Seasonal ozone vertical profiles over North America using the AQMEII3 group of air quality models: model inter-comparison and stratospheric intrusions.

This study evaluates simulated vertical ozone profiles produced in the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3) against ozonesonde observations in North America for the year 2010. Four research groups from the United States (US) and Europe have provided modeled ozone vertical profiles to conduct this analysis. Because some of the modeling systems differ in their meteorological drivers, wind speed and temperature are also included in the analysis. In addition to the seasonal ozone profile evaluation for 2010, we also analyze chemically inert tracers designed to track the influence of lateral boundary conditions on simulated ozone profiles within the modeling domain. Finally, cases of stratospheric ozone intrusions during May-June 2010 are investigated by analyzing ozonesonde measurements and the corresponding model simulations at Intercontinental Chemical Transport Experiment Ozonesonde Network Study (IONS) experiment sites in the western United States. The evaluation of the seasonal ozone profiles reveals that, at a majority of the stations, ozone mixing ratios are underestimated in the 1-6 km range. The seasonal change noted in the errors follows the one seen in the variance of ozone mixing ratios, with the majority of the models exhibiting less variability than the observations. The analysis of chemically inert tracers highlights the importance of lateral boundary conditions up to 250 hPa for the lower-tropospheric ozone mixing ratios (0-2 km). Finally, for the stratospheric intrusions, the models are generally able to reproduce the location and timing of most intrusions but underestimate the magnitude of the maximum mixing ratios in the 2-6 km range and overestimate ozone up to the first kilometer possibly due to marine air influences that are not accurately described by the models. The choice of meteorological driver appears to be a greater predictor of model skill in this altitude range than the choice of air quality model.