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Mesoscale meteorological models are being used to provide inputs of winds, vertical temperature and stability structure, mixing depths, and other parameters to atmospheric transport and dispersion models. An evaluation methodology is suggested and tested with simulations available from four mesoscale meteorological models (Fifth-Generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model, Regional Atmospheric Modeling System, Coupled Ocean-Atmosphere Mesoscale Prediction System, and Op- erational Multiscale Environmental Model with Grid Adaptivity). These models have been applied by others to time periods of several days in three areas of the United States (Northeast, Lake Michigan area, and central California) and in Iraq. The authors' analysis indicates that the typical root-mean-square error (rmse) of hourly averaged surface wind speed is found to be about 2-3 m s21 for a wide range of wind speeds for the models and for the geographic regions studied. The rmse of surface wind direction is about 508 for wind speeds of about 3 o r4ms 21. It is suggested that these uncertainties in wind speeds and directions are primarily due to random turbulent processes that cannot be simulated by the models and to subgrid variations in terrain and land use, and therefore it is unlikely that the errors can be reduced much further. Model simulations of daytime mixing depths are shown to be often within 20% of observations. However, the models tend to predict weaker inversions than are observed in interfacial layers capping the mixing depth. The models also underestimate the vertical temperature gradients in the lowest 100 m during the nighttime, which implies that the simulated boundary layer stability is not as great as that observed, suggesting that the rate of vertical dispersion may be overestimated. The models would be able to simulate better the structure of shallow inversions if their vertical grid sizes were smaller.

Evaluations of Mesoscale Models' Simulations of Near-Surface Winds, Temperature Gradients, and Mixing Depths