A comparison of CMAQ-based and observation-based statistical models relating ozone to meteorological parameters

Statistical relationships between ground-level daily maximum 8-h ozone (O3) concentrations and multiple meteorological parameters were developed for data drawn from ambient measurements and values that were simulated with the U.S. Environmental Protection Agency’s (EPA) Community Multiscale Air Quality (CMAQ) model. This study used concurrent and co-located data from both sources during the O3 season (May 1–September 30) for a four-year period (2002–2005). Regression models were developed for 74 areas across the Eastern U.S. The most important meteorological parameters used in the model were found to be daily maximum temperature and the daily average relative humidity (RH). Average morning and afternoon wind speed as well as factors for the day of the week and years were also included in the statistical models. R2 values above 60% were obtained for the majority of the locations in the analysis for both the ambient and CMAQ statistical models. Analysis of the covariate-specific effects revealed a tendency for the CMAQ model to underestimate how O3 increases with temperature. These results suggest that air quality forecasts that incorporate the CMAQ model may be underestimating the climate penalty on future O3 concentrations from warmer temperatures.

► Relationships between ozone and meteorology are assessed.
► These relationships are separately derived for CMAQ and measurement data.
► CMAQ underestimates the increases in ozone that result from increasing temperature.
► This finding may have implications for coupled climate – air quality models.