Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 22, issue 9
Articles | Volume 22, issue 9
https://doi.org/10.5194/nhess-22-2943-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-22-2943-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 9
Research article
 | 
06 Sep 2022
Research article |  | 06 Sep 2022

A satellite lightning observation operator for storm-scale numerical weather prediction

Pauline Combarnous, Felix Erdmann, Olivier Caumont, Éric Defer, and Maud Martet

Viewed

Total article views: 2,029 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,471 491 67 2,029 54 45
  • HTML: 1,471
  • PDF: 491
  • XML: 67
  • Total: 2,029
  • BibTeX: 54
  • EndNote: 45
Views and downloads (calculated since 01 Mar 2022)
Cumulative views and downloads (calculated since 01 Mar 2022)

Viewed (geographical distribution)

Total article views: 2,029 (including HTML, PDF, and XML) Thereof 1,894 with geography defined and 135 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Dec 2024
Download
Short summary
The objective of this study is to prepare the assimilation of satellite lightning data in the French regional numerical weather prediction system. The assimilation of lightning data requires an observation operator, based on empirical relationships between the lightning observations and a set of proxies derived from the numerical weather prediction system variables. We fit machine learning regression models to our data to yield those relationships and to investigate the best proxy for lightning.
Read more
Altmetrics
Final-revised paper
Preprint