Preprints
https://doi.org/10.5194/tc-2022-191
https://doi.org/10.5194/tc-2022-191
 
04 Oct 2022
04 Oct 2022
Status: this preprint is currently under review for the journal TC.

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

César Deschamps-Berger1,2, Simon Gascoin1, David Shean3, Hannah Besso3, Ambroise Guiot1, and Juan Ignacio López-Moreno2 César Deschamps-Berger et al.
  • 1Centre d’Etudes Spatiales de la Biosphère, CESBIO, Univ. Toulouse, CNES/CNRS/INRAE/IRD/UPS, Toulouse, France
  • 2Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
  • 3University of Washington, Dept. of Civil and Environmental Engineering, Seattle, WA

Abstract. The unprecedented precision of the altimetry satellite ICESat-2 and the increasing availability of high-resolution elevation datasets open new opportunities to measure snow depth in mountains, a critical variable for ecosystems and water resources monitoring. We retrieved snow depth over the upper Tuolumne basin (California, USA) for three years by differencing ICESat-2 ATL06 snow-on elevations and various snow-off elevation sources, including ATL06 and external digital elevation models. Snow depth derived from ATL06 data only (snow-on and snow-off) provided a poor temporal and spatial coverage, limiting its utility. However, using airborne lidar or satellite photogrammetry elevation models as snow-off elevation source yielded an accuracy of ~0.2 m (bias), a precision of ~0.5 m for low slopes and ~1.2 m for steeper areas, compared to eight reference airborne lidar snow depth maps. The snow depth derived from ICESat-2 ATL06 will help address the challenge of measuring the snow depth in unmonitored mountainous areas.

César Deschamps-Berger et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-191', Anonymous Referee #1, 08 Nov 2022
  • RC2: 'Comment on tc-2022-191', Désirée Treichler, 21 Nov 2022

César Deschamps-Berger et al.

César Deschamps-Berger et al.

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Short summary
The estimation of the snow depth in mountains is hard despite the importance of this resource 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 methods. ICESat-2 only derived snow depths were too sparse but using external airborne or satellite products results in spatially richer and sufficiently precise snow depths.