Preprints
https://doi.org/10.5194/acp-2022-458
https://doi.org/10.5194/acp-2022-458
 
04 Jul 2022
04 Jul 2022
Status: this preprint is currently under review for the journal ACP.

Monitoring and assimilation of S5P/TROPOMI carbon monoxide data with the global CAMS near-real time system

Antje Inness1, Ilse Aben2, Melanie Ades1, Tobias Borsdorff2, Johannes Flemming1, Jochen Landgraf2, Bavo Langerock3, Mark Parrington1, and Roberto Ribas1 Antje Inness et al.
  • 1ECMWF, Shinfield Park, Reading, RG2 9AU, UK
  • 2SRON Netherlands Institute for Space Research, Leiden, the Netherlands
  • 3BIRA-IASB, 1180 Brussels, Belgium

Abstract. The Tropospheric Monitoring Instrument (TROPOMI) on the Copernicus Sentinel 5 Precursor (S5P) satellite, launched in October 2017, provides a wealth of atmospheric composition data, including total columns of carbon monoxide (TCCO) at high horizontal resolution (5.5 km x 7 km). Near-real time TROPOMI TCCO data have been monitored in the global data assimilation system of the Copernicus Atmospheric Monitoring Service (CAMS) since November 2018 to assess the quality of the data. The CAMS system already routinely assimilates TCCO data from the Measurement of Pollution in the Troposphere (MOPITT) instrument and the Atmospheric Sounding Interferometer (IASI) outside the polar regions. In the global mean, CAMS TCCO analysis values are about 10 % lower than TROPOMI TCCO when only IASI and MOPITT thermal infrared (TIR) TCCO data are assimilated (averaged over the period November 2018 to Dec 2021), with the largest relative differences (11–14 %) found in the polar latitude bands, i.e., the areas where no satellite CO retrievals are assimilated in the global CAMS system. Most of these differences are due to a low TCCO bias of the CAMS model, rather than a high bias of TROPOMI.

The assimilation of NRT TROPOMI TCCO data in the CAMS system was tested for the period 2021-07-06 to 2021-12-31, i.e., after the TROPOMI algorithm update to version 02.02.00 in July 2021. It leads to a much-improved CO analysis field, with increased CO values and improved fit to independent observations, such as IAGOS aircraft profiles, NDACC FTIR tropospheric and total column CO data, as well as surface CO data from the Air Now, AirBase and Chinese air quality networks. The largest absolute and relative changes from the assimilation of TROPOMI CO, in addition to the already assimilated IASI and MOPITT TIR TCCO data, are found in the lower and mid troposphere, i.e., that part of the atmosphere that is not already well constrained by the already assimilated TIR MOPITT and IASI data. The largest impact near the surface comes from clear-sky TROPOMI data over land, and additional vertical information comes from the retrievals of measurements in cloudy conditions.

July and August 2021 saw record numbers of boreal wildfires over North America and Russia leading to large amounts of CO being released into the atmosphere. The CAMS CO analysis captures the high CO columns resulting from these fires and also shows plumes of high CO from the boreal wildfires that are transported from Siberia over the North Pole and from North America over the North Atlantic reaching as far as Europe, even though some of the high CO values detected in the upper troposphere by IAGOS aircraft that intersected parts of the plumes are not quite reached in the CAMS CO analysis.

Antje Inness et al.

Status: open (until 22 Aug 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-458', Anonymous Referee #1, 29 Jul 2022 reply
  • RC2: 'Comment on acp-2022-458', Anonymous Referee #2, 10 Aug 2022 reply

Antje Inness et al.

Antje Inness et al.

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Short summary
The Copernicus Atmosphere Monitoring Service (CAMS) provides daily global air quality forecasts to users worldwide. One of the species of interest is carbon monoxide (CO), an important trace gas in the atmosphere with anthropogenic and natural sources, produced by incomplete combustion, e.g. by wildfires. This paper looks at how well CAMS can model CO in the atmosphere and shows that the fields can be improved when blending CO data from the TROPOMI instrument with the CAMS model.
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