Articles | Volume 22, issue 24
https://doi.org/10.5194/acp-22-15793-2022
https://doi.org/10.5194/acp-22-15793-2022
Research article
 | 
16 Dec 2022
Research article |  | 16 Dec 2022

Combining short-range dispersion simulations with fine-scale meteorological ensembles: probabilistic indicators and evaluation during a 85Kr field campaign

Youness El-Ouartassy, Irène Korsakissok, Matthieu Plu, Olivier Connan, Laurent Descamps, and Laure Raynaud

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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-2022-646', Anonymous Referee #1, 22 Aug 2022
    • AC1: 'Reply on RC1', Youness El-Ouartassy, 28 Oct 2022
  • RC2: 'Comment on egusphere-2022-646', Anonymous Referee #2, 02 Sep 2022
    • AC2: 'Reply on RC2', Youness El-Ouartassy, 28 Oct 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Youness El-Ouartassy on behalf of the Authors (02 Nov 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (17 Nov 2022) by Stefano Galmarini
AR by Youness El-Ouartassy on behalf of the Authors (21 Nov 2022)
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Short summary
This work investigates the potential value of using fine-scale meteorological ensembles to represent the inherent meteorological uncertainties in atmospheric dispersion model outputs. Probabilistic scores were used to evaluate the probabilistic performance of dispersion ensembles, using an original dataset of new continuous 85Kr air concentration measurements and a well-known source term. The results show that the ensemble dispersion simulations perform better than deterministic ones.
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