Articles | Volume 18, issue 8
https://doi.org/10.5194/essd-18-6171-2026
https://doi.org/10.5194/essd-18-6171-2026
Data description article
 | 
26 Aug 2026
Data description article |  | 26 Aug 2026

TCOM-CFC11 and TCOM-CFC12: a gap-free, observationally constrained global dataset of stratospheric CFC-11 and CFC-12 profiles (v2.0)

Sandip S. Dhomse and Martyn P. Chipperfield

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2026-3', Chris Boone, 13 Apr 2026
    • AC1: 'Reply on RC1', Sandip Dhomse, 07 Jul 2026
  • RC2: 'Comment on essd-2026-3', Anonymous Referee #2, 20 Apr 2026
    • AC2: 'Reply on RC2', Sandip Dhomse, 07 Jul 2026

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Sandip Dhomse on behalf of the Authors (07 Jul 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (03 Aug 2026) by Iolanda Ialongo
AR by Sandip Dhomse on behalf of the Authors (11 Aug 2026)  Manuscript 
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Short summary
We have developed an innovative methodology that uses machine learning to correct errors in chemical models by using satellite data as a guide. In this latest update, we detail improvements to our process for creating a gap-free data of two major ozone-depleting substances: CFC-11 and CFC-12. By combining the strengths of both chemical models and satellites, we have produced a reliable, global dataset that allows researchers to track long-term trends and better evaluate the chemical models.
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