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.
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.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Dec 2022
Research article |
| 08 Dec 2022
| 08 Dec 2022
Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain
U.S. Geological Survey Northern Rocky Mountain Science Center, West
Glacier, MT 59936, USA
Erich H. Peitzsch
U.S. Geological Survey Northern Rocky Mountain Science Center, West
Glacier, MT 59936, USA
Eric A. Sproles
Geospatial Snow, Water, and Ice Resources Lab, Department of Earth
Sciences, Montana State University, Bozeman, MT 59717, USA
Karl W. Birkeland
USDA Forest Service National Avalanche Center, Bozeman, MT
59771, USA
Ross T. Palomaki
Geospatial Snow, Water, and Ice Resources Lab, Department of Earth
Sciences, Montana State University, Bozeman, MT 59717, USA
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Cited
16 citations as recorded by crossref.
- Climate-driven phase transitions and ensemble scenario simulations of spatiotemporal dynamics in snow cover area across the Tianshan Mountains, Central Asia M. Wang et al. https://doi.org/10.1016/j.ecolind.2025.114210
- Influence of slab depth spatial variability on skier-triggering probability and avalanche size F. Meloche et al. https://doi.org/10.1017/aog.2024.3
- Advancing snow data assimilation with a dynamic observation uncertainty D. Dunmire et al. https://doi.org/10.5194/tc-20-609-2026
- Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites Z. Hoppinen et al. https://doi.org/10.5194/tc-18-5407-2024
- Machine learning for snow depth estimation over the European Alps, using Sentinel-1 observations, meteorological forcing data and process-based model simulations L. Boeykens et al. https://doi.org/10.5194/tc-20-3187-2026
- UAS remote sensing applications to abrupt cold region hazards M. Verfaillie et al. https://doi.org/10.3389/frsen.2023.1095275
- Power Spectra’s Perspective on Meteorological Drivers of Snow Depth Multiscale Behavior over the Tibetan Plateau Y. Cao & L. Jiang https://doi.org/10.3390/land14040790
- Snow depth variability increases in a marginal snowpack as it transitions from accumulation to melt A. Marziliano et al. https://doi.org/10.1080/15230430.2025.2495518
- Spatially continuous snow depth mapping by aeroplane photogrammetry for annual peak of winter from 2017 to 2021 in open areas L. Bührle et al. https://doi.org/10.5194/tc-17-3383-2023
- Doğu Anadolu Bölgesi’nde Kar Kalınlığının Co-kriging Yöntemiyle Mekânsal Modellemesi: Bitlis, Van ve Hakkâri Örneği Ö. Güner & O. Aydın https://doi.org/10.29128/geomatik.1783742
- A machine learning approach for estimating snow depth across the European Alps from Sentinel-1 imagery D. Dunmire et al. https://doi.org/10.1016/j.rse.2024.114369
- Recent Advances in Snow Monitoring from Local to Global Scales J. Revuelto et al. https://doi.org/10.1007/s40641-025-00207-0
- Does meter-scale snow data matter for modeling alpine plant distribution? A comparison of four data sources at two resolutions A. Kollert et al. https://doi.org/10.1016/j.ecolmodel.2025.111366
- Advances in image-based estimation of snow variable: A systematic literature review on recent studies G. Demil et al. https://doi.org/10.1016/j.jhydrol.2025.132855
- Characterizing the spatial distribution of field-scale snowpack using unpiloted aerial system (UAS) lidar and structure-from-motion (SfM) photogrammetry E. Cho et al. https://doi.org/10.5194/hess-29-4539-2025
- Applications of Snow-Covered Areas from Unoccupied Aerial Systems (UAS) Visible Imagery: A Demonstration in Southeastern New Hampshire J. Johnston et al. https://doi.org/10.3390/rs17111885
16 citations as recorded by crossref.
- Climate-driven phase transitions and ensemble scenario simulations of spatiotemporal dynamics in snow cover area across the Tianshan Mountains, Central Asia M. Wang et al. https://doi.org/10.1016/j.ecolind.2025.114210
- Influence of slab depth spatial variability on skier-triggering probability and avalanche size F. Meloche et al. https://doi.org/10.1017/aog.2024.3
- Advancing snow data assimilation with a dynamic observation uncertainty D. Dunmire et al. https://doi.org/10.5194/tc-20-609-2026
- Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites Z. Hoppinen et al. https://doi.org/10.5194/tc-18-5407-2024
- Machine learning for snow depth estimation over the European Alps, using Sentinel-1 observations, meteorological forcing data and process-based model simulations L. Boeykens et al. https://doi.org/10.5194/tc-20-3187-2026
- UAS remote sensing applications to abrupt cold region hazards M. Verfaillie et al. https://doi.org/10.3389/frsen.2023.1095275
- Power Spectra’s Perspective on Meteorological Drivers of Snow Depth Multiscale Behavior over the Tibetan Plateau Y. Cao & L. Jiang https://doi.org/10.3390/land14040790
- Snow depth variability increases in a marginal snowpack as it transitions from accumulation to melt A. Marziliano et al. https://doi.org/10.1080/15230430.2025.2495518
- Spatially continuous snow depth mapping by aeroplane photogrammetry for annual peak of winter from 2017 to 2021 in open areas L. Bührle et al. https://doi.org/10.5194/tc-17-3383-2023
- Doğu Anadolu Bölgesi’nde Kar Kalınlığının Co-kriging Yöntemiyle Mekânsal Modellemesi: Bitlis, Van ve Hakkâri Örneği Ö. Güner & O. Aydın https://doi.org/10.29128/geomatik.1783742
- A machine learning approach for estimating snow depth across the European Alps from Sentinel-1 imagery D. Dunmire et al. https://doi.org/10.1016/j.rse.2024.114369
- Recent Advances in Snow Monitoring from Local to Global Scales J. Revuelto et al. https://doi.org/10.1007/s40641-025-00207-0
- Does meter-scale snow data matter for modeling alpine plant distribution? A comparison of four data sources at two resolutions A. Kollert et al. https://doi.org/10.1016/j.ecolmodel.2025.111366
- Advances in image-based estimation of snow variable: A systematic literature review on recent studies G. Demil et al. https://doi.org/10.1016/j.jhydrol.2025.132855
- Characterizing the spatial distribution of field-scale snowpack using unpiloted aerial system (UAS) lidar and structure-from-motion (SfM) photogrammetry E. Cho et al. https://doi.org/10.5194/hess-29-4539-2025
- Applications of Snow-Covered Areas from Unoccupied Aerial Systems (UAS) Visible Imagery: A Demonstration in Southeastern New Hampshire J. Johnston et al. https://doi.org/10.3390/rs17111885
Saved (final revised paper)
Latest update: 09 Jun 2026
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.
Snow depth varies across steep, complex mountain landscapes due to interactions between dynamic...
