The Cryosphere
The Cryosphere
TC
Articles | Volume 16, issue 9
Articles | Volume 16, issue 9
https://doi.org/10.5194/tc-16-3801-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-3801-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 9
Research article
 | 
22 Sep 2022
Research article |  | 22 Sep 2022

Sensitivity of modeled snow grain size retrievals to solar geometry, snow particle asphericity, and snowpack impurities

Zachary Fair, Mark Flanner, Adam Schneider, and S. McKenzie Skiles

Viewed

Total article views: 1,500 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,101 351 48 1,500 45 51
  • HTML: 1,101
  • PDF: 351
  • XML: 48
  • Total: 1,500
  • BibTeX: 45
  • EndNote: 51
Views and downloads (calculated since 17 May 2022)
Cumulative views and downloads (calculated since 17 May 2022)

Viewed (geographical distribution)

Total article views: 1,500 (including HTML, PDF, and XML) Thereof 1,420 with geography defined and 80 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 21 Feb 2025
Download
Short summary
Snow grain size is important to determine the age and structure of snow, but it is difficult to measure. Snow grain size can be found from airborne and spaceborne observations by measuring near-infrared energy reflected from snow. In this study, we use the SNICAR radiative transfer model and a Monte Carlo model to examine how snow grain size measurements change with snow structure and solar zenith angle. We show that improved understanding of these variables improves snow grain size precision.
Read more
Share