Articles | Volume 20, issue 12
https://doi.org/10.5194/nhess-20-3551-2020
https://doi.org/10.5194/nhess-20-3551-2020
Research article
 | 
18 Dec 2020
Research article |  | 18 Dec 2020

Examining the operational use of avalanche problems with decision trees and model-generated weather and snowpack variables

Simon Horton, Moses Towell, and Pascal Haegeli

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Cited articles

Bellaire, S. and Jamieson, B.: On estimating avalanche danger from simulated snow profiles, in: Proc. Int. Snow Sci. Workshop, Grenoble, France, 7–11 October 2013, 154–161, 2013. a
Blattenberger, G. and Fowles, R.: Treed avalanche forecasting: Mitigating avalanche danger utilizing bayesian additive regression trees, J. Forecasting, 36, 165–180, https://doi.org/10.1002/for.2421, 2016. a
Brabec, B. and Meister, R.: A nearest-neighbor model for regional avalanche forecasting, Ann. Glaciol., 32, 130–134, https://doi.org/10.3189/172756401781819247, 2001. a
Breiman, L., Freidman, J., Olshen, R., and Stone, C.: Classification and regression trees, Wadsworth statistics/probability series, Wadsworth International Group, Belmont, CA, USA, 1984. a
Canadian Avalanche Association: Observation Guidelines and Recording Standards for Weather, Snowpack, and Avalanches, Canadian Avalanche Association, Revelstoke, BC, available at: https://cdn.ymaws.com/www.avalancheassociation.ca/resource/resmgr/standards_docs/OGRS2016web.pdf (last access: 14 December 2020), 2016a. a
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Short summary
We investigate patterns in how avalanche forecasters characterize snow avalanche hazard with avalanche problem types. Decision tree analysis was used to investigate both physical influences based on weather and on snowpack variables and operational practices. The results highlight challenges with developing decision aids based on previous hazard assessments.
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