Articles | Volume 16, issue 9
The Cryosphere, 16, 3801–3814, 2022
https://doi.org/10.5194/tc-16-3801-2022
The Cryosphere, 16, 3801–3814, 2022
https://doi.org/10.5194/tc-16-3801-2022
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 et al.

Data sets

mflanner/SNICARv3: SNICAR-ADv3 (v3.0) Mark Flanner https://doi.org/10.5281/zenodo.5176213

Model code and software

The Snow, Ice, and Aerosol Radiative Model (SNICAR) version 3 M. G. Flanner, J. Arnheim, J. M. Cook, C. Dang, C. He, X. Huang, D. Singh, S. M. Skiles, S. A. Whicker, and C. S. Zender https://github.com/mflanner/SNICARv3

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.