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Refinements of empirical models to forecast the shear strength of persistent weak snow layers
PART B: Layers of surface hoar crystals
AbstractBuried layers of surface hoar often release skier-triggered avalanches in the Columbia Mountains of Canada and their shear strength can be used to assess the stability of a slab overlaying these layers. In 2001 Chalmers introduced an Interval Model to calculate the shear strength of layers of surface hoar based on manual snowprofile observations. We refined his model by adjusting the measured shear strength for the normal load and included only data points where the weak layer depth did not exceed 100 cm to better account for skier triggering. Further, we used average and daily loading rates as well as a regression analysis to determine the best estimate of the shear strength change. Our final Forecasting Model used a multivariate regression to calculate the shear strength on days with snowprofile observations and as well as average and daily loading rates to forecast the shear strength on days without manual snowprofile observations. The performance of the model (r2) was 0.71 and 0.63 using average and daily loading rates, respectively. A companion paper, Part A, develops a forecasting model for weak layers of faceted crystals.
Refinements of empirical models to forecast the shear strength of persistent weak snow layers
PART B: Layers of surface hoar crystals
AbstractBuried layers of surface hoar often release skier-triggered avalanches in the Columbia Mountains of Canada and their shear strength can be used to assess the stability of a slab overlaying these layers. In 2001 Chalmers introduced an Interval Model to calculate the shear strength of layers of surface hoar based on manual snowprofile observations. We refined his model by adjusting the measured shear strength for the normal load and included only data points where the weak layer depth did not exceed 100 cm to better account for skier triggering. Further, we used average and daily loading rates as well as a regression analysis to determine the best estimate of the shear strength change. Our final Forecasting Model used a multivariate regression to calculate the shear strength on days with snowprofile observations and as well as average and daily loading rates to forecast the shear strength on days without manual snowprofile observations. The performance of the model (r2) was 0.71 and 0.63 using average and daily loading rates, respectively. A companion paper, Part A, develops a forecasting model for weak layers of faceted crystals.
Refinements of empirical models to forecast the shear strength of persistent weak snow layers
PART B: Layers of surface hoar crystals
Zeidler, Antonia (author) / Jamieson, Bruce (author)
Cold Regions, Science and Technology ; 44 ; 184-193
2005-11-19
10 pages
Article (Journal)
Electronic Resource
English
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