Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm

Creators: O'Dell, Christopher W.; Eldering, Annmarie; Wennberg, Paul O.; Crisp, David; Gunson, Michael R.; Fisher, Brendan; Frankenberg, Christian; Kiel, Matthäus; Lindqvist, Hannakaisa; Mandrake, Lukas; Merrelli, Aronne; Natraj, Vijay; Nelson, Robert R.; Osterman, Gregory B.; Payne, Vivienne H.; Taylor, Thomas E.; Wunch, Debra; Drouin, Brian J.; Oyafuso, Fabiano; Chang, Albert; McDuffie, James; Smyth, Michael; Baker, David F.; Basu, Sourish; Chevallier, Frédéric; Crowell, Sean M. R.; Feng, Liang; Palmer, Paul I.; Dubey, Mavendra; García, Omaira E.; Griffith, David W. T.; Hase, Frank; Iraci, Laura T.; Kivi, Rigel; Morino, Isamu; Notholt, Justus; Ohyama, Hirofumi; Petri, Christof; Roehl, Coleen M.; Sha, Mahesh K.; Strong, Kimberly; Sussmann, Ralf; Te, Yao; Uchino, Osamu; Velazco, Voltaire A.

Abstract

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 (X_(CO₂)) 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 X_(CO₂), 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 good-quality 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 regional-scale 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.

Additional Information

© Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License. Published by Copernicus Publications on behalf of the European Geosciences Union. Received: 27 Jul 2018 – Discussion started: 16 Aug 2018 – Revised: 12 Nov 2018 – Accepted: 15 Nov 2018 – Published: 11 Dec 2018. Part of this work was conducted at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration (NASA) for the Orbiting Carbon Observatory 2 project. Work at Colorado State University and the Geology and Planetary Sciences Department at the California Institute of Technology was supported by subcontracts from the OCO-2 project. CarbonTracker CT2015 and CT-NRT.v2016-1 results provided by NOAA ESRL, Boulder, Colorado, USA, from the website at https://carbontracker.noaa.gov (last access: 4 December 2018). Jena CarboScope atmospheric inversion results provided by Christian Rödenbeck and the Max Planck Institute for Biogeochemistry, from http://www.bgc-jena.mpg.de/CarboScope/ (last access: 4 December 2018). Special thanks to Geoff Toon for illuminating discussions regarding the TCCON CO2 prior. We also thank Julia Marshall and one anonymous referee for their reviews of the manuscript, which greatly improved its quality. Author contributions: CO and AE were involved in nearly all aspects of this work. PW provided critical guidance on nearly all aspects of the work, throughout all stages. DC provided guidance on instrument effects on the algorithm and feedback on the algorithm. MG provided project leadership and algorithm guidance. BF designed and implemented many tests and performed substantial data analysis. CF was involved in earlier phases of algorithm development, in particular with the IMAP-DOAS retrieval, SIF retrieval, and EOF development. MK contributed to the bias correction and analyzed TCCON target-mode data. HL provided the updated cloud ice optical properties. LM created the testing data sets and warn levels, and contributed to filtering and bias correction. AM contributed substantial analysis and wrote the BRDF section. VN guided implementation of the BRDF surface model. RN performed data analysis, in particular with regards to aerosol effects. GO led the target-mode operational effort and organized the validation activities. VP led the spectroscopy effort and wrote the spectroscopy section. TT edited early drafts of this paper and led the pre-filtering activities and analysis. DW provided critical analysis of TCCON/OCO-2 comparisons and advice regarding TCCON data use. BD and FO made important contributions to the ABSCO spectroscopy. AC operationalized the code and assisted in daily operations. JM and MS coded the L2 algorithm and processed testing data sets. DB, SB, FC, SC, LF, and PP provided model data used in the filtering, bias-correction, and validation efforts. MD, OG, DG, FH, LI, RK, IM, JN, HO, CP, CR, MKS, KS, RS, YT, OU, and VV provided TCCON data used in the filtering, bias-correction, and validation efforts. The authors declare that they have no conflict of interest. Edited by: Helen Worden. Reviewed by: Julia Marshall and one anonymous referee.

Attached Files

Published - amt-11-6539-2018.pdf

Files

amt-11-6539-2018.pdf

Files (11.5 MB)

Name	Size	Download all
amt-11-6539-2018.pdf md5:4ac30553817e34fefa19149c42b0ac5e	11.5 MB	Preview Download

Additional details

	All versions	This version
Views	0	0
Downloads	0	0
Data volume	0 Bytes	0 Bytes