Articles | Volume 23, issue 9
https://doi.org/10.5194/acp-23-5317-2023
https://doi.org/10.5194/acp-23-5317-2023
Technical note
 | 
11 May 2023
Technical note |  | 11 May 2023

Technical note: Improving the European air quality forecast of the Copernicus Atmosphere Monitoring Service using machine learning techniques

Jean-Maxime Bertrand, Frédérik Meleux, Anthony Ung, Gaël Descombes, and Augustin Colette

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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 acp-2022-767', Anonymous Referee #1, 15 Dec 2022
  • RC2: 'Comment on acp-2022-767', Anonymous Referee #2, 19 Dec 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Jean-Maxime Bertrand on behalf of the Authors (17 Mar 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (20 Mar 2023) by Stefano Galmarini
AR by Jean-Maxime Bertrand on behalf of the Authors (28 Mar 2023)
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Short summary
Post-processing methods based on machine learning algorithms were applied to refine the...
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