Results from air quality simulations have far reaching implications and are closely linked to the meteorological model that drives chemical transport, diffusion, and reactions. Therefore, modeling systems should be evaluated by considering all components involved (Hogrefe et al. 2001). This connection can be achieved by linking the statistical analysis of the air quality model with that of the meteorological model in space and time, in order to distinguish how errors in the air chemistry model are attributed to errors in the meteorological modeling. An evaluation tool is being developed that will (1) provide a better sense of meteorological model uncertainty; (2) standardize the evaluation process; (3) manage a large volume of evaluation results; (4) make the overall evaluation process more efficient and less labor intensive; and (5) directly link the meteorological model evaluation with the air quality model evaluation. This study applies the model evaluation tool to a year-long simulation using the Pennsylvania State University (PSU) / National Center for Atmospheric Research (NCAR) fifth-generation mesoscale model (MM5). The results are reported not only to examine the MM5 model performance, but also to demonstrate the effectiveness of the evaluation system. Among the evaluations presented are surface-based 2 m temperature, 10 m wind, 2 m mixing ratio, precipitation and solar radiation. Wind profiler data are also used to examine the ability of MM5 to simulate the vertical distribution of wind over the diurnal cycle. Additionally, a direct linkage between the meteorological and the air quality model performance, specifically ozone and nitrate, is attempted. Only a brief summary of the results are presented here because of manuscript length requirements.