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

Data sets

ATLAS/ICESat-2 L3A Land Ice Height, Version 5 B. Smith, S. Adusumilli, B. M. Csathó, D. Felikson, H. A. Fricker, A. Gardner, N. Holschuh, J. Lee, J. Nilsson, F. S. Paolo, M. R. Siegfried, T. Sutterley, and the ICESat-2 Science Team https://doi.org/10.5067/ATLAS/ATL06.005

ASO L4 Lidar Snow Depth 3m UTM Grid, Version 1 T. Painter https://doi.org/10.5067/KIE9QNVG7HP0

Digital Elevation Model from Pléiades stereo images - Upper Tuolumne basin, California, 2017-08-13 César Deschamps-Berger and Simon Gascoin https://doi.org/10.5281/zenodo.6466891

Copernicus DEM - Global and European Digital Elevation Model (COP-DEM), GLO-30, ESA Copernicus https://doi.org/10.5270/ESA-c5d3d65

Model code and software

Digital Elevation Model from Pléiades stereo images - Upper Tuolumne basin, California, 2017-08-13 C. Deschamps-Berger and S. Gascoin https://doi.org/10.5281/zenodo.6466891

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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.