Articles | Volume 18, issue 11
https://doi.org/10.5194/tc-18-5407-2024
© Author(s) 2024. 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-18-5407-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Nov 2024
Research article |
| 25 Nov 2024
| 25 Nov 2024
Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites
Zachary Hoppinen
CORRESPONDING AUTHOR
Boise State University, Department of Geosciences, 1910 University Drive, Boise, ID 83725, USA
Cold Regions Research and Engineering Laboratory, Engineer Research and Development Center, United States Army, 72 Lyme Road, Hanover, NH 03755, USA
Ross T. Palomaki
Institute of Arctic and Alpine Research, University of Colorado, 4001 Discovery Dr, Boulder, CO 80303, USA
George Brencher
Civil and Environmental Engineering Department, University of Washington, Seattle, WA 98195, USA
Devon Dunmire
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Department of Atmospheric and Oceanic Sciences, CU Boulder, 4001 Discovery Dr, Boulder, CO 80303, USA
Eric Gagliano
Civil and Environmental Engineering Department, University of Washington, Seattle, WA 98195, USA
Adrian Marziliano
Department of Civil, Construction, and Environmental Engineering, University of New Mexico, Albuquerque, NM 87131, USA
Jack Tarricone
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20770, USA
NASA Postdoctoral Program, NASA Goddard Space Flight Center, Greenbelt, MD 20770, USA
Hans-Peter Marshall
Boise State University, Department of Geosciences, 1910 University Drive, Boise, ID 83725, USA
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Cited
16 citations as recorded by crossref.
- Scale patterns of the Sentinel-1 SAR-based snow depth product compared with station measurements and airborne LiDAR observations J. Ying et al.
- Creeping snow drought threatens Canada’s water supply R. Sarpong et al.
- Hybrid approach for estimating snow water equivalent in Siberian basins using GRACE and climate data H. Mohasseb & S. Yi
- Snow Depth Estimation Based on STCTNet for Sentinel-1 and Multisource Data Q. Cheng et al.
- Evaluation of high-resolution snowpack simulations from global datasets and comparison with Sentinel-1 snow depth retrievals in the Sierra Nevada, USA L. Sourp et al.
- Celestial sculptors. Brief remarks on the landforms of the snow surface of mountain and polar region D. Sinev
- Impact of Surface-Volume Scattering Interaction on C-Band Radar Depolarization Signal in Snow-Covered Regions C. Xiong et al.
- Advances and prospects in reconstruction approaches for snow cover mapping using polar-orbiting satellites J. Zhang et al.
- Advancing snow data assimilation with a dynamic observation uncertainty D. Dunmire et al.
- Evaluating the utility of Sentinel-1 in a Data Assimilation System for estimating snow depth in a mountainous basin B. Mirza et al.
- Can Sentinel-1 reliably provide regional-scale information on avalanche activity S. Kaushik et al.
- C-Band Radar-Based Improved Snow Depth Estimation (C-RISE) in the Indian Western Himalayas and Colorado Rocky Mountains R. Chandra Prabha et al.
- Investigating the Impact of Optical Snow Cover Data on L-Band InSAR Snow Water Equivalent Retrievals J. Tarricone et al.
- Snow depth measurements from Arctic tundra and boreal forest collected during NASA SnowEx Alaska campaign S. Stuefer et al.
- Snow depth derived from Sentinel-1 compared to in situ observations in northern Finland A. Lemos & A. Riihelä
- A Snow Depth Retrieval Method Based on Super-Resolution Brightness Temperature Reconstruction and Multimodal Feature Synergy Y. Bai et al.
16 citations as recorded by crossref.
- Scale patterns of the Sentinel-1 SAR-based snow depth product compared with station measurements and airborne LiDAR observations J. Ying et al.
- Creeping snow drought threatens Canada’s water supply R. Sarpong et al.
- Hybrid approach for estimating snow water equivalent in Siberian basins using GRACE and climate data H. Mohasseb & S. Yi
- Snow Depth Estimation Based on STCTNet for Sentinel-1 and Multisource Data Q. Cheng et al.
- Evaluation of high-resolution snowpack simulations from global datasets and comparison with Sentinel-1 snow depth retrievals in the Sierra Nevada, USA L. Sourp et al.
- Celestial sculptors. Brief remarks on the landforms of the snow surface of mountain and polar region D. Sinev
- Impact of Surface-Volume Scattering Interaction on C-Band Radar Depolarization Signal in Snow-Covered Regions C. Xiong et al.
- Advances and prospects in reconstruction approaches for snow cover mapping using polar-orbiting satellites J. Zhang et al.
- Advancing snow data assimilation with a dynamic observation uncertainty D. Dunmire et al.
- Evaluating the utility of Sentinel-1 in a Data Assimilation System for estimating snow depth in a mountainous basin B. Mirza et al.
- Can Sentinel-1 reliably provide regional-scale information on avalanche activity S. Kaushik et al.
- C-Band Radar-Based Improved Snow Depth Estimation (C-RISE) in the Indian Western Himalayas and Colorado Rocky Mountains R. Chandra Prabha et al.
- Investigating the Impact of Optical Snow Cover Data on L-Band InSAR Snow Water Equivalent Retrievals J. Tarricone et al.
- Snow depth measurements from Arctic tundra and boreal forest collected during NASA SnowEx Alaska campaign S. Stuefer et al.
- Snow depth derived from Sentinel-1 compared to in situ observations in northern Finland A. Lemos & A. Riihelä
- A Snow Depth Retrieval Method Based on Super-Resolution Brightness Temperature Reconstruction and Multimodal Feature Synergy Y. Bai et al.
Saved (final revised paper)
Latest update: 17 May 2026
Short summary
This study uses radar imagery from the Sentinel-1 satellite to derive snow depth from increases in the returning energy. These retrieved depths are then compared to nine lidar-derived snow depths across the western United State to assess the ability of this technique to be used to monitor global snow distributions. We also qualitatively compare the changes in underlying Sentinel-1 amplitudes against both the total lidar snow depths and nine automated snow monitoring stations.
This study uses radar imagery from the Sentinel-1 satellite to derive snow depth from increases...
