The Cryosphere
The Cryosphere
TC
Articles | Volume 16, issue 4
Articles | Volume 16, issue 4
https://doi.org/10.5194/tc-16-1281-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-1281-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 4
Research article
 | 
11 Apr 2022
Research article |  | 11 Apr 2022

Propagating information from snow observations with CrocO ensemble data assimilation system: a 10-years case study over a snow depth observation network

Bertrand Cluzet, Matthieu Lafaysse, César Deschamps-Berger, Matthieu Vernay, and Marie Dumont

Viewed

Total article views: 2,366 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,660 620 86 2,366 56 60
  • HTML: 1,660
  • PDF: 620
  • XML: 86
  • Total: 2,366
  • BibTeX: 56
  • EndNote: 60
Views and downloads (calculated since 05 Aug 2021)
Cumulative views and downloads (calculated since 05 Aug 2021)

Viewed (geographical distribution)

Total article views: 2,366 (including HTML, PDF, and XML) Thereof 2,303 with geography defined and 63 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Nov 2024
Download
Short summary
The mountainous snow cover is highly variable at all temporal and spatial scales. Snow cover models suffer from large errors, while snowpack observations are sparse. Data assimilation combines them into a better estimate of the snow cover. A major challenge is to propagate information from observed into unobserved areas. This paper presents a spatialized version of the particle filter, in which information from in situ snow depth observations is successfully used to constrain nearby simulations.
Read more