Articles | Volume 18, issue 20
https://doi.org/10.5194/amt-18-5619-2025
https://doi.org/10.5194/amt-18-5619-2025
Research article
 | 
21 Oct 2025
Research article |  | 21 Oct 2025

Extension of the Complete Data Fusion algorithm to tomographic retrieval products

Cecilia Tirelli, Simone Ceccherini, Samuele Del Bianco, Bernd Funke, Michael Höpfner, Ugo Cortesi, and Piera Raspollini

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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 egusphere-2025-1283', Anonymous Referee #1, 30 Apr 2025
    • AC1: 'Reply on RC1', Cecilia Tirelli, 20 Aug 2025
  • RC2: 'Comment on egusphere-2025-1283', Anonymous Referee #2, 02 Jul 2025
    • AC2: 'Reply on RC2', Cecilia Tirelli, 20 Aug 2025

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Cecilia Tirelli on behalf of the Authors (20 Aug 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to technical corrections (02 Sep 2025) by Mark Weber
AR by Cecilia Tirelli on behalf of the Authors (04 Sep 2025)  Author's response   Manuscript 
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Short summary
The Complete Data Fusion is an a posteriori method used to combine remote sensing products from independent observations of the same or proximate air masses. In this study, we extend the algorithm’s applicability to two-dimensional products, testing it with simulated ozone datasets from nadir and limb measurements. Our results show that the exploitation of the tomographic capabilities of future atmospheric sensors maximizes the information extracted from complementary datasets.
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