Articles | Volume 9, issue 2
https://doi.org/10.5194/amt-9-683-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-683-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Consistent evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON
Susan Kulawik , Debra Wunch, Christopher O'Dell, Christian Frankenberg, Maximilian Reuter, Tomohiro Oda, Frederic Chevallier, Vanessa Sherlock, Michael Buchwitz, Greg Osterman, Charles E. Miller, Paul O. Wennberg, David Griffith, Isamu Morino, Manvendra K. Dubey, Nicholas M. Deutscher, Justus Notholt, Frank Hase, Thorsten Warneke, Ralf Sussmann, John Robinson, Kimberly Strong, Matthias Schneider, Martine De Mazière, Kei Shiomi, Dietrich G. Feist, Laura T. Iraci, and Joyce Wolf
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- Final revised paper (published on 29 Feb 2016)
- Preprint (discussion started on 22 Jun 2015)
Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Supplement - Supplement
- RC C2148: 'Review of "Consistent evaluation of GOSAT SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON" by Kulawik et al.', Anonymous Referee #1, 20 Jul 2015 Printer-friendly Version
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RC C2594: 'Review of Consistent evaluation of GOSAT, SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON by Kulawik et al.', Anonymous Referee #2, 14 Aug 2015
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- AC C4258: 'Response to reviewers', Susan Kulawik, 10 Dec 2015 Printer-friendly Version
Short summary
To accurately estimate source and sink locations of carbon dioxide, systematic errors in satellite measurements and models must be characterized. This paper examines two satellite data sets (GOSAT, launched 2009, and SCIAMACHY, launched 2002), and two models (CarbonTracker and MACC) vs. the TCCON CO2 validation data set. We assess biases and errors by season and latitude, satellite performance under averaging, and diurnal variability. Our findings are useful for assimilation of satellite data.
To accurately estimate source and sink locations of carbon dioxide, systematic errors in...