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


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • AC1: 'Comment on gmd-2021-106', Joel Thanwerdas, 28 May 2021
  • CEC1: 'Comment on gmd-2021-106', Astrid Kerkweg, 08 Jun 2021
  • RC1: 'Comment on gmd-2021-106', Anonymous Referee #1, 27 Jul 2021
  • RC2: 'Overall comment', Peter Rayner, 23 Feb 2022
  • RC3: 'Comment on gmd-2021-106', Anonymous Referee #3, 24 Feb 2022
  • AC2: 'Author final response', Joel Thanwerdas, 21 Mar 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Joel Thanwerdas on behalf of the Authors (21 Mar 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (26 May 2022) by Richard Neale
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.