Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain

Miller, Zachary S.; Peitzsch, Erich H.; Sproles, Eric A.; Birkeland, Karl W.; Palomaki, Ross T.

doi:https://doi.org/10.5194/tc-16-4907-2022

Articles | Volume 16, issue 12

https://doi.org/10.5194/tc-16-4907-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-16-4907-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 16, issue 12

Research article

|

08 Dec 2022

Research article |

| 08 Dec 2022

Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain

Zachary S. Miller, Erich H. Peitzsch, Eric A. Sproles, Karl W. Birkeland, and Ross T. Palomaki

Data sets

2020 winter timeseries of UAS derived digital surface models (DSMs) from the Hourglass study site, Bridger Mountains, Montana, USA Zachary S. Miller, Erich H. Peitzsch, Eric Sproles, Ross T. Palomaki, and Karl W. Birkeland https://doi.org/10.5066/P9YCIA1R

Short summary

Snow depth varies across steep, complex mountain landscapes due to interactions between dynamic natural processes. Our study of a winter time series of high-resolution snow depth maps found that spatial resolutions greater than 0.5 m do not capture the complete patterns of snow depth spatial variability at a couloir study site in the Bridger Range of Montana, USA. The results of this research have the potential to reduce uncertainty associated with snowpack and snow water resource analysis.