Documenting, quantifying, and modeling a large glide avalanche in Glacier National Park, Montana, USA

Abstract

Glide avalanches present a significant and repetitive challenge to many operational forecasting programs, and they are likely to become more frequent. While the spatial location of glide release areas is extremely consistent, the onset of glide avalanche release is notoriously difficult to forecast, and their destructive potential can be immense. Thus, the timing and dynamics of glide avalanches is an important area of study. To better understand these processes, and to improve assessments of risk to transportation corridors and infrastructure, event documentation is key. Here, we survey a large glide avalanche event along the Going-to-the-Sun Road in Glacier National Park, Montana, USA, during road opening operations in the spring of 2022. Using three sets of terrestrial lidar data (pre-event, post-event, and snow-off), we quantified key aspects of the avalanche and created powerful visualizations for analysis. Further, we evaluated meteorological data from automated weather stations between the onset of glide cracking and avalanche release. Last, we synthesized lidar data with a numerical dynamics model to replicate the event in a simulated environment. Using the tuned model, we determined the critical mean snow depth in the release area necessary for an avalanche to reach the road (4.2 m). Our method may be of particular use for glide avalanches, which tend to release in roughly the same place and time each year at a known interface. This could make the calculated critical depths more consistently reliable and preclude the need for additional tuning in dynamics models. As 1) lidar technology continues to improve and reduce in cost, 2) transportation corridors continue to extend into avalanche terrain, and 3) glide avalanches potentially become increasingly frequent, the synthesis outlined here provides a valuable tool for operational forecasters considering infrastructure threatened by glide events.