The missing drifts: snow density heterogeneity from wind-packing exacerbates systematic underestimation of deep snow storage from the scale of nivation hollows to mountain ranges

Boardman, Elijah N.; Boardman, Karen L.; Jones, Christopher A.; Shipman, Sean D.; Whiting, John A.; Boardman, Joseph W.; Harpold, Adrian A.

doi:10.5194/tc-20-4877-2026

Articles | Volume 20, issue 9

https://doi.org/10.5194/tc-20-4877-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-20-4877-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 9

Research article

|

01 Sep 2026

Research article |

| 01 Sep 2026

The missing drifts: snow density heterogeneity from wind-packing exacerbates systematic underestimation of deep snow storage from the scale of nivation hollows to mountain ranges

Elijah N. Boardman, Karen L. Boardman, Christopher A. Jones, Sean D. Shipman, John A. Whiting, Joseph W. Boardman, and Adrian A. Harpold

Supplement

https://doi.org/10.5194/tc-20-4877-2026-supplement

Data sets

Data and Code for Wind River Range Snow Density Heterogeneity Study E. N. Boardman https://doi.org/10.5281/zenodo.17114675

Model code and software

Data and Code for Wind River Range Snow Density Heterogeneity Study E. N. Boardman https://doi.org/10.5281/zenodo.17114675

Short summary

Deep wind drifts are an important component of the mountain snowpack, but drifts are underrepresented by most datasets. Our synthesis of field surveys, statistical modeling, and remote sensing quantifies the contribution of drift depth and bulk density to snowpack heterogeneity across scales, from the vertical structure at a single location to the kilometer-scale patterning of snow across a mountain range.