with observations, the WRF model overpredicted fog events with extended duration in Salt Lake City because it produced higher moisture, lower wind speeds, and colder temperatures near the surface. In contrast, the WRF model missed all fog events in Heber City, as it reproduced lower moisture, higher wind speeds, and warmer temperatures against observations at the near-surface level. The inability of the model to produce proper levels of near-surface atmospheric conditions under fog conditions reflects uncertainties in model physical parameterizations, such as the surface layer, boundary layer, and microphysical schemes.