International Snow Science Workshop Proceedings - Montana State University Library

Item: Monitoring Snowpack Temperature Gradient Using Automatic Snow Depth Sensor

• • Title: Monitoring Snowpack Temperature Gradient Using Automatic Snow Depth Sensor

    Proceedings: Proceedings, 2012 International Snow Science Workshop, Anchorage, Alaska

    Authors:

    • Örn Ingólfsson  [ POLS Engineering, IS - 400 Ísafjörður, ICELAND ]
    • Harpa Grímsdóttir  [ Icelandic Meteorological Office, Avalanche Research Center, IS-400 Ísafjörður, ICELAND ]
    • Magni Hreinn Jónsson  [ Icelandic Meteorological Office, Avalanche Research Center, IS-400 Ísafjörður, ICELAND ]

    Date: 2012

    Abstract: An instrument for measuring snow depth and snow temperature has been developed by POLS engineering in Iceland. The snow sensor (SM4) consists of a series of digital thermistors mounted with a fixed interval on a pole that extends through the snowpack. An algorithm has been developed to calculate the snow depth based on the temperature data. The temperature profile is obtained as additional information. Avalanches in Iceland are most commonly triggered directly by heavy snowfall and high wind speeds. However, stability tests and data from avalanche crowns indicate that facets are one of the most common crystal types in persistent weak layers in Iceland. Comparing historical data from the SM4 sensors to avalanche occurrences indicates that avalanche cycles that are not explained solely by severe weather may in many cases be explained by high temperature gradients for a long time, which may be assumed to lead to the formation of a weak layer of facets. Methods have been developed to detect and visualize layers with temperature gradients that exceed a critical value, assumed to be the critical gradient to produce facets. The duration of the temperature gradient above the critical value is also shown. Showing the location and time periods of critical temperature gradient in a visual way should help avalanche forecasters to detect warning signs related to possible facet formation. This will improve the avalanche forecast for both human and naturally triggered avalanches and decrease the risk of a failure to forecast avalanches that are not a direct consequence of severe weather.

    Object ID: issw-2012-956-960.pdf

    Language of Article: English

    Presenter(s): unknown

    Keywords: snow sensor, avalanche monitoring, snowpack temperature, faceted crystals, weak layers

    Page Number(s): 956-960

    Subjects: avalanche forecasting faceted crystals historical avalanche data

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