Item: INITIALIZING SNOW COVER SIMULATIONS WITH OBSERVED SNOW PROFILES
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Title: INITIALIZING SNOW COVER SIMULATIONS WITH OBSERVED SNOW PROFILES
Proceedings: International Snow Science Workshop Proceedings 2023, Bend, Oregon
Authors:
- Michael Binder [ Institute of Atmospheric Physics, German Aerospace Center, Oberpfaffenhofen, Germany ] [ Avalanche Warning Service Tirol, Innsbruck, Austria ]
- Christoph Mitterer [ Avalanche Warning Service Tirol, Innsbruck, Austria ]
Date: 2023-10-08
Abstract: Snow cover models were originally developed to advance snow and avalanche research and assist operational avalanche forecasting. Though indispensable for research, their vast application within forecasting operations is just starting, and, until now, most avalanche forecasters mainly rely on traditional measurements, observations, and weather forecasts to assess the avalanche danger for their region. Partly, this slow transition can be related to limited technical infrastructure. On the other hand, interpreting the snow cover simulations is not intuitive, and integrating them into the traditional workflow for assessing the avalanche danger is challenging. A model chain that utilizes observed snow profiles to initialize snow cover simulations with the SNOWPACK model is presented to close this gap. One of its essential parts is the parameterization of the snow density. Another key part is the stacking of consecutive numerical weather prediction runs. In this way, the simulations are independent of weather station locations, and any observed snow profile can be simulated by retrieving the relevant meteorological parameters from the numerical weather prediction model. Combining the output of these simulations with state-of-the-art post-processing algorithms resulted in a precious and accessible tool for avalanche forecasters. Furthermore, the model chain's output had significantly higher similarity to recurring snow pit observations than conventional snow cover simulations driven by automated weather stations, especially a few days to weeks after the initial snow profile. In that respect, simulating snow profiles obtained shortly before critical avalanche situations can be particularly effective and helpful for forecasting avalanche danger.
Object ID: ISSW2023_O4.02.pdf
Language of Article: English
Presenter(s): Michael Binder
Keywords: snowpack simulations, snow profiles, operational assessment and forecasting of avalanche danger, snow density parameterization, numerical weather prediction models, snow profile alignment and similarity assessment
Page Number(s): 108 - 114
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