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Published June 27, 2023 | Version Published
Journal Article Open

Evaluating the consistency between OCO-2 and OCO-3 XCO₂ estimates derived from the NASA ACOS version 10 retrieval algorithm

Creators

  • 1. ROR icon Colorado State University
  • 2. ROR icon Jet Propulsion Lab
  • 3. ROR icon Laboratoire des Sciences du Climat et de l'Environnement
  • 4. ROR icon University of Edinburgh
  • 5. ROR icon University of Michigan–Ann Arbor
  • 6. ROR icon University of Oklahoma
  • 7. ROR icon Morgan State University
  • 8. ROR icon Goddard Space Flight Center
  • 9. ROR icon California Institute of Technology

Abstract

The version 10 (v10) Atmospheric Carbon Observations from Space (ACOS) Level 2 full-physics (L2FP) retrieval algorithm has been applied to multiyear records of observations from NASA's Orbiting Carbon Observatory 2 and 3 sensors (OCO-2 and OCO-3, respectively) to provide estimates of the carbon dioxide (CO2) column-averaged dry-air mole fraction (XCO2). In this study, a number of improvements to the ACOS v10 L2FP algorithm are described. The post-processing quality filtering and bias correction of the XCO2 estimates against multiple truth proxies are also discussed. The OCO v10 data volumes and XCO2 estimates from the two sensors for the time period of August 2019 through February 2022 are compared, highlighting differences in spatiotemporal sampling but demonstrating broad agreement between the two sensors where they overlap in time and space. A number of evaluation sources applied to both sensors suggest they are broadly similar in data and error characteristics. Mean OCO-3 differences relative to collocated OCO-2 data are approximately 0.2 and −0.3 ppm for land and ocean observations, respectively. Comparison of XCO2 estimates to collocated Total Carbon Column Observing Network (TCCON) measurements shows root mean squared errors (RMSEs) of approximately 0.8 and 0.9 ppm for OCO-2 and OCO-3, respectively. An evaluation against XCO2 fields derived from atmospheric inversion systems that assimilated only near-surface CO2 observations, i.e., did not assimilate satellite CO2 measurements, yielded RMSEs of 1.0 and 1.1 ppm for OCO-2 and OCO-3, respectively. Evaluation of uncertainties in XCO2 over small areas, as well as XCO2 biases across land–ocean crossings, also indicates similar behavior in the error characteristics of both sensors. Taken together, these results demonstrate a broad consistency of OCO-2 and OCO-3 XCO2 measurements, suggesting they may be used together for scientific analyses.

Copyright and License

© Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License. Published by Copernicus Publications on behalf of the European Geosciences Union.

Acknowledgement

A portion of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration (80NM0018D0004). Government sponsorship is acknowledged. The CSU/CIRA contribution to this work was supported by JPL subcontracts 1439002 (OCO-2) and 1557985 (OCO-3). Aronne Merrelli's contributions to this work were supported by JPL subcontract 1577173. Paul I. Palmer and Liang Feng acknowledge support from the UK National Centre for Earth Observation funded by the National Environment Research Council (NE/R016518/1). We gratefully acknowledge the use of TCCON data in this work. We thank the two anonymous reviewers for their time to provide very useful comments on the paper. We also thank the journal editor, Joanna Joiner, for her willingness to oversee the review process.

Funding

This research has been supported by the National Aeronautics and Space Administration (grant no. 80NM0018D0004), JPL (subcontracts 1439002 (OCO-2), 1557985 (OCO-3), and 1577173), and the UK National Centre for Earth Observation funded by the National Environment Research Council (grant no. NE/R016518/1).

Data Availability

The OCO XCO2 and other retrieval properties are publicly available at the NASA Goddard Earth Science Data and Information Services Center (GES-DISC). The full suite of retrieval products in the standard per-orbit format can be obtained at https://doi.org/10.5067/6SBROTA57TFH (OCO Science Team et al., 2020b) and https://doi.org/10.5067/D9S8ZOCHCADE (OCO Science Team et al., 2021) for OCO-2 and OCO-3, respectively. The Lite files, which include the quality-flagged and bias-corrected estimates of XCO2, can be obtained at https://doi.org/10.5067/E4E140XDMPO2 (OCO Science Team et al., 2020a) and https://doi.org/10.5067/970BCC4DHH24 (OCO Science Team et al., 2022) for OCO-2 and OCO-3, respectively. For OCO-3, researchers are urged to use the v10.4 Lite files and avoid use of the XCO2 values reported in the v10 L2 Standard product, which do not have the ad hoc bias correction applied.

The TCCON data for individual stations are referenced in Table 3 and are available on the CaltechDATA site (https://data.caltech.edu/, last access: 21 June 2023). CarbonTracker CT-NRT.v2019-2 and CT-NRT.v2021-3 results are provided by NOAA ESRL, Boulder, Colorado, USA, from the website at https://carbontracker.noaa.gov (last access: 21 June 2023). The Jena-CarboScope model data are available at http://www.bgc-jena.mpg.de/CarboScope (last access: 21 June 2023). The Copernicus Atmosphere Monitoring Service (CAMS) CAMS-INV model data were obtained from https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-greenhouse-gas-inversion?tab=overview (last access: 21 June 2023), while the CAMS-REAN data were obtained from https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-ghg-reanalysis-egg4?tab=overview (last access: 21 June 2023). The UoL model data are available at https://www.geos.ed.ac.uk/~lfeng/ (last access: 21 June 2023). The GEOS data used in this study were provided by the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center.

Contributions

TET conceptualized the study, performed the data analysis, generated the graphics, and wrote the paper. CWO'D helped conceptualize the study, led the ACOS L2FP retrieval algorithm development, performed the quality filtering and bias correction, helped with data analysis, and edited an early draft of the paper. CB, LC, DF, VH, RL, YM, GRK, RR, and SY performed instrument calibration required for accurate retrievals of XCO2. JZ performed the geolocation of the soundings. BD and FO developed and provided the spectroscopic lookup tables that are crucial for accurate retrievals of XCO2. BF, MK, LK, TK, AL, JL, LM, GM, AM, RRN, GO, PS, GS, and POW all contributed in various ways to OCO operations, the v10 ACOS L2FP algorithm testing and development, and the v10 quality filtering and bias correction procedure. AlC, CC, LD, and CT performed the data testing and maintained the operational pipeline required to produce the XCO2 products. DB provided the 10 s average XCO2 files used in the evaluation against models and provided valuable insight into the OCO v10 XCO2 products during and after development. FC, LF, PIP, and BW provided model data used in the quality filtering, bias correction, and evaluation of the v10 XCO2. VHP and AbC are the current project scientists for OCO-2 and OCO-3, respectively, while MG and AE were the former project scientists for OCO-2 and OCO-3, respectively. JL is the current OCO-2/3 science team lead, while DC was the former OCO-2/3 science team lead. DC also edited a mature version of the paper. All coauthors reviewed and provided comments on the draft paper prior to submission.

Conflict of Interest

At least one of the (co-)authors is a member of the editorial board of Atmospheric Measurement Techniques. The peer-review process was guided by an independent editor, and the authors also have no other competing interests to declare.

Additional Information

This paper was edited by Joanna Joiner and reviewed by two anonymous referees.

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Additional details

Related works

Is new version of
Discussion Paper: 10.5194/amt-2022-329 (DOI)
Is supplemented by
Dataset: 10.5067/6SBROTA57TFH (DOI)
Dataset: 10.5067/D9S8ZOCHCADE (DOI)
Dataset: 10.5067/E4E140XDMPO2 (DOI)

Funding

National Aeronautics and Space Administration
80NM0018D0004
Jet Propulsion Laboratory
1439002
Jet Propulsion Laboratory
1557985
Jet Propulsion Laboratory
1577173
National Centre for Earth Observation
NE/R016518/1

Dates

Accepted
2023-05-18

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Caltech groups
Division of Engineering and Applied Science (EAS), Division of Geological and Planetary Sciences (GPS)
Publication Status
Published