Articles | Volume 18, issue 8
https://doi.org/10.5194/tc-18-3765-2024
© 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-18-3765-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Aug 2024
Research article |
| 22 Aug 2024
| 22 Aug 2024
Evaluating L-band InSAR snow water equivalent retrievals with repeat ground-penetrating radar and terrestrial lidar surveys in northern Colorado
Randall Bonnell
CORRESPONDING AUTHOR
Department of Geosciences, Colorado State University, Fort Collins, Colorado, USA
Daniel McGrath
Department of Geosciences, Colorado State University, Fort Collins, Colorado, USA
Jack Tarricone
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
NASA Postdoctoral Program, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Hans-Peter Marshall
Department of Geosciences, Boise State University, Boise, Idaho, USA
Ella Bump
Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, Colorado, USA
Caroline Duncan
Alaska District, U.S. Army Corps of Engineers, Anchorage, Alaska, USA
Stephanie Kampf
Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, Colorado, USA
Yunling Lou
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Alex Olsen-Mikitowicz
Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, Colorado, USA
Megan Sears
Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, Colorado, USA
Keith Williams
GAGE Facility, UNAVCO Inc., Boulder, Colorado, USA
Lucas Zeller
Department of Geosciences, Colorado State University, Fort Collins, Colorado, USA
Yang Zheng
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
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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
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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
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Short summary
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.
Snow provides water for billions of people, but the amount of snow is difficult to detect...
