Articles | Volume 17, issue 7
https://doi.org/10.5194/tc-17-2779-2023
https://doi.org/10.5194/tc-17-2779-2023
Research article
 | 
13 Jul 2023
Research article |  | 13 Jul 2023

Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data

César Deschamps-Berger, Simon Gascoin, David Shean, Hannah Besso, Ambroise Guiot, and Juan Ignacio López-Moreno

Related authors

Rain-on-snow responses to warmer Pyrenees: a sensitivity analysis using a physically based snow hydrological model
Josep Bonsoms, Juan I. López-Moreno, Esteban Alonso-González, César Deschamps-Berger, and Marc Oliva
Nat. Hazards Earth Syst. Sci., 24, 245–264, https://doi.org/10.5194/nhess-24-245-2024,https://doi.org/10.5194/nhess-24-245-2024, 2024
Short summary
Exploring the sensitivity to precipitation, blowing snow, and horizontal resolution of the spatial distribution of simulated snow cover
Ange Haddjeri, Matthieu Baron, Matthieu Lafaysse, Louis Le Toumelin, César Deschamp-Berger, Vincent Vionnet, Simon Gascoin, Matthieu Vernay, and Marie Dumont
EGUsphere, https://doi.org/10.5194/egusphere-2023-2604,https://doi.org/10.5194/egusphere-2023-2604, 2023
Short summary
Pre-collapse motion of the February 2021 Chamoli rock–ice avalanche, Indian Himalaya
Maximillian Van Wyk de Vries, Shashank Bhushan, Mylène Jacquemart, César Deschamps-Berger, Etienne Berthier, Simon Gascoin, David E. Shean, Dan H. Shugar, and Andreas Kääb
Nat. Hazards Earth Syst. Sci., 22, 3309–3327, https://doi.org/10.5194/nhess-22-3309-2022,https://doi.org/10.5194/nhess-22-3309-2022, 2022
Short summary
Propagating information from snow observations with CrocO ensemble data assimilation system: a 10-years case study over a snow depth observation network
Bertrand Cluzet, Matthieu Lafaysse, César Deschamps-Berger, Matthieu Vernay, and Marie Dumont
The Cryosphere, 16, 1281–1298, https://doi.org/10.5194/tc-16-1281-2022,https://doi.org/10.5194/tc-16-1281-2022, 2022
Short summary
Fractional snow-covered area: scale-independent peak of winter parameterization
Nora Helbig, Yves Bühler, Lucie Eberhard, César Deschamps-Berger, Simon Gascoin, Marie Dumont, Jesus Revuelto, Jeff S. Deems, and Tobias Jonas
The Cryosphere, 15, 615–632, https://doi.org/10.5194/tc-15-615-2021,https://doi.org/10.5194/tc-15-615-2021, 2021
Short summary

Related subject area

Discipline: Snow | Subject: Remote Sensing
Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign
Steven J. Pestana, C. Chris Chickadel, and Jessica D. Lundquist
The Cryosphere, 18, 2257–2276, https://doi.org/10.5194/tc-18-2257-2024,https://doi.org/10.5194/tc-18-2257-2024, 2024
Short summary
Temperature-dominated spatiotemporal variability in snow phenology on the Tibetan Plateau from 2002 to 2022
Jiahui Xu, Yao Tang, Linxin Dong, Shujie Wang, Bailang Yu, Jianping Wu, Zhaojun Zheng, and Yan Huang
The Cryosphere, 18, 1817–1834, https://doi.org/10.5194/tc-18-1817-2024,https://doi.org/10.5194/tc-18-1817-2024, 2024
Short summary
Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
Jinmei Pan, Michael Durand, Juha Lemmetyinen, Desheng Liu, and Jiancheng Shi
The Cryosphere, 18, 1561–1578, https://doi.org/10.5194/tc-18-1561-2024,https://doi.org/10.5194/tc-18-1561-2024, 2024
Short summary
Bayesian physical–statistical retrieval of snow water equivalent and snow depth from X- and Ku-band synthetic aperture radar – demonstration using airborne SnowSAr in SnowEx'17
Siddharth Singh, Michael Durand, Edward Kim, and Ana P. Barros
The Cryosphere, 18, 747–773, https://doi.org/10.5194/tc-18-747-2024,https://doi.org/10.5194/tc-18-747-2024, 2024
Short summary
Snow water equivalent retrieval over Idaho – Part 1: Using Sentinel-1 repeat-pass interferometry
Shadi Oveisgharan, Robert Zinke, Zachary Hoppinen, and Hans Peter Marshall
The Cryosphere, 18, 559–574, https://doi.org/10.5194/tc-18-559-2024,https://doi.org/10.5194/tc-18-559-2024, 2024
Short summary

Cited articles

Airborne Snow Observatories, Inc.: OUR DATA, Airborne Snow Observatories, Inc. [data set], https://data.airbornesnowobservatories.com/#, last access: 1 June 2023. 
Alfieri, L., Avanzi, F., Delogu, F., Gabellani, S., Bruno, G., Campo, L., Libertino, A., Massari, C., Tarpanelli, A., Rains, D., Miralles, D. G., Quast, R., Vreugdenhil, M., Wu, H., and Brocca, L.: High-resolution satellite products improve hydrological modeling in northern Italy, Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, 2022. 
Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.: Potential impacts of a warming climate on water availability in snow-dominated regions, Nature, 438, 303–309, https://doi.org/10.1038/nature04141, 2005. 
Berthier, E., Arnaud, Y., Kumar, R., Ahmad, S., Wagnon, P., and Chevallier, P.: Remote sensing estimates of glacier mass balances in the Himachal Pradesh (Western Himalaya, India), Remote Sens. Environ., 108, 327–338, https://doi.org/10.1016/j.rse.2006.11.017, 2007. 
Beyer, R. A., Alexandrov, O., and Scott, M.: The Ames Stereo Pipeline: NASA's Open Source Software for Deriving and Processing Terrain Data Special Section, Earth Space Sci., 5, 537–548, https://doi.org/10.1029/2018EA000409, 2018. 
Download
Short summary
The estimation of the snow depth in mountains is hard, despite the importance of the snowpack for human societies and ecosystems. We measured the snow depth in mountains by comparing the elevation of points measured with snow from the high-precision altimetric satellite ICESat-2 to the elevation without snow from various sources. Snow depths derived only from ICESat-2 were too sparse, but using external airborne/satellite products results in spatially richer and sufficiently precise snow depths.