Articles | Volume 18, issue 2
https://doi.org/10.5194/tc-18-559-2024
© 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-18-559-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Snow water equivalent retrieval over Idaho – Part 1: Using Sentinel-1 repeat-pass interferometry
Shadi Oveisgharan
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr, Pasadena, CA, USA
Robert Zinke
Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr, Pasadena, CA, USA
Zachary Hoppinen
Boise State University, Department of Geosciences, 1295 University Drive, Boise, ID, USA
Hans Peter Marshall
Boise State University, Department of Geosciences, 1295 University Drive, Boise, ID, USA
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Zachary Hoppinen, Shadi Oveisgharan, Hans-Peter Marshall, Ross Mower, Kelly Elder, and Carrie Vuyovich
The Cryosphere, 18, 575–592, https://doi.org/10.5194/tc-18-575-2024, https://doi.org/10.5194/tc-18-575-2024, 2024
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We used changes in radar echo travel time from multiple airborne flights to estimate changes in snow depths across Idaho for two winters. We compared our radar-derived retrievals to snow pits, weather stations, and a 100 m resolution numerical snow model. We had a strong Pearson correlation and root mean squared error of 10 cm relative to in situ measurements. Our retrievals also correlated well with our model, especially in regions of dry snow and low tree coverage.
Kajsa Holland-Goon, Randall Bonnell, Daniel McGrath, W. Brad Baxter, Tate Meehan, Ryan Webb, Chris Larsen, Hans-Peter Marshall, Megan Mason, and Carrie Vuyovich
EGUsphere, https://doi.org/10.5194/egusphere-2025-2435, https://doi.org/10.5194/egusphere-2025-2435, 2025
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As part of the NASA SnowEx23 campaign, we conducted detailed snowpack experiments in Alaska’s boreal forests and Arctic tundra. We collected ground-penetrating radar measurements of snow depth along 44 short transects. We then excavated the snowpack from below the transects and measured snow depth, noting any vegetation and void spaces. We used the detailed in situ measurements to evaluate uncertainties in ground-penetrating radar and airborne lidar methods for snow depth retrieval.
Rainey Aberle, Ellyn Enderlin, Shad O'Neel, Caitlyn Florentine, Louis Sass, Adam Dickson, Hans-Peter Marshall, and Alejandro Flores
The Cryosphere, 19, 1675–1693, https://doi.org/10.5194/tc-19-1675-2025, https://doi.org/10.5194/tc-19-1675-2025, 2025
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Tracking seasonal snow on glaciers is critical for understanding glacier health. Yet previous work has not directly compared machine learning algorithms for snow classification across satellite image products. To address this, we developed a new automated workflow for tracking seasonal snow on glaciers using several image products and machine learning models. Applying this method can help provide insights into glacier health, water resources, and the effects of climate change on snow cover.
Zachary Hoppinen, Ross T. Palomaki, George Brencher, Devon Dunmire, Eric Gagliano, Adrian Marziliano, Jack Tarricone, and Hans-Peter Marshall
The Cryosphere, 18, 5407–5430, https://doi.org/10.5194/tc-18-5407-2024, https://doi.org/10.5194/tc-18-5407-2024, 2024
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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.
Randall Bonnell, Daniel McGrath, Jack Tarricone, Hans-Peter Marshall, Ella Bump, Caroline Duncan, Stephanie Kampf, Yunling Lou, Alex Olsen-Mikitowicz, Megan Sears, Keith Williams, Lucas Zeller, and Yang Zheng
The Cryosphere, 18, 3765–3785, https://doi.org/10.5194/tc-18-3765-2024, https://doi.org/10.5194/tc-18-3765-2024, 2024
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Snow provides water for billions of people, but the amount of snow is difficult to detect remotely. During the 2020 and 2021 winters, a radar was flown over mountains in Colorado, USA, to measure the amount of snow on the ground, while our team collected ground observations to test the radar technique’s capabilities. The technique yielded accurate measurements of the snowpack that had good correlation with ground measurements, making it a promising application for the upcoming NISAR satellite.
Tate G. Meehan, Ahmad Hojatimalekshah, Hans-Peter Marshall, Elias J. Deeb, Shad O'Neel, Daniel McGrath, Ryan W. Webb, Randall Bonnell, Mark S. Raleigh, Christopher Hiemstra, and Kelly Elder
The Cryosphere, 18, 3253–3276, https://doi.org/10.5194/tc-18-3253-2024, https://doi.org/10.5194/tc-18-3253-2024, 2024
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Snow water equivalent (SWE) is a critical parameter for yearly water supply forecasting and can be calculated by multiplying the snow depth by the snow density. We combined high-spatial-resolution snow depth information with ground-based radar measurements to solve for snow density. Extrapolated density estimates over our study area resolved detailed patterns that agree with the known interactions of snow with wind, terrain, and vegetation and were utilized in the calculation of SWE.
Isis Brangers, Hans-Peter Marshall, Gabrielle De Lannoy, Devon Dunmire, Christian Mätzler, and Hans Lievens
The Cryosphere, 18, 3177–3193, https://doi.org/10.5194/tc-18-3177-2024, https://doi.org/10.5194/tc-18-3177-2024, 2024
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To better understand the interactions between C-band radar waves and snow, a tower-based experiment was set up in the Idaho Rocky Mountains. The reflections were collected in the time domain to measure the backscatter profile from the various snowpack and ground surface layers. The results demonstrate that C-band radar is sensitive to seasonal patterns in snow accumulation but that changes in microstructure, stratigraphy and snow wetness may complicate satellite-based snow depth retrievals.
Ian E. McDowell, Kaitlin M. Keegan, S. McKenzie Skiles, Christopher P. Donahue, Erich C. Osterberg, Robert L. Hawley, and Hans-Peter Marshall
The Cryosphere, 18, 1925–1946, https://doi.org/10.5194/tc-18-1925-2024, https://doi.org/10.5194/tc-18-1925-2024, 2024
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Accurate knowledge of firn grain size is crucial for many ice sheet research applications. Unfortunately, collecting detailed measurements of firn grain size is difficult. We demonstrate that scanning firn cores with a near-infrared imager can quickly produce high-resolution maps of both grain size and ice layer distributions. We map grain size and ice layer stratigraphy in 14 firn cores from Greenland and document changes to grain size and ice layer content from the extreme melt summer of 2012.
Zachary Hoppinen, Shadi Oveisgharan, Hans-Peter Marshall, Ross Mower, Kelly Elder, and Carrie Vuyovich
The Cryosphere, 18, 575–592, https://doi.org/10.5194/tc-18-575-2024, https://doi.org/10.5194/tc-18-575-2024, 2024
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We used changes in radar echo travel time from multiple airborne flights to estimate changes in snow depths across Idaho for two winters. We compared our radar-derived retrievals to snow pits, weather stations, and a 100 m resolution numerical snow model. We had a strong Pearson correlation and root mean squared error of 10 cm relative to in situ measurements. Our retrievals also correlated well with our model, especially in regions of dry snow and low tree coverage.
Jack Tarricone, Ryan W. Webb, Hans-Peter Marshall, Anne W. Nolin, and Franz J. Meyer
The Cryosphere, 17, 1997–2019, https://doi.org/10.5194/tc-17-1997-2023, https://doi.org/10.5194/tc-17-1997-2023, 2023
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Mountain snowmelt provides water for billions of people across the globe. Despite its importance, we cannot currently measure the amount of water in mountain snowpacks from satellites. In this research, we test the ability of an experimental snow remote sensing technique from an airplane in preparation for the same sensor being launched on a future NASA satellite. We found that the method worked better than expected for estimating important snowpack properties.
Leung Tsang, Michael Durand, Chris Derksen, Ana P. Barros, Do-Hyuk Kang, Hans Lievens, Hans-Peter Marshall, Jiyue Zhu, Joel Johnson, Joshua King, Juha Lemmetyinen, Melody Sandells, Nick Rutter, Paul Siqueira, Anne Nolin, Batu Osmanoglu, Carrie Vuyovich, Edward Kim, Drew Taylor, Ioanna Merkouriadi, Ludovic Brucker, Mahdi Navari, Marie Dumont, Richard Kelly, Rhae Sung Kim, Tien-Hao Liao, Firoz Borah, and Xiaolan Xu
The Cryosphere, 16, 3531–3573, https://doi.org/10.5194/tc-16-3531-2022, https://doi.org/10.5194/tc-16-3531-2022, 2022
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Snow water equivalent (SWE) is of fundamental importance to water, energy, and geochemical cycles but is poorly observed globally. Synthetic aperture radar (SAR) measurements at X- and Ku-band can address this gap. This review serves to inform the broad snow research, monitoring, and application communities about the progress made in recent decades to move towards a new satellite mission capable of addressing the needs of the geoscience researchers and users.
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
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The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
Hans Lievens, Isis Brangers, Hans-Peter Marshall, Tobias Jonas, Marc Olefs, and Gabriëlle De Lannoy
The Cryosphere, 16, 159–177, https://doi.org/10.5194/tc-16-159-2022, https://doi.org/10.5194/tc-16-159-2022, 2022
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Snow depth observations at high spatial resolution from the Sentinel-1 satellite mission are presented over the European Alps. The novel observations can improve our knowledge of seasonal snow mass in areas with complex topography, where satellite-based estimates are currently lacking, and benefit a number of applications including water resource management, flood forecasting, and numerical weather prediction.
Ahmad Hojatimalekshah, Zachary Uhlmann, Nancy F. Glenn, Christopher A. Hiemstra, Christopher J. Tennant, Jake D. Graham, Lucas Spaete, Arthur Gelvin, Hans-Peter Marshall, James P. McNamara, and Josh Enterkine
The Cryosphere, 15, 2187–2209, https://doi.org/10.5194/tc-15-2187-2021, https://doi.org/10.5194/tc-15-2187-2021, 2021
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We describe the relationships between snow depth, vegetation canopy, and local-scale processes during the snow accumulation period using terrestrial laser scanning (TLS). In addition to topography and wind, our findings suggest the importance of fine-scale tree structure, species type, and distributions on snow depth. Snow depth increases from the canopy edge toward the open areas, but wind and topographic controls may affect this trend. TLS data are complementary to wide-area lidar surveys.
Rhae Sung Kim, Sujay Kumar, Carrie Vuyovich, Paul Houser, Jessica Lundquist, Lawrence Mudryk, Michael Durand, Ana Barros, Edward J. Kim, Barton A. Forman, Ethan D. Gutmann, Melissa L. Wrzesien, Camille Garnaud, Melody Sandells, Hans-Peter Marshall, Nicoleta Cristea, Justin M. Pflug, Jeremy Johnston, Yueqian Cao, David Mocko, and Shugong Wang
The Cryosphere, 15, 771–791, https://doi.org/10.5194/tc-15-771-2021, https://doi.org/10.5194/tc-15-771-2021, 2021
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High SWE uncertainty is observed in mountainous and forested regions, highlighting the need for high-resolution snow observations in these regions. Substantial uncertainty in snow water storage in Tundra regions and the dominance of water storage in these regions points to the need for high-accuracy snow estimation. Finally, snow measurements during the melt season are most needed at high latitudes, whereas observations at near peak snow accumulations are most beneficial over the midlatitudes.
Miguel A. Aguayo, Alejandro N. Flores, James P. McNamara, Hans-Peter Marshall, and Jodi Mead
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-451, https://doi.org/10.5194/hess-2020-451, 2020
Manuscript not accepted for further review
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Short summary
The seasonal snowpack provides water resources to billions of people worldwide. Large-scale mapping of snow water equivalent (SWE) with high resolution is critical for many scientific and economics fields. In this work we used the radar remote sensing interferometric synthetic aperture radar (InSAR) to estimate the SWE change between 2 d. The error in the estimated SWE change is less than 2 cm for in situ stations. Additionally, the retrieved SWE using InSAR is correlated with lidar snow depth.
The seasonal snowpack provides water resources to billions of people worldwide. Large-scale...