Global O<sub>3</sub>–CO correlations in a chemistry and transport model during July–August: evaluation with TES satellite observations and sensitivity to input meteorological data and emissions
We examine the capability of the Global Modeling Initiative (GMI) chemistry and transport model to reproduce global mid-tropospheric (618 hPa) ozone–carbon monoxide (O<sub>3</sub>–CO) correlations determined by the measurements from the Tropospheric Emission Spectrometer (TES) aboard...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-07-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/17/8429/2017/acp-17-8429-2017.pdf |
| _version_ | 1817998110548295680 |
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| author | H.-D. Choi H. Liu J. H. Crawford D. B. Considine D. B. Considine D. J. Allen B. N. Duncan L. W. Horowitz J. M. Rodriguez S. E. Strahan S. E. Strahan L. Zhang L. Zhang X. Liu M. R. Damon M. R. Damon S. D. Steenrod S. D. Steenrod |
| author_facet | H.-D. Choi H. Liu J. H. Crawford D. B. Considine D. B. Considine D. J. Allen B. N. Duncan L. W. Horowitz J. M. Rodriguez S. E. Strahan S. E. Strahan L. Zhang L. Zhang X. Liu M. R. Damon M. R. Damon S. D. Steenrod S. D. Steenrod |
| author_sort | H.-D. Choi |
| collection | DOAJ |
| description | We examine the capability of the Global Modeling Initiative (GMI) chemistry
and transport model to reproduce global mid-tropospheric (618 hPa)
ozone–carbon monoxide (O<sub>3</sub>–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 O<sub>3</sub>–CO correlations to
input meteorological data. Model simulations of radionuclide tracers
(<sup>222</sup>Rn, <sup>210</sup>Pb, and <sup>7</sup>Be) are used to illustrate the differences
in transport-related processes among the meteorological data sets. Simulated
O<sub>3</sub> values are evaluated with climatological profiles from ozonesonde
measurements and satellite tropospheric O<sub>3</sub> columns. Despite the fact
that the three simulations show significantly different global and regional
distributions of O<sub>3</sub> and CO concentrations, they show similar patterns of
O<sub>3</sub>–CO correlations on a global scale. All model simulations sampled
along the TES orbit track capture the observed positive O<sub>3</sub>–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 O<sub>3</sub> 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 O<sub>3</sub>–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 O<sub>3</sub>–CO correlation patterns, we examine the sensitivity of
GMI/MERRA model-calculated O<sub>3</sub> and CO concentrations and their
correlations to emission types (fossil fuel, biomass burning, biogenic, and
lightning NO<sub><i>x</i></sub> emissions). Fossil fuel and biomass burning emissions are
mainly responsible for the strong positive O<sub>3</sub>–CO correlations over
continental outflow regions in both hemispheres. Biogenic emissions have a
relatively smaller impact on O<sub>3</sub>–CO correlations than other emissions
but are largely responsible for the negative correlations over the tropical
eastern Pacific, reflecting the fact that O<sub>3</sub> is consumed and CO
generated during the atmospheric oxidation process of isoprene under
low-NO<sub><i>x</i></sub> conditions. We find that lightning NO<sub><i>x</i></sub> emissions degrade
both positive correlations at mid- and high latitudes and negative
correlations in the tropics because ozone production downwind of lightning
NO<sub><i>x</i></sub> emissions is not directly related to the emission and transport of
CO. Our study concludes that O<sub>3</sub>–CO correlations may be used effectively
to constrain the sources of regional tropospheric O<sub>3</sub> in global 3-D
models, especially for those regions where convective transport of pollution
plays an important role. |
| first_indexed | 2024-04-14T02:48:25Z |
| format | Article |
| id | doaj.art-d212891ece2d43f5b73d69d8f599cbc1 |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-04-14T02:48:25Z |
| publishDate | 2017-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-d212891ece2d43f5b73d69d8f599cbc12022-12-22T02:16:25ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242017-07-01178429845210.5194/acp-17-8429-2017Global O<sub>3</sub>–CO correlations in a chemistry and transport model during July–August: evaluation with TES satellite observations and sensitivity to input meteorological data and emissionsH.-D. Choi0H. Liu1J. H. Crawford2D. B. Considine3D. B. Considine4D. J. Allen5B. N. Duncan6L. W. Horowitz7J. M. Rodriguez8S. E. Strahan9S. E. Strahan10L. Zhang11L. Zhang12X. Liu13M. R. Damon14M. R. Damon15S. D. Steenrod16S. D. Steenrod17National Institute of Aerospace, Hampton, VA, USANational Institute of Aerospace, Hampton, VA, USANASA Langley Research Center, Hampton, VA, USANASA Langley Research Center, Hampton, VA, USAnow at: NASA Headquarters, Washington, D.C., USAUniversity of Maryland, College Park, MD, USANASA Goddard Space Flight Center, Greenbelt, MD, USANOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USANASA Goddard Space Flight Center, Greenbelt, MD, USANASA Goddard Space Flight Center, Greenbelt, MD, USAUniversities Space Research Association, Columbia, MD, USAHarvard University, Cambridge, MA, USAnow at: Peking University, Beijing, ChinaHarvard University, Cambridge, MA, USANASA Goddard Space Flight Center, Greenbelt, MD, USAScience Systems and Applications, Inc., Lanham, MD, USANASA Goddard Space Flight Center, Greenbelt, MD, USAUniversities Space Research Association, Columbia, MD, USAWe examine the capability of the Global Modeling Initiative (GMI) chemistry and transport model to reproduce global mid-tropospheric (618 hPa) ozone–carbon monoxide (O<sub>3</sub>–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 O<sub>3</sub>–CO correlations to input meteorological data. Model simulations of radionuclide tracers (<sup>222</sup>Rn, <sup>210</sup>Pb, and <sup>7</sup>Be) are used to illustrate the differences in transport-related processes among the meteorological data sets. Simulated O<sub>3</sub> values are evaluated with climatological profiles from ozonesonde measurements and satellite tropospheric O<sub>3</sub> columns. Despite the fact that the three simulations show significantly different global and regional distributions of O<sub>3</sub> and CO concentrations, they show similar patterns of O<sub>3</sub>–CO correlations on a global scale. All model simulations sampled along the TES orbit track capture the observed positive O<sub>3</sub>–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 O<sub>3</sub> 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 O<sub>3</sub>–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 O<sub>3</sub>–CO correlation patterns, we examine the sensitivity of GMI/MERRA model-calculated O<sub>3</sub> and CO concentrations and their correlations to emission types (fossil fuel, biomass burning, biogenic, and lightning NO<sub><i>x</i></sub> emissions). Fossil fuel and biomass burning emissions are mainly responsible for the strong positive O<sub>3</sub>–CO correlations over continental outflow regions in both hemispheres. Biogenic emissions have a relatively smaller impact on O<sub>3</sub>–CO correlations than other emissions but are largely responsible for the negative correlations over the tropical eastern Pacific, reflecting the fact that O<sub>3</sub> is consumed and CO generated during the atmospheric oxidation process of isoprene under low-NO<sub><i>x</i></sub> conditions. We find that lightning NO<sub><i>x</i></sub> emissions degrade both positive correlations at mid- and high latitudes and negative correlations in the tropics because ozone production downwind of lightning NO<sub><i>x</i></sub> emissions is not directly related to the emission and transport of CO. Our study concludes that O<sub>3</sub>–CO correlations may be used effectively to constrain the sources of regional tropospheric O<sub>3</sub> in global 3-D models, especially for those regions where convective transport of pollution plays an important role.https://www.atmos-chem-phys.net/17/8429/2017/acp-17-8429-2017.pdf |
| spellingShingle | H.-D. Choi H. Liu J. H. Crawford D. B. Considine D. B. Considine D. J. Allen B. N. Duncan L. W. Horowitz J. M. Rodriguez S. E. Strahan S. E. Strahan L. Zhang L. Zhang X. Liu M. R. Damon M. R. Damon S. D. Steenrod S. D. Steenrod Global O<sub>3</sub>–CO correlations in a chemistry and transport model during July–August: evaluation with TES satellite observations and sensitivity to input meteorological data and emissions Atmospheric Chemistry and Physics |
| title | Global O<sub>3</sub>–CO correlations in a chemistry and transport model during July–August: evaluation with TES satellite observations and sensitivity to input meteorological data and emissions |
| title_full | Global O<sub>3</sub>–CO correlations in a chemistry and transport model during July–August: evaluation with TES satellite observations and sensitivity to input meteorological data and emissions |
| title_fullStr | Global O<sub>3</sub>–CO correlations in a chemistry and transport model during July–August: evaluation with TES satellite observations and sensitivity to input meteorological data and emissions |
| title_full_unstemmed | Global O<sub>3</sub>–CO correlations in a chemistry and transport model during July–August: evaluation with TES satellite observations and sensitivity to input meteorological data and emissions |
| title_short | Global O<sub>3</sub>–CO correlations in a chemistry and transport model during July–August: evaluation with TES satellite observations and sensitivity to input meteorological data and emissions |
| title_sort | global o sub 3 sub co correlations in a chemistry and transport model during july august evaluation with tes satellite observations and sensitivity to input meteorological data and emissions |
| url | https://www.atmos-chem-phys.net/17/8429/2017/acp-17-8429-2017.pdf |
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