Atmospheric Measurement Techniques (Jun 2023)
Evaluating the consistency between OCO-2 and OCO-3 XCO<sub>2</sub> estimates derived from the NASA ACOS version 10 retrieval algorithm
- T. E. Taylor,
- C. W. O'Dell,
- D. Baker,
- C. Bruegge,
- A. Chang,
- L. Chapsky,
- A. Chatterjee,
- C. Cheng,
- F. Chevallier,
- D. Crisp,
- L. Dang,
- B. Drouin,
- A. Eldering,
- L. Feng,
- B. Fisher,
- D. Fu,
- M. Gunson,
- V. Haemmerle,
- G. R. Keller,
- M. Kiel,
- L. Kuai,
- T. Kurosu,
- A. Lambert,
- J. Laughner,
- R. Lee,
- J. Liu,
- L. Mandrake,
- Y. Marchetti,
- G. McGarragh,
- A. Merrelli,
- R. R. Nelson,
- G. Osterman,
- F. Oyafuso,
- P. I. Palmer,
- V. H. Payne,
- R. Rosenberg,
- P. Somkuti,
- G. Spiers,
- C. To,
- B. Weir,
- B. Weir,
- P. O. Wennberg,
- P. O. Wennberg,
- S. Yu,
- J. Zong
Affiliations
- T. E. Taylor
- Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
- C. W. O'Dell
- Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
- D. Baker
- Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
- C. Bruegge
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- A. Chang
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- L. Chapsky
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- A. Chatterjee
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- C. Cheng
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- F. Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91198 Gif-sur-Yvette, France
- D. Crisp
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- L. Dang
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- B. Drouin
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- A. Eldering
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- L. Feng
- National Centre for Earth Observation, University of Edinburgh, Edinburgh, UK
- B. Fisher
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- D. Fu
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- M. Gunson
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- V. Haemmerle
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- G. R. Keller
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- M. Kiel
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- L. Kuai
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- T. Kurosu
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- A. Lambert
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- J. Laughner
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- R. Lee
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- J. Liu
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- L. Mandrake
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- Y. Marchetti
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- G. McGarragh
- Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
- A. Merrelli
- Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, USA
- R. R. Nelson
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- G. Osterman
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- F. Oyafuso
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- P. I. Palmer
- National Centre for Earth Observation, University of Edinburgh, Edinburgh, UK
- V. H. Payne
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- R. Rosenberg
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- P. Somkuti
- College of Atmospheric and Geographic Sciences, University of Oklahoma, Norman, OK, USA
- G. Spiers
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- C. To
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- B. Weir
- Goddard Earth Sciences Technology and Research, Morgan State University, Baltimore, MD, USA
- B. Weir
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- P. O. Wennberg
- Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA
- P. O. Wennberg
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
- S. Yu
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- J. Zong
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
- DOI
- https://doi.org/10.5194/amt-16-3173-2023
- Journal volume & issue
-
Vol. 16
pp. 3173 – 3209
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.
