Articles | Volume 17, issue 8
https://doi.org/10.5194/tc-17-3329-2023
https://doi.org/10.5194/tc-17-3329-2023
Research article
 | 
17 Aug 2023
Research article |  | 17 Aug 2023

Exploring the potential of thermal infrared remote sensing to improve a snowpack model through an observing system simulation experiment

Esteban Alonso-González, Simon Gascoin, Sara Arioli, and Ghislain Picard

Viewed

Total article views: 1,387 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
965 367 55 1,387 35 39 38
  • HTML: 965
  • PDF: 367
  • XML: 55
  • Total: 1,387
  • Supplement: 35
  • BibTeX: 39
  • EndNote: 38
Views and downloads (calculated since 01 Dec 2022)
Cumulative views and downloads (calculated since 01 Dec 2022)

Viewed (geographical distribution)

Total article views: 1,387 (including HTML, PDF, and XML) Thereof 1,356 with geography defined and 31 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 08 May 2024
Download
Short summary
Data assimilation techniques are a promising approach to improve snowpack simulations in remote areas that are difficult to monitor. This paper studies the ability of satellite-observed land surface temperature to improve snowpack simulations through data assimilation. We show that it is possible to improve snowpack simulations, but the temporal resolution of the observations and the algorithm used are critical to obtain satisfactory results.