Preprints
https://doi.org/10.5194/egusphere-2023-2258
https://doi.org/10.5194/egusphere-2023-2258
24 Oct 2023
 | 24 Oct 2023

Quantification of regional terrestrial biosphere CO2 flux errors in v10 OCO-2 MIP models using airborne measurements

Jeongmin Yun, Junjie Liu, Brendan Byrne, Brad Weir, Lesley E. Ott, Kathryn McKain, Bianca Baier, and Luciana V. Gatti

Abstract. Multi-inverse modeling inter-comparison projects (MIPs) provide a chance to assess the uncertainties in inversion estimates arising from various sources such as atmospheric CO2 observations, transport models, and prior fluxes. However, accurately quantifying ensemble CO2 flux errors remains challenging, often relying on the ensemble spread as a surrogate. This study proposes a method to quantify the errors of regional terrestrial biosphere CO2 flux estimates from 10 inverse models within the Orbiting Carbon Observatory-2 (OCO-2) MIP by using independent airborne CO2 measurements for the period 2015–2017. We first calculate the root-mean-square error (RMSE) between the ensemble mean of posterior CO2 concentration estimates and airborne observations and then isolate the CO2 concentration error caused solely by the ensemble mean of posterior terrestrial biosphere CO2 flux estimates by subtracting the errors of observation and transport in seven regions. Our analysis reveals significant regional variations in the average monthly RMSE over three years, ranging from 0.90 to 2.04 ppm. The ensemble flux error projected into CO2 space is a major component that accounts for 58–84 % of the mean RMSE. We further show that in five regions, the observation-based error estimates exceed the atmospheric CO2 errors computed from the ensemble spread of posterior CO2 flux estimates by 1.37–1.89 times, implying an underestimation of the actual ensemble flux error, while their magnitudes are comparable in two regions. By identifying the most sensitive areas to airborne measurements through adjoint sensitivity analysis, we find that the underestimation of flux errors is prominent in eastern parts of Australia and East Asia, western parts of Europe and Southeast Asia, and midlatitude North America, suggesting the presence of systematic biases related to anthropogenic CO2 emissions in inversion estimates. The regions with no underestimation were southeastern Alaska and northeastern South America. Our study emphasizes the value of independent airborne measurements not only for the overall evaluation of inversion performance but also for quantifying regional errors in ensemble terrestrial biosphere flux estimates.

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Journal article(s) based on this preprint

06 Feb 2025
Quantification of regional net CO2 flux errors in the Orbiting Carbon Observatory-2 (OCO-2) v10 model intercomparison project (MIP) ensemble using airborne measurements
Jeongmin Yun, Junjie Liu, Brendan Byrne, Brad Weir, Lesley E. Ott, Kathryn McKain, Bianca C. Baier, Luciana V. Gatti, and Sebastien C. Biraud
Atmos. Chem. Phys., 25, 1725–1748, https://doi.org/10.5194/acp-25-1725-2025,https://doi.org/10.5194/acp-25-1725-2025, 2025
Short summary
Jeongmin Yun, Junjie Liu, Brendan Byrne, Brad Weir, Lesley E. Ott, Kathryn McKain, Bianca Baier, and Luciana V. Gatti

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2023-2258', Andrew Jacobson, 15 Nov 2023
    • AC1: 'Reply on CC1', Jeongmin Yun, 17 Dec 2023
  • RC1: 'Comment on egusphere-2023-2258', Anonymous Referee #1, 16 Jan 2024
  • RC2: 'Comment on egusphere-2023-2258', Anonymous Referee #2, 25 Feb 2024

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2023-2258', Andrew Jacobson, 15 Nov 2023
    • AC1: 'Reply on CC1', Jeongmin Yun, 17 Dec 2023
  • RC1: 'Comment on egusphere-2023-2258', Anonymous Referee #1, 16 Jan 2024
  • RC2: 'Comment on egusphere-2023-2258', Anonymous Referee #2, 25 Feb 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Jeongmin Yun on behalf of the Authors (13 Apr 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (24 Apr 2024) by Christoph Gerbig
RR by Anonymous Referee #1 (17 May 2024)
ED: Reconsider after major revisions (18 Jun 2024) by Christoph Gerbig
AR by Jeongmin Yun on behalf of the Authors (30 Jun 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (29 Jul 2024) by Christoph Gerbig
RR by Anonymous Referee #1 (27 Aug 2024)
ED: Reconsider after major revisions (06 Sep 2024) by Christoph Gerbig
AR by Jeongmin Yun on behalf of the Authors (04 Oct 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (22 Oct 2024) by Christoph Gerbig
RR by Anonymous Referee #1 (05 Nov 2024)
ED: Publish as is (21 Nov 2024) by Christoph Gerbig
AR by Jeongmin Yun on behalf of the Authors (26 Nov 2024)  Manuscript 

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Jeongmin Yun on behalf of the Authors (29 Jan 2025)   Author's adjustment   Manuscript
EA: Adjustments approved (29 Jan 2025) by Christoph Gerbig

Journal article(s) based on this preprint

06 Feb 2025
Quantification of regional net CO2 flux errors in the Orbiting Carbon Observatory-2 (OCO-2) v10 model intercomparison project (MIP) ensemble using airborne measurements
Jeongmin Yun, Junjie Liu, Brendan Byrne, Brad Weir, Lesley E. Ott, Kathryn McKain, Bianca C. Baier, Luciana V. Gatti, and Sebastien C. Biraud
Atmos. Chem. Phys., 25, 1725–1748, https://doi.org/10.5194/acp-25-1725-2025,https://doi.org/10.5194/acp-25-1725-2025, 2025
Short summary
Jeongmin Yun, Junjie Liu, Brendan Byrne, Brad Weir, Lesley E. Ott, Kathryn McKain, Bianca Baier, and Luciana V. Gatti
Jeongmin Yun, Junjie Liu, Brendan Byrne, Brad Weir, Lesley E. Ott, Kathryn McKain, Bianca Baier, and Luciana V. Gatti

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Short summary
Multi-inverse modeling inter-comparison projects offer a chance to assess uncertainties in inversion estimates arising from various sources. This study proposes a method to quantify errors of regional terrestrial biosphere CO2 flux estimates from an inverse model ensemble by using airborne CO2 measurements. Our observation-based error estimates exceed the ensemble spread of flux estimates in regions with high anthropogenic emission regions, suggesting systematic biases in inversion estimates.
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