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In 2010, Statham et al. (2018) introduced the Conceptual Model of Avalanche Hazard (CMAH) to improve transparency and consistency of avalanche bulletin production in North America. However, since the CMAH has no explicit link to the avalanche danger scale, forecasters must rely on their own judgment to assign danger ratings, which can lead to inconsistencies in public avalanche risk communication. My research aims to address this missing link by exploring the relationship between avalanche hazard assessments and danger rating assignments in public avalanche bulletins. Using conditional inference trees, key decision rules and components of the CMAH influencing danger rating assignments are extracted. While the analysis offers insights into the assignment rules, it also highlights substantial variability that cannot be explained by components of the CMAH. The results from this study offer a foundation for critically reviewing existing forecasting practices and developing evidence-based decision aids to increase danger rating consistency.
The application below allows you to explore Taylor’s analysis yourself. Use the controls on the left to specify the scenarios for your hazard chart visualization. The pie charts in the hazard chart present the probabilities of the different danger rating levels for the given combination of likelihood of avalanches and destructive size. The data foundation for these visualizations are all avalanche bulletins from Avalanche Canada and Parks Canada from 2012 to 2018. See Taylor’s thesis for more details.
These visualizations are for exploratory purposes only and do not come with any warranty. They should not be used as a decision aid.