Item: AUTOMATED DRY SNOWFALL LEVEL CALCULATION FOR IMPROVED ASSESSMENT OF MELT-FREEZE CRUSTS AND ASSOCIATED FACETED WEAK LAYERS
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Title: AUTOMATED DRY SNOWFALL LEVEL CALCULATION FOR IMPROVED ASSESSMENT OF MELT-FREEZE CRUSTS AND ASSOCIATED FACETED WEAK LAYERS
Proceedings: International Snow Science Workshop 2024, Tromsø, Norway
Authors:
- Marie Hofmann [ Avalanche Warning Service Tyrol ]
- Jil Lehnert [ Avalanche Warning Service Tyrol ] [ University of Innsbruck ]
- Christoph Mitterer [ Avalanche Warning Service Tyrol ]
Date: 2024-09-23
Abstract: Faceted weak layers relevant for avalanche triggering often develop around melt-freeze crusts. These can - besides a formation through shortwave radiation or sensible heat - originate from moisture input into the snowpack during rain events. Traditionally, avalanche forecasters track such melt-freeze crusts with the help of snow profiles or by examining forecasted and observed snowfall limits. However, these approaches have limitations in spatial coverage and accuracy. This study introduces an approach to facilitate the tracking of melt-freeze crusts. We calculated dry-snowfall levels (DSLs) from automated weather station (AWS) data located in Tyrol (Austria). Unlike conventional snowfall limits, which denote the elevation where 50% of precipitation is snow, DSLs define the elevation where 100% of precipitation is dry snow, thus indicating crust-free zones above. To obtain this information, in a first step, we calculated wet-bulb temperature from air temperature and relative humidity data provided by AWSs. Assuming a threshold wet-bulb temperature of 0.3 °C for the elevation of the DSL we then calculated the respective DSL for the given locations of the AWSs. A first validation of calculated DSLs against observed snowfall limits from the 2023-2024 winter season shows promising alignment. We generally expect observers to report a snowfall limit which is lower (i.e. wetter) than the calculated DSL. In line with this, DSLs were usually higher in elevation than reported snowfall limits. Besides these results, we implemented our work into the operational system of the Avalanche Warning Service Tyrol, including a visual representation of daily maximum DSLs on a map interface. With this, forecasters can now easily assess spatial DSL distributions during specific precipitation events. Future work will focus on refining DSL calculations and enhancing observational practices to further strengthen forecasting accuracy and reliability.
Object ID: ISSW2024_P1.7.pdf
Language of Article: English
Presenter(s): Christoph Mitterer
Keywords: Melt-freeze crust, snowfall level, avalanche forecasting, automated weather stations
Page Number(s): 109 - 115
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