Articles | Volume 16, issue 21
Model evaluation paper
10 Nov 2023
Model evaluation paper |  | 10 Nov 2023

Implementation of a satellite-based tool for the quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: forward modelling evaluation against near-surface and satellite data

Angel Liduvino Vara-Vela, Christoffer Karoff, Noelia Rojas Benavente, and Janaina P. Nascimento


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2023-9', Juan Antonio Añel, 05 May 2023
    • AC1: 'Reply on CEC1', Angel Liduvino Vara-Vela, 05 May 2023
      • EC1: 'Reply on AC1', Fiona O'Connor, 05 May 2023
        • AC2: 'Reply on EC1', Angel Liduvino Vara-Vela, 06 May 2023
          • CEC2: 'Reply on AC2', Juan Antonio Añel, 10 May 2023
  • RC1: 'Comment on gmd-2023-9', Anonymous Referee #1, 12 May 2023
    • AC3: 'Reply on RC1', Angel Liduvino Vara-Vela, 25 May 2023
  • RC2: 'Comment on gmd-2023-9', Anonymous Referee #2, 01 Jun 2023
    • AC4: 'Reply on RC2', Angel Liduvino Vara-Vela, 08 Jun 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Angel Liduvino Vara-Vela on behalf of the Authors (16 Jun 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (14 Jul 2023) by Fiona O'Connor
RR by Anonymous Referee #2 (20 Jul 2023)
ED: Publish as is (01 Oct 2023) by Fiona O'Connor
AR by Angel Liduvino Vara-Vela on behalf of the Authors (02 Oct 2023)  Author's response   Manuscript 
Short summary
A 1-year simulation of atmospheric CH4 over Europe is performed and evaluated against observations based on the TROPOspheric Monitoring Instrument (TROPOMI). A good general model–observation agreement is found, with discrepancies reaching their minimum and maximum values during the summer peak season and winter months, respectively. A huge and under-explored potential for CH4 inverse modeling using improved TROPOMI XCH4 data sets in large-scale applications is identified.