International Snow Science Workshop Proceedings - Montana State University Library

Item: RECENT ADVANCES IN MEASURING SNOW PHYSICAL PROPERTIES: DENSITY, SPECIFIC SURFACE AREA, AND LIQUID WATER CONTENT

• • Title: RECENT ADVANCES IN MEASURING SNOW PHYSICAL PROPERTIES: DENSITY, SPECIFIC SURFACE AREA, AND LIQUID WATER CONTENT

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

    Authors:

    • Benjamin Walter  [ WSL Institute for Snow and Avalanche Research SLF, CH-7260 Davos Dorf, Switzerland ]
    • Valentin Philippe  [ WSL Institute for Snow and Avalanche Research SLF, CH-7260 Davos Dorf, Switzerland ]
    • Leah Gaillard Festa  [ WSL Institute for Snow and Avalanche Research SLF, CH-7260 Davos Dorf, Switzerland ]
    • Michael Lombardo  [ WSL Institute for Snow and Avalanche Research SLF, CH-7260 Davos Dorf, Switzerland ]
    • Lars Mewes  [ WSL Institute for Snow and Avalanche Research SLF, CH-7260 Davos Dorf, Switzerland ]

    Date: 2026-09-28

    Abstract: Accurate measurements of snow density, specific surface area (SSA), and liquid water content (LWC) are essential for studying snow metamorphosis, snow physical properties, snow processes, and for developing snow cover models. We present recent advances in three different snow measurement techniques developed and applied at the WSL Institute for Snow and Avalanche Research SLF. First, the SnowImager instrument enables rapid, high-resolution optical measurements of SSA and density, with ongoing developments targeting spatially resolved LWC measurements. Second, a unique ten-year record of daily SnowMicroPen measurements at Weissfluhjoch demonstrates the potential for monitoring the seasonal evolution of snow density, SSA, and stratigraphy at unprecedented temporal and vertical resolution. Finally, preliminary time-domain nuclear magnetic resonance measurements show a strong linear response to LWC and indicate the potential for highly accurate reference measurements. Together, these complementary techniques provide new opportunities for efficient snow characterization, process studies, model validation, and the generation of high-quality datasets for machine-learning applications.

    Object ID: ISSW2026_P4.7.pdf

    DOI: https://doi.org/10.15788/1790099415

    Language of Article: English

    Presenter(s): Benjamin Walter

    Keywords: Snow microstructure, Density, Specific surface area, Liquid water content, Cryosphere monitoring.

    Page Number(s): 366 - 370

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