Articles | Volume 18, issue 7
https://doi.org/10.5194/tc-18-3253-2024
https://doi.org/10.5194/tc-18-3253-2024
Research article
 | 
22 Jul 2024
Research article |  | 22 Jul 2024

Spatially distributed snow depth, bulk density, and snow water equivalent from ground-based and airborne sensor integration at Grand Mesa, Colorado, USA

Tate G. Meehan, Ahmad Hojatimalekshah, Hans-Peter Marshall, Elias J. Deeb, Shad O'Neel, Daniel McGrath, Ryan W. Webb, Randall Bonnell, Mark S. Raleigh, Christopher Hiemstra, and Kelly Elder

Viewed

Total article views: 899 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
629 229 41 899 34 28
  • HTML: 629
  • PDF: 229
  • XML: 41
  • Total: 899
  • BibTeX: 34
  • EndNote: 28
Views and downloads (calculated since 20 Sep 2023)
Cumulative views and downloads (calculated since 20 Sep 2023)

Viewed (geographical distribution)

Total article views: 899 (including HTML, PDF, and XML) Thereof 878 with geography defined and 21 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 22 Jul 2024
Download
Short summary
Snow water equivalent (SWE) is a critical parameter for yearly water supply forecasting and can be calculated by multiplying the snow depth by the snow density. We combined high-spatial-resolution snow depth information with ground-based radar measurements to solve for snow density. Extrapolated density estimates over our study area resolved detailed patterns that agree with the known interactions of snow with wind, terrain, and vegetation and were utilized in the calculation of SWE.