Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 23, issue 8
Articles | Volume 23, issue 8
https://doi.org/10.5194/nhess-23-2821-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-23-2821-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 8
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

Viewed

Total article views: 3,729 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,379 1,216 134 3,729 155 277
  • HTML: 2,379
  • PDF: 1,216
  • XML: 134
  • Total: 3,729
  • BibTeX: 155
  • EndNote: 277
Views and downloads (calculated since 28 Jul 2022)
Cumulative views and downloads (calculated since 28 Jul 2022)

Viewed (geographical distribution)

Total article views: 3,729 (including HTML, PDF, and XML) Thereof 3,631 with geography defined and 98 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 28 May 2026
Download
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.
Read more
Share
Altmetrics
Final-revised paper
Preprint