The Cryosphere
The Cryosphere
TC
Articles | Volume 16, issue 9
Articles | Volume 16, issue 9
https://doi.org/10.5194/tc-16-3489-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-3489-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 9
Research article
 | 
01 Sep 2022
Research article |  | 01 Sep 2022

Large-scale snow data assimilation using a spatialized particle filter: recovering the spatial structure of the particles

Jean Odry, Marie-Amélie Boucher, Simon Lachance-Cloutier, Richard Turcotte, and Pierre-Yves St-Louis

Viewed

Total article views: 1,589 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,035 483 71 1,589 55 49
  • HTML: 1,035
  • PDF: 483
  • XML: 71
  • Total: 1,589
  • BibTeX: 55
  • EndNote: 49
Views and downloads (calculated since 27 Oct 2021)
Cumulative views and downloads (calculated since 27 Oct 2021)

Viewed (geographical distribution)

Total article views: 1,589 (including HTML, PDF, and XML) Thereof 1,536 with geography defined and 53 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 21 Nov 2024
Download
Short summary
The research deals with the assimilation of in-situ local snow observations in a large-scale spatialized snow modeling framework over the province of Quebec (eastern Canada). The methodology is based on proposing multiple spatialized snow scenarios using the snow model and weighting them according to the available observations. The paper especially focuses on the spatial coherence of the snow scenario proposed in the framework.
Read more