Estimating North American background ozone in U.S. surface air with two independent global models: Variability, uncertainties, and recommendations

摘要

Accurate estimates for North American background (NAB) ozone (O_3) in surface air over the United States are needed for setting and implementing an attainable national O_3 standard. These estimates rely on simulations with atmospheric chemistry-transport models that set North American anthropogenic emissions to zero, and to date have relied heavily on one global model. We examine NAB estimates for spring and summer 2006 with two independent global models (GEOS-Chem and GFDL AM3). We evaluate the base simulations, which include North American anthropogenic emissions, with mid-tropospheric O_3 retrieved from space and ground-level O_3 measurements. The models often bracket the observed values, implying value in developing a multi-model approach to estimate NAB O_3. Consistent with earlier studies, the models robustly simulate the largest nation-wide NAB levels at high-altitude western U.S. sites (seasonal average maximum daily 8-h values of ～40-50 ppb in spring and ～25-40 ppb in summer) where it correlates with observed O_3. At these sites, a 27-year GFDL AM3 simulation simulates observed O_3 events above 60 ppb and indicates that year-to-year variations in NAB O_3 influence their annual frequency (with NAB contributing 50-60 ppb or more during individual events). During summer over the eastern United States (EUS), when photochemical production from regional anthropogenic emissions peaks, NAB is largely uncorrelated with observed values and it is lower than at high-altitude sites (average values of ～20-30 ppb). Four processes contribute substantially to model differences in specific regions and seasons: lightning NO_x, biogenic isoprene emissions and chemistry, wildfires, and stratosphere-to-troposphere transport. Differences in the representations of these processes within the GFDL AM3 and GEOS-Chem models contribute more to uncertainty in NAB estimates, particularly in spring when NAB is highest, than the choice of horizontal resolution within a single model (GEOS-Chem). We propose that future efforts seek to constrain these processes with targeted analysis of multi-model simulations evaluated with observations of O_3 and related species from multiple platforms, and thereby reduce the error on NAB estimates needed for air quality planning.