Abstract
Abstract. We present a global data set of free tropospheric ozone–CO correlations with 2° × 2.5° spatial resolution from the Ozone Monitoring Instrument (OMI) and Atmospheric Infrared Sounder (AIRS) satellite instruments for each season of 2008. OMI and AIRS have near-daily global coverage of ozone and CO respectively and observe coincident scenes with similar vertical sensitivities. The resulting ozone–CO correlations are highly statistically significant (positive or negative) in most regions of the world, and are less noisy than previous satellite-based studies that used sparser data. Comparison with ozone–CO correlations and regression slopes (dO3/dCO) from MOZAIC (Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by in-service AIrbus airCraft) aircraft profiles shows good general agreement. We interpret the observed ozone–CO correlations with the GEOS (Goddard Earth Observing System)-Chem chemical transport model to infer constraints on ozone sources. Driving GEOS-Chem with different meteorological fields generally shows consistent ozone–CO correlation patterns, except in some tropical regions where the correlations are strongly sensitive to model transport error associated with deep convection. GEOS-Chem reproduces the general structure of the observed ozone–CO correlations and regression slopes, although there are some large regional discrepancies. We examine the model sensitivity of dO3/dCO to different ozone sources (combustion, biosphere, stratosphere, and lightning NOx) by correlating the ozone change from that source to CO from the standard simulation. The model reproduces the observed positive dO3/dCO in the extratropical Northern Hemisphere in spring–summer, driven by combustion sources. Stratospheric influence there is also associated with a positive dO3/dCO because of the interweaving of stratospheric downwelling with continental outflow. The well-known ozone maximum over the tropical South Atlantic is associated with negative dO3/dCO in the observations; this feature is reproduced in GEOS-Chem and supports a dominant contribution from lightning to the ozone maximum. A major model discrepancy is found over the northeastern Pacific in summer–fall where dO3/dCO is positive in the observations but negative in the model, for all ozone sources. We suggest that this reflects a model overestimate of lightning at northern midlatitudes combined with an underestimate of the East Asian CO source.
Highlights
GEOS-Chem reproduces the general structure of the observed ozone–CO correlations and regression slopes, there are some large regional discrepancies
We evaluate the ozone–CO correlations and regression slopes derived from Ozone Monitoring Instrument (OMI)/Atmospheric Infrared Sounder (AIRS) with in situ aircraft profiles over commercial airports in 2006 and 2008 from the MOZAIC program (Marenco et al, 1998 and www.iagos.fr)
We require at least 10 MOZAIC vertical profiles with coincident satellite data at a site in a given season to derive ozone–CO correlations. This requirement is satisfied in those two years for three MOZAIC sites in Europe (Frankfurt, London, Vienna), four sites in the USA (Atlanta, Dallas, Philadelphia, Portland), two sites in Asia (Hyderabad, Tokyo), and one site in Africa (Windhoek)
Summary
GEOS-Chem reproduces the general structure of the observed ozone–CO correlations and regression slopes, there are some large regional discrepancies. Tropospheric ozone is produced by the photochemical oxidation of carbon monoxide (SCOo)l,imdeEthaanret(hCH4), and nonmethane volatile organic compounds (NMVOCs) in the presence of nitrogen oxides (NOx ≡ NO + NO2). Current global models can capture the observed large-scale spatial and seasonal patterns of ozone concentrations but there is large uncertainty in the driving factors, as reflected by the large differences between models in ozone production and loss rates (Wild, 2007; Wu et al, 2007) and in source contributions (Fiore et al, 2009). We present here a high-density global satellite database of ozone–CO correlations using data from the Ozone Monitoring Instrument (OMI; Levelt et al, 2006) and the Atmospheric Infrared Sounder (AIRS; Aumann et al, 2003), and explore its value for constraining our understanding of the factors controlling ozone
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