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https://doi.org/10.5194/egusphere-2025-109
https://doi.org/10.5194/egusphere-2025-109
30 Jan 2025
 | 30 Jan 2025

Towards the Assimilation of Atmospheric CO2 Concentration Data in a Land Surface Model using Adjoint-free Variational Methods

Simon Beylat, Nina Raoult, Cédric Bacour, Natalie Douglas, Tristan Quaife, Vladislav Bastrikov, Peter Julien Rayner, and Philippe Peylin

Abstract. A comprehensive understanding and an accurate modelling of the terrestrial carbon cycle, are of paramount importance to improve projections of the global carbon cycle and more accurately gauge its impact on global climate systems. Land Surface Models, which have become an important component of weather and climate applications, simulate key aspects of the terrestrial carbon cycle such as photosynthesis and respiration. These models rely on parameterisations that necessitate to be carefully calibrated. In this study we explore the assimilation of atmospheric CO2 concentration data for parameter calibration of the ORCHIDEE Land Surface Model using 4DEnVar, an adjoint-free ensemble-variational data assimilation method. By circumventing the challenges associated with developing and maintaining tangent linear and adjoint models, the 4DEnVar method offers a very promising alternative. Using synthetic observations generated through a twin experiment, we demonstrate the ability of 4DEnVar to assimilate atmospheric CO2 concentration for model parameter calibration. We then compare the results to a 4DVar method that uses finite differences to estimate tangent linear and adjoint models, which reveal that 4DEnVar is superior in terms of computational efficiency and fit to the observations as well as parameter recovery.

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Journal article(s) based on this preprint

21 Oct 2025
Towards the assimilation of atmospheric CO2 concentration data in a land surface model using adjoint-free variational methods
Simon Beylat, Nina Raoult, Cédric Bacour, Natalie Douglas, Tristan Quaife, Vladislav Bastrikov, Peter J. Rayner, and Philippe Peylin
Geosci. Model Dev., 18, 7501–7527, https://doi.org/10.5194/gmd-18-7501-2025,https://doi.org/10.5194/gmd-18-7501-2025, 2025
Short summary
Simon Beylat, Nina Raoult, Cédric Bacour, Natalie Douglas, Tristan Quaife, Vladislav Bastrikov, Peter Julien Rayner, and Philippe Peylin

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2025-109', Anonymous Referee #1, 11 Mar 2025
    • AC1: 'Reply on RC1', Simon Beylat, 05 Jun 2025
  • RC2: 'Comment on egusphere-2025-109', Anonymous Referee #2, 26 Apr 2025
    • AC3: 'Reply on RC2', Simon Beylat, 05 Jun 2025
  • RC3: 'Comment on egusphere-2025-109', Anonymous Referee #3, 29 Apr 2025
    • AC2: 'Reply on RC3', Simon Beylat, 05 Jun 2025

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2025-109', Anonymous Referee #1, 11 Mar 2025
    • AC1: 'Reply on RC1', Simon Beylat, 05 Jun 2025
  • RC2: 'Comment on egusphere-2025-109', Anonymous Referee #2, 26 Apr 2025
    • AC3: 'Reply on RC2', Simon Beylat, 05 Jun 2025
  • RC3: 'Comment on egusphere-2025-109', Anonymous Referee #3, 29 Apr 2025
    • AC2: 'Reply on RC3', Simon Beylat, 05 Jun 2025

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Simon Beylat on behalf of the Authors (05 Jun 2025)  Author's response 
EF by Mario Ebel (06 Jun 2025)  Manuscript   Author's tracked changes 
ED: Referee Nomination & Report Request started (06 Jun 2025) by Marko Scholze
RR by Anonymous Referee #2 (06 Jun 2025)
ED: Reconsider after major revisions (09 Jul 2025) by Marko Scholze
AR by Simon Beylat on behalf of the Authors (24 Jul 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (31 Jul 2025) by Marko Scholze
AR by Simon Beylat on behalf of the Authors (04 Aug 2025)  Manuscript 

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Simon Beylat on behalf of the Authors (16 Oct 2025)   Author's adjustment   Manuscript
EA: Adjustments approved (16 Oct 2025) by Marko Scholze

Journal article(s) based on this preprint

21 Oct 2025
Towards the assimilation of atmospheric CO2 concentration data in a land surface model using adjoint-free variational methods
Simon Beylat, Nina Raoult, Cédric Bacour, Natalie Douglas, Tristan Quaife, Vladislav Bastrikov, Peter J. Rayner, and Philippe Peylin
Geosci. Model Dev., 18, 7501–7527, https://doi.org/10.5194/gmd-18-7501-2025,https://doi.org/10.5194/gmd-18-7501-2025, 2025
Short summary
Simon Beylat, Nina Raoult, Cédric Bacour, Natalie Douglas, Tristan Quaife, Vladislav Bastrikov, Peter Julien Rayner, and Philippe Peylin
Simon Beylat, Nina Raoult, Cédric Bacour, Natalie Douglas, Tristan Quaife, Vladislav Bastrikov, Peter Julien Rayner, and Philippe Peylin

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Short summary
Land surface models are important tools for understanding and predicting the land components of the carbon cycle. Atmospheric CO2 concentration data is a valuable source of information that can be used to improve the accuracy of these models. In this study, we present a statistical method named 4DEnVar to calibrate parameters of a land surface model using this data. We show that this method is easy to implement and more efficient and accurate than traditional methods.
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