Linking avalanche problem types to modelled weather and snowpack conditions: A pilot study in Glacier National Park, British Columbia

Author: 
Date created: 
2019-12-13
Identifier: 
etd20669
Keywords: 
Numeric weather prediction models
Snow cover models
Avalanche problem types
Avalanche forecasting
SNOWPACK model
Conditional inference trees
Abstract: 

To help amateur recreationists to make better informed decisions about when and where to travel in the backcountry, Canadian avalanche bulletins include structured information on the nature of avalanche problems of concern. Using conditional inference trees, this study explores the relationships between modelled weather and snowpack conditions and avalanche problems identified by forecasters in Glacier Nation Park, British Columbia, during the 2013 to 2018 winter seasons to better understand what makes avalanche forecasters identify individual avalanche problem types and explore possibilities for predicting avalanche problems in data-spare regions using numerical models. The results confirm the influence of the expected weather and snowpack variables and provide useful additional insight into forecaster practices when making decisions about avalanche problems. This study provides an important step for integrating avalanche problems and the Conceptual Model of Avalanche Hazard into existing weather and snowpack model chains and making avalanche bulletins in Canada more consistent.

Document type: 
Graduating extended essay / Research project
Rights: 
This thesis may be printed or downloaded for non-commercial research and scholarly purposes. Copyright remains with the author.
File(s): 
Senior supervisor: 
Pascal Haegeli
Department: 
Environment: School of Resource and Environmental Management
Thesis type: 
(Project) M.R.M. (Planning)
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