In 2010, Statham, Haegeli, 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.
Copyright is held by the author.
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Member of collection