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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 5 | Copyright
Atmos. Meas. Tech., 10, 1769-1782, 2017
https://doi.org/10.5194/amt-10-1769-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 11 May 2017

Research article | 11 May 2017

Carbon monoxide column retrieval for clear-sky and cloudy atmospheres: a full-mission data set from SCIAMACHY 2.3  µm reflectance measurements

Tobias Borsdorff1, Joost aan de Brugh1, Haili Hu1, Philippe Nédélec2, Ilse Aben1, and Jochen Landgraf1 Tobias Borsdorff et al.
  • 1Earth science group, SRON Netherlands Institute for Space Research, Utrecht, the Netherlands
  • 2Laboratoire d'aérologie (LA), CNRS UMR-5560 et Observatoire Midi-Pyrénées, Université Paul-Sabatier, Toulouse, France

Abstract. We discuss the retrieval of carbon monoxide (CO) vertical column densities from clear-sky and cloud contaminated 2311–2338nm reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) from January 2003 until the end of the mission in April 2012. These data were processed with the Shortwave Infrared CO Retrieval algorithm (SICOR) that we developed for the operational data processing of the Tropospheric Monitoring Instrument (TROPOMI) that will be launched on ESA's Sentinel-5 Precursor (S5P) mission. This study complements previous work that was limited to clear-sky observations over land. Over the oceans, CO is estimated from cloudy-sky measurements only, which is an important addition to the SCIAMACHY clear-sky CO data set as shown by NDACC and TCCON measurements at coastal sites. For Ny-Ålesund, Lauder, Mauna Loa and Reunion, a validation of SCIAMACHY clear-sky retrievals is not meaningful because of the high retrieval noise and the few collocations at these sites. The situation improves significantly when considering cloudy-sky observations, where we find a low mean bias b = ±6. 0ppb and a strong correlation between the validation and the SCIAMACHY results with a mean Pearson correlation coefficient r = 0. 7. Also for land observations, cloudy-sky CO retrievals present an interesting complement to the clear-sky data set. For example, at the cities Tehran and Beijing the agreement of SCIAMACHY clear-sky CO observations with MOZAIC/IAGOS airborne measurements is poor with a mean bias of b = 171. 2ppb and 57.9ppb because of local CO pollution, which cannot be captured by SCIAMACHY. For cloudy-sky retrievals, the validation improves significantly. Here the retrieved column is mainly sensitive to CO above the cloud and so not affected by the strong local surface emissions. Adjusting the MOZAIC/IAGOS measurements to the vertical sensitivity of the retrieval, the mean bias adds up to b = 52. 3ppb and 5.0ppb for Tehran and Beijing. At the less urbanised region around the airport Windhoek, local CO pollution is less prominent and so MOZAIC/IAGOS measurements agree well with SCIAMACHY clear-sky retrievals with a mean bias of b = 15. 5ppb, but can be even further improved for cloudy SCIAMACHY observations with a mean bias of b = 0. 2ppb. Overall the cloudy-sky CO retrievals from SCIAMACHY short-wave infrared measurements present a major extension of the clear-sky-only data set, which more than triples the amount of data and adds unique observations over the oceans. Moreover, the study represents the first application of the S5P algorithm for operational CO data processing on cloudy observations prior to the launch of the S5P mission.

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