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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 5, issue 9
Atmos. Meas. Tech., 5, 2133–2142, 2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 5, 2133–2142, 2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 05 Sep 2012

Research article | 05 Sep 2012

Validation of six years of SCIAMACHY carbon monoxide observations using MOZAIC CO profile measurements

A. T. J. de Laat1,2, R. Dijkstra2, H. Schrijver2, P. Nédélec3, and I. Aben2 A. T. J. de Laat et al.
  • 1Royal Netherlands Meteorological Institute (KNMI), de Bilt, The Netherlands
  • 2SRON Netherlands Institute for Space Research, Utrecht, The Netherlands
  • 3Centre National de la Recherche Scientifique (CNRS), Universite Paul Sabatier, Laboratoire d'aérologie, Toulouse, France

Abstract. This paper presents a validation study of SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) carbon monoxide (CO) total column measurements from the Iterative Maximum Likelihood Method (IMLM) algorithm using vertically integrated profile aircraft measurements obtained within the MOZAIC project for the six year time period of 2003–2008.

Overall we find a good agreement between SCIAMACHY and airborne measurements for both mean values – also on a year-to-year basis – as well as seasonal variations. Several locations show large biases that are attributed to local effects like orography and proximity of large emission sources. Differences were detected for individual years: 2003, 2004 and 2006 have larger biases than 2005, 2007 and 2008, which appear to be related to SCIAMACHY instrumental issues but require more research. Results from this study are consistent with, and complementary to, findings from a previous validation study using ground-based measurements (de Laat et al., 2010b). According to this study, the SCIAMACHY data, if individual measurements are of sufficient quality – good signal-to-noise, can be used to determine the spatial distribution and seasonal cycles of CO total columns over clean areas. Biases found over areas with strong emissions (Africa, China) could be explained by low sensitivity of the instrument in the boundary layer and users are recommended to avoid using the SCIAMACHY data while trying to quantify CO burden and/or retrieve CO emissions in such areas.

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