Abstract

Abstract. We use the GEOS-Chem chemistry-transport model (CTM) to interpret the spatial and temporal variations of tropical tropospheric CO observed by the Microwave Limb Sounder (MLS) and the Tropospheric Emission Spectrometer (TES). In so doing, we diagnose and evaluate transport in the GEOS-4 and GEOS-5 assimilated meteorological fields that drive the model, with a particular focus on vertical mixing at the end of the dry season when convection moves over the source regions. The results indicate that over South America, deep convection in both GEOS-4 and GEOS-5 decays at too low an altitude early in the wet season, and the source of CO from isoprene in the model (MEGAN v2.1) is too large, causing a lag in the model's seasonal maximum of CO compared to MLS CO in the upper troposphere (UT). TES and MLS data reveal problems with excessive transport of CO to the eastern equatorial Pacific and lofting in the ITCZ in August and September, particularly in GEOS-4. Over southern Africa, GEOS-4 and GEOS-5 simulations match the phase of the observed CO variation from the lower troposphere (LT) to the UT fairly well, although the magnitude of the seasonal maximum is underestimated considerably due to low emissions in the model. A sensitivity run with increased emissions leads to improved agreement with observed CO in the LT and middle troposphere (MT), but the amplitude of the seasonal variation is too high in the UT in GEOS-4. Difficulty in matching CO in the LT and UT implies there may be overly vigorous vertical mixing in GEOS-4 early in the wet season. Both simulations and observations show a time lag between the peak in fire emissions (July and August) and in CO (September and October). We argue that it is caused by the prevailing subsidence in the LT until convection moves south in September, as well as the low sensitivity of TES data in the LT over the African Plateau. The MLS data suggest that too much CO has been transported from fires in northern Africa to the UT in the model during the burning season, as does MOZAIC aircraft data, perhaps as a result of the combined influence of too strong Harmattan winds in the LT and too strong vertical mixing over the Gulf of Guinea in the model.

Highlights

  • Atmospheric carbon monoxide (CO) is produced from incomplete combustion of fossil fuel and biofuels, biomass burning, and from oxidation of atmospheric methane and other hydrocarbons

  • Our analysis reveals flaws in aspects of tropical transport in the Goddard Earth Observing System (GEOS)-4 and GEOS-5 meteorological fields, and in the isoprene emissions in the model, as well as successes

  • Our analysis shows that these deficiencies are caused by two major factors: deep convection decays at too low an altitude in the upper troposphere (UT), and the source of CO from isoprene in the model is too large in the wet season

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Summary

Introduction

Atmospheric carbon monoxide (CO) is produced from incomplete combustion of fossil fuel and biofuels, biomass burning, and from oxidation of atmospheric methane and other hydrocarbons. Barret et al (2008) assimilated MLS data in the MOCAGE Chemistry Transport Model (CTM) to investigate the transport pathways affecting CO in the UT over Africa in July 2006 They found that the CO maximum at ∼200 hPa around 10◦ N is driven by deep convective uplift of air masses affected by biomass burning in southern Africa. The MLS data show maxima at 215 hPa over regions with biomass burning that are associated with convective activity (Liu et al, 2007) This is about the level with maximum outflow from convection, according to evidence from ozone profiles that show a minimum near 200 hPa (Folkins et al, 1999, 2002), and according to a recent review of transport in the tropical tropopause layer (TTL) by Fueglistaler et al (2009). We identify the causes of discrepancies between model and observations, including deficiencies in transport and in sources of CO

Model description
Satellite data
Lower troposphere
Upper troposphere
Influence of dynamics
South America
East Pacific
Africa
Southern Africa
Northern Africa
Indonesia
Findings
Discussion and conclusions
Full Text
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