Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 22, issue 24
Articles | Volume 22, issue 24
https://doi.org/10.5194/acp-22-15793-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-15793-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 24
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

Viewed

Total article views: 1,863 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,503 309 51 1,863 37 34
  • HTML: 1,503
  • PDF: 309
  • XML: 51
  • Total: 1,863
  • BibTeX: 37
  • EndNote: 34
Views and downloads (calculated since 04 Aug 2022)
Cumulative views and downloads (calculated since 04 Aug 2022)

Viewed (geographical distribution)

Total article views: 1,863 (including HTML, PDF, and XML) Thereof 1,864 with geography defined and -1 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 16 Jul 2024
Download
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.
Read more
Altmetrics
Final-revised paper
Preprint