Linking the effective thermal conductivity of snow to its shear strength and density
The effective thermal conductivity of snow, keff, is a crucial climatic and environmental variable. Here, we test the intuition that keff is linked to microstructural and mechanical properties by attempting to relate keff to density ρsnow, and to shear strength σ measured with a handheld shear vane....
Gespeichert in:
Veröffentlicht in: | Journal of Geophysical Research 2011-12, Vol.116 (F4), p.n/a, Article F04027 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The effective thermal conductivity of snow, keff, is a crucial climatic and environmental variable. Here, we test the intuition that keff is linked to microstructural and mechanical properties by attempting to relate keff to density ρsnow, and to shear strength σ measured with a handheld shear vane. We performed 106 combined measurements of keff, ρsnow and σ in the Alps, Svalbard, Arctic Alaska, and near the North Pole, covering essentially all snow types. We find a good correlation between keff and ρsnow which is not significantly different from that of Sturm et al. (1997). The correlation between keff and a combination of σ and ρsnow is stronger than with density alone. We propose an equation linking keff, (W m−1 K−1) ρsnow (kg m−3) and σ (Pa): keff = 7.114 10−5 ρsnow σ0.333 + 2.367 10−2. This equation places constraints on the calculation of keff, ρsnow and σ in avalanche warning models where σ is a key variable. For our samples, we calculate σ from measured values of keff and ρsnow using our equation and compare the value to that predicted by the French MEPRA avalanche warning model, which uses density and grain type as input data. MEPRA and the prediction of σ based on keff and ρsnow agree within 8%. MEPRA agrees with observations within 11%. Calculating σ from density only yields values 55% lower than measured, showing the interest of using additional data to predict σ.
Key Points
We correlate the thermal conductivity, shear strength and density of snow
A structural model shows that snow microstructure is not random
Avalanche forecasting may be improved by the correlations found |
---|---|
ISSN: | 0148-0227 2169-9003 2156-2202 2169-9011 |
DOI: | 10.1029/2011JF002000 |