Articles | Volume 23, issue 8
https://doi.org/10.5194/nhess-23-2821-2023
https://doi.org/10.5194/nhess-23-2821-2023
Research article
 | 
18 Aug 2023
Research article |  | 18 Aug 2023

Assimilation of Meteosat Third Generation (MTG) Lightning Imager (LI) pseudo-observations in AROME-France – proof of concept

Felix Erdmann, Olivier Caumont, and Eric Defer

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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-2022-637', Anonymous Referee #1, 19 Aug 2022
    • AC1: 'Reply on RC1', Felix Erdmann, 31 Mar 2023
  • RC2: 'Comment on egusphere-2022-637', Anonymous Referee #2, 27 Sep 2022
    • AC2: 'Reply on RC2', Felix Erdmann, 31 Mar 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (25 Apr 2023) by Gregor C. Leckebusch
AR by Felix Erdmann on behalf of the Authors (26 Apr 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (10 May 2023) by Gregor C. Leckebusch
RR by Anonymous Referee #1 (25 May 2023)
RR by Anonymous Referee #2 (25 May 2023)
ED: Publish subject to minor revisions (review by editor) (08 Jun 2023) by Gregor C. Leckebusch
AR by Felix Erdmann on behalf of the Authors (27 Jun 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (28 Jun 2023) by Gregor C. Leckebusch
AR by Felix Erdmann on behalf of the Authors (29 Jun 2023)
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Short summary
This work develops a novel lightning data assimilation (LDA) technique to make use of Meteosat Third Generation (MTG) Lightning Imager (LI) data in a regional, convection-permitting numerical weather prediction model. The approach combines statistical Bayesian and 3-dimensional variational methods. Our LDA can promote missing convection and suppress spurious convection in the initial state of the model, and it has similar skill to the operational radar data assimilation for rainfall forecasts.
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