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

• Published in: The Cryosphere
• Main Authors: Deschamps-Berger, César, Gascoin, Simon, Shean, David, Besso, Hannah, Guiot, Ambroise, López-Moreno, Juan Ignacio
• Other Authors: Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Instituto Pirenaico de Ecologìa = Pyrenean Institute of Ecology Zaragoza (IPE - CSIC), University of Washington Seattle, This work has been supported by the Programme National de Télédétection Spatiale (PNTS; grant no. PNTS-2018-4), by the Centre National d’Études Spatiales (CNES), and by the Spanish Ministry of Science and Innovation (MARGISNOW project, grant no. PID2021-124220OB-100; HIDROIBERNIEVE project, grant no. CGL2017-82216K). Ambroise Guiot was supported by Météo-France during the internship which laid the groundwork for this article. David Shean was supported by NASA (award no. 80NSSC20K0995). Hannah Besso was supported by NASA (award no. 80NSSC20K1293).
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2023
• Subjects: [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology; The Cryosphere
• Online Access: https://hal.science/hal-04171885; https://hal.science/hal-04171885/document; https://hal.science/hal-04171885/file/tc-17-2779-2023.pdf; https://doi.org/10.5194/tc-17-2779-2023

International audience Abstract. The unprecedented precision of satellite laser altimetry data from the NASA ICESat-2 mission and the increasing availability of high-resolution elevation datasets open new opportunities to measure snow depth in mountains, a critical variable for ecosystem and water resource monitoring. We retrieved snow depth over the upper Tuolumne basin (California, USA) for 3 years by differencing ICESat-2 ATL06 snow-on elevations and various snow-off digital elevation models. Snow depth derived from ATL06 data only (snow-on and snow-off) offers a poor temporal and spatial coverage, limiting its potential utility. However, using a digital terrain model from airborne lidar surveys as the snow-off elevation source yielded a snow depth accuracy of ∼ 0.2 m (bias) and precision of ∼ 1 m (random error) across the basin, with an improved precision of 0.5 m for low slopes (< 10∘), compared to eight reference airborne lidar snow depth maps. Snow depths derived from ICESat-2 ATL06 and a satellite photogrammetry digital elevation model have a larger bias and reduced precision, partly induced by increased errors in forested areas. These various combinations of repeated ICESat-2 snow surface elevation measurements with satellite or airborne products will enable tailored approaches to map snow depth and estimate water resource availability in mountainous areas with limited snow depth observations.