An Examination of MM5 based Meteorological Data in Modeling a High-Ozone Episode
Jia-Yeong Ku1, Kurt Kebschull2, Jennifer Galbraith3, Mohamed Majeed4, Jennifer Desimone5,and Gopal Sistla1
Abstract
In the past decade increased reliance has been placed on the predictive ability of air quality simulation models (AQSM) in the development of emissions control policies for improving ambient air quality. Often these AQSMs are based upon historical meteorological events, and in recent years there has been an increased application of prognostic meteorological models such as MM5 and RAMS to develop the required meteorological inputs. Thus there is a need for careful assessment of the meteorological fields as they are responsible for the transport and dispersion of pollutants. Even though these prognostic meteorological models often employed four dimensional data assimilation (FDDA) techniques in their simulations, a 12 km horizontal grid resolution may not be sufficient to resolve the mesoscale features along the mid-Atlantic and New England coastal regions.
In this study, we evaluated MM5 simulations of a high ozone event for a period of 6 days in July 1997. This was part of an extended 46-day simulation period during the summer of 1997 over the eastern United States. We focused our evaluation on the comparison of meteorological measurements obtained along the mid-Atlantic and New England coastal regions with those obtained from the MM5 simulations. The results of this evaluation are based upon traditional statistical measures as well as on the spatial and temporal distributions of hourly temperature, wind speed and direction. The reasons for agreement and or disagreement are discussed.
1 New York State Department of Environmental Conservation, Albany, NY 12233
2.Connecticut Department of Environmental Protection, Hartford, CT, 06106
3.New Hampshire Department of Environmental Services, Concord, NH 03301
4.Delaware Department of Natural Resources, Dover, DE 19901
5.Maine Department of Environmental Protection, Augusta, ME 04333
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