Variational inverse modeling within the Community Inversion Framework v1.1 to assimilate δ13C(CH4) and CH4: a case study with model LMDz-SACS

Thanwerdas, Joël; Saunois, Marielle; Berchet, Antoine; Pison, Isabelle; Vaughn, Bruce H.; Michel, Sylvia Englund; Bousquet, Philippe

doi:https://doi.org/10.5194/gmd-15-4831-2022

Articles | Volume 15, issue 12

https://doi.org/10.5194/gmd-15-4831-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-15-4831-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 12

Development and technical paper

|

27 Jun 2022

Development and technical paper |

| 27 Jun 2022

Variational inverse modeling within the Community Inversion Framework v1.1 to assimilate δ¹³C(CH₄) and CH₄: a case study with model LMDz-SACS

Joël Thanwerdas, Marielle Saunois, Antoine Berchet, Isabelle Pison, Bruce H. Vaughn, Sylvia Englund Michel, and Philippe Bousquet

Supplement

https://doi.org/10.5194/gmd-15-4831-2022-supplement

Model code and software

The Community Inversion Framework: codes and documentation Antoine Berchet, Espen Sollum, Isabelle Pison, Rona L. Thompson, Joël Thanwerdas, Audrey Fortems-Cheiney, Jacob C. A. van Peet, Elise Potier, Frédéric Chevallier, Grégoire Broquet, and Adrien Berchet https://doi.org/10.5281/zenodo.6304912

Short summary

Estimating CH₄ sources by exploiting observations within an inverse modeling framework is a powerful approach. Here, a new system designed to assimilate δ¹³C(CH₄) observations together with CH₄ observations is presented. By optimizing both the emissions and associated source signatures of multiple emission categories, this new system can efficiently differentiate the co-located emission categories and provide estimates of CH₄ sources that are consistent with isotopic data.