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Addendum published on 16 March 2018, see Remote Sens. 2018, 10(3), 469.

Open AccessEditor’s ChoiceArticle
Remote Sens. 2018, 10(2), 223; https://doi.org/10.3390/rs10020223

Validation of Carbon Monoxide Total Column Retrievals from SCIAMACHY Observations with NDACC/TCCON Ground-Based Measurements

1
DLR—German Aerospace Center, Remote Sensing Technology Institute, 82234 Oberpfaffenhofen, Germany
2
EUMETSAT—European Organisation for the Exploitation of Meteorological Satellites, 64283 Darmstadt, Germany
*
Author to whom correspondence should be addressed.
Received: 6 December 2017 / Revised: 19 January 2018 / Accepted: 25 January 2018 / Published: 1 February 2018
(This article belongs to the Section Atmosphere Remote Sensing)
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Abstract

The objective was to validate the carbon monoxide (CO) total column product inferred from Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) full-mission (2003–2011) short-wave infrared (SWIR) nadir observations using the Beer InfraRed Retrieval Algorithm (BIRRA). Globally distributed Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) ground-based (g-b) measurements were used as a true reference. Weighted averages of SCIAMACHY CO observations within a circle around the g-b observing system were utilized to minimize effects due to spatial mismatch of space-based (s-b) and g-b observations, i.e., disagreements due to representation errors rather than instrument and/or algorithm deficiencies. In addition, temporal weighted averages were examined and then the unweighted (classical) approach was compared to the weighted (non-classical) method. The delivered distance-based filtered SCIAMACHY data were in better agreement with respect to CO averages as compared to square-shaped sampling areas throughout the year. Errors in individual SCIAMACHY retrievals have increased substantially since 2005. The global bias was determined to be in the order of 10 parts per billion in volume (ppbv) depending on the reference network and validation strategy used. The largest negative bias was found to occur in the northern mid-latitudes in Europe and North America, and was partly caused by insufficient a priori estimates of CO and cloud shielding. Furthermore, no significant trend was identified in the global bias throughout the mission. The global analysis of the CO columns retrieved by the BIRRA shows results that are largely consistent with similar investigations in previous works. View Full-Text
Keywords: SCIAMACHY; BIRRA; NDACC; TCCON; validation; retrieval; carbon monoxide; mixing ratios; weighted averages SCIAMACHY; BIRRA; NDACC; TCCON; validation; retrieval; carbon monoxide; mixing ratios; weighted averages
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Hochstaffl, P.; Schreier, F.; Lichtenberg, G.; Gimeno García, S. Validation of Carbon Monoxide Total Column Retrievals from SCIAMACHY Observations with NDACC/TCCON Ground-Based Measurements. Remote Sens. 2018, 10, 223.

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