Evaluating the performance of a computationally efficient MM5/CALMET system for developing wind field inputs to air quality models

The present study investigates the usefulness of coupling the prognostic MM5 mesoscale model with the CALMET diagnostic model for producing high resolution wind fields in a computationally efficient manner. Wind fields derived from this system are compared with the wind profiler observations from the Northeast-Oxidant and Particle Study (NE-OPS) field campaign over Philadelphia, PA undertaken during one of the summer ozone episodes in 1999 (23-24 July 1999). The MM5 simulations were performed on a nested grid (36, 12 and 4km horizontal resolution) with 14 layers in the vertical direction for the period 21 July 1999; 00 UTC to 25 July 1999; 05 UTC. The CALMET meteorological model was applied with 14 layers in the vertical direction, a horizontal resolution of 4 km and a domain which includes New Jersey and the Philadelphia region and was employed in two modes. In the first mode, the MM5 model wind and mixing ratio output results (for 36, 12 and 4 km horizontal resolution) are ingested every hour into the CALMET diagnostic meteorological model along with an objective analysis procedure using all available observations. In the second mode, no MM5 results were utilized and CALMET employed the objective analysis procedure. All the above simulations are compared with the wind profiler data collected during the NE-OPS program. The results of this study indicate that utilizing the coarsest prognostic meteorological model output in a diagnostic model provides an attractive option for generating accurate meteorological inputs for air quality modeling studies, especially for long-term simulations of periods lasting from several weeks to a year. While the mean relative errors for the meridional component of velocity decreased significantly when the CALMET model was operated in the first mode, there was no corresponding significant decrease in the relative errors for the zonal component of velocity in the above mode. (C) 2003 Elsevier Science Ltd. All rights reserved.