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| Titel |
Analysis of the snow-atmosphere energy balance during wet-snow instabilities and implications for avalanche prediction |
| VerfasserIn |
C. Mitterer, J. Schweizer |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1994-0416
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| Digitales Dokument |
URL |
| Erschienen |
In: The Cryosphere ; 7, no. 1 ; Nr. 7, no. 1 (2013-02-01), S.205-216 |
| Datensatznummer |
250017413
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| Publikation (Nr.) |
 copernicus.org/tc-7-205-2013.pdf |
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| Zusammenfassung |
| Wet-snow avalanches are notoriously difficult to predict; their formation
mechanism is poorly understood since in situ measurements representing the
thermal and mechanical evolution are difficult to perform. Instead, air
temperature is commonly used as a predictor variable for days with high
wet-snow avalanche danger – often with limited success. As melt water is a
major driver of wet-snow instability and snow melt depends on the energy
input into the snow cover, we computed the energy balance for predicting
periods with high wet-snow avalanche activity. The energy balance was partly
measured and partly modelled for virtual slopes at different elevations for
the aspects south and north using the 1-D snow cover model SNOWPACK. We used
measured meteorological variables and computed energy balance and its
components to compare wet-snow avalanche days to non-avalanche days for four
consecutive winter seasons in the surroundings of Davos, Switzerland. Air
temperature, the net shortwave radiation and the energy input integrated
over 3 or 5 days showed best results in discriminating event from non-event
days. Multivariate statistics, however, revealed that for better predicting
avalanche days, information on the cold content of the snowpack is
necessary. Wet-snow avalanche activity was closely related to periods when
large parts of the snowpack reached an isothermal state (0 °C) and
energy input exceeded a maximum value of 200 kJ m−2 in one day, or the
3-day sum of positive energy input was larger than 1.2 MJ m−2.
Prediction accuracy with measured meteorological variables was as good as
with computed energy balance parameters, but simulated energy balance
variables accounted better for different aspects, slopes and elevations than
meteorological data. |
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