International Snow Science Workshop Proceedings - Montana State University Library

Item: CONTINUOUS SNOW WATER EQUIVALENT MONITORING ON GLACIERS USING COSMIC RAY NEUTRON SENSOR TECHNOLOGY A CASE STUDY ON HINTEREISFERNER, AUSTRIA

• • Title: CONTINUOUS SNOW WATER EQUIVALENT MONITORING ON GLACIERS USING COSMIC RAY NEUTRON SENSOR TECHNOLOGY A CASE STUDY ON HINTEREISFERNER, AUSTRIA

    Proceedings: International Snow Science Workshop 2024, Tromsø, Norway

    Authors:

    • Marie Schroeder  [ University of Innsbruck, Department of Atmospheric and Cryospheric Sciences, Innsbruck, Austria ]  [ Austrian Association of Snow and Avalanches, Innsbruck, Austria ]
    • Rainer Prinz  [ University of Innsbruck, Department of Atmospheric and Cryospheric Sciences, Innsbruck, Austria ]  [ Austrian Association of Snow and Avalanches, Innsbruck, Austria ]
    • Michael Binder  [ Austrian Association of Snow and Avalanches, Innsbruck, Austria ]  [ Avalanche Warning Service Tyrol, Innsbruck, Austria ]  [ Institute of Atmospheric Physics, German Aerospace Center, Oberpfaffenhofen, Germany ]
    • Michael Winkler  [ Avalanche Warning Service Tyrol, Innsbruck, Austria ]  [ GeoSphere Austria, Innsbruck, Austria ]
    • Harald Schellander  [ GeoSphere Austria, Innsbruck, Austria ]

    Date: 2024-09-23

    Abstract: Snow water equivalent (SWE) is crucial for assessing snow mass in various fields, particularly on glaciers to quantify accumulation and ablation of the winter snow cover. Presently, the majority of glacier science relies on manual measurements once or a few times per year, given the limited techniques for continuous SWE monitoring and the challenging conditions in a high mountain environment. The Cosmic Ray Neutron Sensor (CRNS) offers sub-daily SWE estimates derived from neutron counts. Though CRNS’s potential was first identified in the 1980s, its deployment on glaciers remains scarcely studied. This study employs a CRNS installed on Hintereisferner (HEF), Austria. Comparing CRNS outputs with frequent manual SWE measurements, the results demonstrate a MAE of 34 kg m−2 (14 %). Applying an independent automated snow depth measurement, a snow density deviation of 34 kg m−3 (9 %) is identified. The CRNS appears remarkably resilient in harsh conditions, providing nearly continuous 1 hour data over the last 3 years. The study evaluated the performance of three snow models - SNOWPACK, ∆snow, and ∆snow 2.0 - in estimating SWE against CRNS measurements. While SNOWPACK, with its physically-based approach, delivered the best results, ∆snow stood out for its simplicity, requiring only snow depth measurements. ∆snow 2.0, with slight adaptations in its maximum density module, showed significant improvement and performed almost as well as SNOWPACK in terms of MAE.

    Object ID: ISSW2024_P8.8.pdf

    Language of Article: English

    Presenter(s): Marie Schroeder

    Keywords: Snow Measurements, Cosmic Ray Neutron Sensor, Snow Water Equivalent, Snow Modeling

    Page Number(s): 1107 - 1114

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