Christopher O'Dell, Colorado State University
A Eldering, California Institute of Technology
Paul O. Wennberg, California Institute of TechnologyFollow
David Crisp, California Institute of TechnologyFollow
Michael Gunson, California Institute of Technology
B Fisher, California Institute of Technology, Jet Propulsion Laboratory NASA
Christian Frankenberg, California Institute of TechnologyFollow
Matthaus Kiel, Karlsruhe Institute of Technology, California Institute of Technology
Hannakaisa Lindqvist, Finnish Meteorological Institute
L Mandrake, California Institute of Technology, Jet Propulsion Laboratory NASA
Aronne Merrelli, University of Wisconsin
V Natraj, California Institute of Technology
Robert Nelson, Colorado State University
Greg Osterman, California Institute of Technology, Jet Propulsion Laboratory NASA
V H. Payne, California Institute of Technology
T E. Taylor, Colorado State University
Debra Wunch, California Institute of Technology, University of TorontoFollow
Brian Drouin, California Institute of Technology
F A. Oyafuso, California Institute of Technology
Albert Chang, California Institute of Technology
James McDuffie, California Institute of Technology
Michael M. Smyth, California Institute of Technology, Jet Propulsion Laboratory NASA
David Baker, Colorado State University
Sourish Basu, Netherlands Institute for Space Research, University of ColoradoFollow
Frédéric Chevallier, CNRS Centre National de la Recherche ScientifiqueFollow
Sean Crowell, University of Oklahoma
L Feng, University of Edinburgh
Paul I. Palmer, University of EdinburghFollow
Mavendra Dubey, Los Alamos National Laboratory
Omar E. Garcia, Izana Atmospheric Research Centre, Izaña Atmospheric Research Centre, Spain
David W. T Griffith, University of WollongongFollow
Frank Hase, IMK-A-SF, Karlsruhe Institute of Technology, Laboratoire des Sciences du Climat et de L'Environnement
Laura T. Iraci, NASA Ames Research Center, Moffett Field, CA, USA
Rigel Kivi, FMI Arctic Research Center, Finnish Meteorological Institute
Isamu Morino, National Institute for Environmental Studies
Justus Notholt, University of Bremen
Hirofumi Ohyama, Japan Aerospace Exploration Agency, National Institute for Environmental Studies
Christof Petri, University of BremenFollow
Coleen M. Roehl, California Institute of Technology
Mahesh Kumar Sha, BIRA-IASB, Belgium
Kimberly Strong, University of TorontoFollow
Ralf Sussmann, Karlsruhe Institute of TechnologyFollow
Yao Te, Sorbonne Universites, PSL Research University
Osamu Uchino, National Institute for Environmental StudiesFollow
Voltaire A. Velazco, University of WollongongFollow



Publication Details

O'Dell, C. W., Eldering, A., Wennberg, P. O., Crisp, D., Gunson, M. R., Fisher, B., Frankenberg, C., Kiel, M., Lindqvist, H., Mandrake, L., Merrelli, A., Natraj, V., Nelson, R. R., Osterman, G. B., Payne, V. H., Taylor, T. E., Wunch, D., Drouin, B. J., Oyafuso, F., Chang, A., McDuffie, J., Smyth, M., Baker, D. F., Basu, S., Chevallier, F., Crowell, S. M.R., Feng, L., Palmer, P. I., Dubey, M., Garcia, O. E., Griffith, D. W.T., Hase, F., Iraci, L. T., Kivi, R., Morino, I., Notholt, J., Ohyama, H., Petri, C., Roehl, C. M., Sha, M. K., Strong, K., Sussmann, R., Te, Y., Uchino, O. & Velazco, V. A. (2018). Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm. Atmospheric Measurement Techniques, 11 (12), 6539-6576.


Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-Averaged dry air mole fraction of atmospheric CO2 (XCO2 ) for the roughly 100 000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25 %, is required in order to accurately infer carbon sources and sinks from XCO2 , significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining goodquality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regionalscale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20% over land and 40% over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO2 data record continues to expand.



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