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High levels of ozone have been observed along the shores of Lake Michigan for the last 40 years. Models continue to struggle in their ability to replicate ozone behavior in the region. In the retrospective way in which models are used in air quality regulation development, nudging or four-dimensional data assimilation (FDDA) of the large-scale environment is important for constraining model forecast errors. Here, paths for incorporating large-scale meteorological conditions but retaining model mesoscale structure are evaluated. For the July 2011 case studied here, iterative FDDA strategies did not improve mesoscale performance in the Great Lakes region in terms of diurnal trends or monthly averaged statistics, with overestimations of nighttime wind speed remaining as an issue. Two vertical nudging strategies were evaluated for their effects on the development of nocturnal low-level jets (LLJ) and their impacts on air quality simulations. Nudging only above the planetary boundary layer, which has been a standard option in many air quality simulations, significantly dampened the amplitude of LLJ relative to nudging only above a height of 2 km. While the LLJ was preserved with nudging only above 2 km, there was some deterioration in wind performance when compared with profiler networks above the jet between 500 m and 2 km. In examining the impact of nudging strategies on air quality performance of the Community Multiscale Air Quality model, it was found that performance was improved for the case of nudging above 2 km. This result may reflect the importance of the LLJ in transport or perhaps a change in mixing in the models.

Examination of Nudging Schemes in the Simulation of Meteorology for Use in Air Quality Experiments: Application in the Great Lakes Region