Global O₃–CO correlations in a chemistry and transport model during July–August: evaluation with TES satellite observations and sensitivity to input meteorological data and emissions

Abstract. We examine the capability of the Global Modeling Initiative (GMI) chemistry and transport model to reproduce global mid-tropospheric (618 hPa) ozone–carbon monoxide (O₃–CO) correlations determined by the measurements from the Tropospheric Emission Spectrometer (TES) aboard NASA's Aura satellite during boreal summer (July–August). The model is driven by three meteorological data sets (finite-volume General Circulation Model (fvGCM) with sea surface temperature for 1995, Goddard Earth Observing System Data Assimilation System Version 4 (GEOS-4 DAS) for 2005, and Modern-Era Retrospective Analysis for Research and Applications (MERRA) for 2005), allowing us to examine the sensitivity of model O₃–CO correlations to input meteorological data. Model simulations of radionuclide tracers (²²²Rn, ²¹⁰Pb, and ⁷Be) are used to illustrate the differences in transport-related processes among the meteorological data sets. Simulated O₃ values are evaluated with climatological profiles from ozonesonde measurements and satellite tropospheric O₃ columns. Despite the fact that the three simulations show significantly different global and regional distributions of O₃ and CO concentrations, they show similar patterns of O₃–CO correlations on a global scale. All model simulations sampled along the TES orbit track capture the observed positive O₃–CO correlations in the Northern Hemisphere midlatitude continental outflow and the Southern Hemisphere subtropics. While all simulations show strong negative correlations over the Tibetan Plateau, northern Africa, the subtropical eastern North Pacific, and the Caribbean, TES O₃ and CO concentrations at 618 hPa only show weak negative correlations over much narrower areas (i.e., the Tibetan Plateau and northern Africa). Discrepancies in regional O₃–CO correlation patterns in the three simulations may be attributed to differences in convective transport, stratospheric influence, and subsidence, among other processes. To understand how various emissions drive global O₃–CO correlation patterns, we examine the sensitivity of GMI/MERRA model-calculated O₃ and CO concentrations and their correlations to emission types (fossil fuel, biomass burning, biogenic, and lightning NO_x emissions). Fossil fuel and biomass burning emissions are mainly responsible for the strong positive O₃–CO correlations over continental outflow regions in both hemispheres. Biogenic emissions have a relatively smaller impact on O₃–CO correlations than other emissions but are largely responsible for the negative correlations over the tropical eastern Pacific, reflecting the fact that O₃ is consumed and CO generated during the atmospheric oxidation process of isoprene under low-NO_x conditions. We find that lightning NO_x emissions degrade both positive correlations at mid- and high latitudes and negative correlations in the tropics because ozone production downwind of lightning NO_x emissions is not directly related to the emission and transport of CO. Our study concludes that O₃–CO correlations may be used effectively to constrain the sources of regional tropospheric O₃ in global 3-D models, especially for those regions where convective transport of pollution plays an important role.