International Snow Science Workshop Proceedings - Montana State University Library

Item: TOWER-BASED SNOW REMOTE SENSING FOR IMPROVED UNDERSTANDING OF RETRIEVAL ALGORITHMS

• • Title: TOWER-BASED SNOW REMOTE SENSING FOR IMPROVED UNDERSTANDING OF RETRIEVAL ALGORITHMS

    Proceedings: Proceedings, International Snow Science Workshop, Whistler, BC, Canada, 2026

    Authors:

    • Hans-Peter Marshall  [ Cryosphere Geophysics And Remote Sensing (CryoGARS) Lab, Department of Geosciences, Boise State University, Boise, ID, USA ]
    • Eli Deeb  [ U.S. Army Cold Regions Research and Engineering Laboratory ]
    • Rashmi Shaw  [ NASA Jet Propulsion Laboratory ]
    • Hans Lievens  [ Department of Environment, Ghent University, Belgium ]
    • Manuela Girotto  [ Environmental Science, Policy, and Management, University of California Berkeley ]
    • Coleman Kane  [ Cryosphere Geophysics And Remote Sensing (CryoGARS) Lab, Department of Geosciences, Boise State University, Boise, ID, USA ]
    • Jaron Vandenbrouke  [ Department of Environment, Ghent University, Belgium ]
    • Jarne Van Mulders  [ Department of Electrical Engineering, KU Leuven, Belgium ]
    • Thomas Van Der Weide  [ Cryosphere Geophysics And Remote Sensing (CryoGARS) Lab, Department of Geosciences, Boise State University, Boise, ID, USA ]

    Date: 2026-09-28

    Abstract: Microwave snow remote sensing has been challenged by a lack of the ideal frequencies, polarizations, spatial resolution, and temporal resolution, in order to test retrieval algorithms over a wide range of well-characterized snow conditions. Large efforts using combined airborne and field campaigns, such as CLPX, CoreH2O, and SnowEx, have resulted in snapshots of snow conditions with both low and high frequency radar. However aligning independent observations for calibration and validation, and addressing scale mismatches, can be difficult. While time-series campaigns have been the most valuable, they are costly. We present a time series of observations from tower platforms, combining scanning lidar, P-band signals of opportunity, radar, and standard meteorological and snowpack measurements. These tower-based remote sensing experiments provide an opportunity to observe a large dynamic range in well-characterized conditions.

    Object ID: ISSW2026_P3.55.pdf

    DOI: https://doi.org/10.15788/1790099223

    Language of Article: English

    Presenter(s): H.P. Marshall

    Keywords: snow remote sensing, radar, lidar, SWE, tower-based observations, retrieval algorithms

    Page Number(s): 2286 - 2291

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