The Use of Global and Mesoscale Meteorological Model Data to Predict the Transport and Dispersion of Tracer Plumes over Washington, D.C.

 

Roland R. Draxler

 

Weather and Forecasting, Vol 21, No. 3, pages 383-394, June 2006

                                                             

Abstract. The data from a yearlong tracer dispersion experiment over Washington, DC in 1984 were used to evaluate HYSPLIT dispersion model calculations using coarse global meteorological reanalysis data (NCEP/NCAR and ERA40) and calculations using meteorological data fields created by running a high-resolution meteorological model (MM5). None of the meteorological models were optimized for urban environments. The dispersion calculation using the ERA40 data showed better performance than those using the NCEP/NCAR data and comparable performance to those using MM5 data fields. Calculations with MM5 data that used shorter-period forecasts were superior to calculations that used forecast data that extended beyond 24 hours. Day-time dispersion model calculations using the MM5 data showed an under-prediction bias not evident in calculations using the ERA40 data or for night-time calculations using either meteorological data. It was found that small changes in the wind direction for all meteorological model data resulted in dramatic improvements in dispersion model performance. All meteorological data modeled plume directions were biased 10 to 20 degrees clockwise to the measured plume direction. This bias was greatest when using the global meteorological data. A detailed analysis of the wind observations during the November intensive, which had the greatest difference between the model and measured plume directions, showed that only the very lowest level observed winds could account for the transport direction of the measured plume. In the Northern Hemisphere, winds tend to turn clockwise with height resulting in positive directional transport bias if the lowest level winds are not represented in sufficient detail by the meteorological model.

 

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