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Titel |
Forecasting of wet snow avalanche activity: Proof of concept and operational implementation |
VerfasserIn |
Andreas Gobiet, Lisa Jöbstl, Hannes Rieder, Sascha Bellaire, Christoph Mitterer |
Konferenz |
EGU General Assembly 2017
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Medientyp |
Artikel
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Sprache |
en
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 19 (2017) |
Datensatznummer |
250149764
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Publikation (Nr.) |
EGU/EGU2017-14150.pdf |
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Zusammenfassung |
State-of-the-art tools for the operational assessment of avalanche danger include field
observations, recordings from automatic weather stations, meteorological analyses and
forecasts, and recently also indices derived from snowpack models. In particular, an index for
identifying the onset of wet-snow avalanche cycles (LWCindex), has been demonstrated to be
useful. However, its value for operational avalanche forecasting is currently limited, since
detailed, physically based snowpack models are usually driven by meteorological data from
automatic weather stations only and have therefore no prognostic ability. Since avalanche risk
management heavily relies on timely information and early warnings, many avalanche
services in Europe nowadays start issuing forecasts for the following days, instead of the
traditional assessment of the current avalanche danger. In this context, the prognostic
operation of detailed snowpack models has recently been objective of extensive
research.
In this study a new, observationally constrained setup for forecasting the onset of wet-snow
avalanche cycles with the detailed snow cover model SNOWPACK is presented and
evaluated. Based on data from weather stations and different numerical weather
prediction models, we demonstrate that forecasts of the LWCindex as indicator for
wet-snow avalanche cycles can be useful for operational warning services, but is so far
not reliable enough to be used as single warning tool without considering other
factors.
Therefore, further development currently focuses on the improvement of the forecasts by
applying ensemble techniques and suitable post processing approaches to the output of
numerical weather prediction models. In parallel, the prognostic meteo-snow model chain is
operationally used by two regional avalanche warning services in Austria since winter
2016/2017 for the first time. Experiences from the first operational season and first results
from current model developments will be reported. |
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