Abstract
Abstract. Deep persistent slab avalanches are capable of destroying infrastructure and are usually unsurvivable for those who are caught. Formation of a snowpack conducive to deep persistent slab avalanches is typically driven by meteorological conditions occurring in the beginning weeks to months of the winter season, and yet the avalanche event may not occur for several weeks to months later. While predicting the exact timing of the release of deep persistent slab avalanches is difficult, onset of avalanche activity is commonly preceded by rapid warming, heavy precipitation, or high winds. This work investigates the synoptic drivers of deep persistent slab avalanches at three sites in the western USA with long records: Bridger Bowl, Montana; Jackson, Wyoming; and Mammoth Mountain, California. We use self-organizing maps to generate 20 synoptic types that summarize 5899 daily 500 mbar geopotential height maps for the winters (November–March) of 1979/80–2017/18. For each of the three locations, we identify major and minor deep persistent slab avalanche seasons and analyze the number of days represented by each synoptic type during the beginning (November–January) of the major and minor seasons. We also examine the number of days assigned to each synoptic type during the 72 h preceding deep persistent slab avalanche activity for both dry and wet slab events. Each of the three sites exhibits a unique distribution of the number of days assigned to each synoptic type during November–January of major and minor seasons and for the 72 h period preceding deep persistent slab avalanche activity. This work identifies the synoptic-scale atmospheric circulation patterns contributing to deep persistent slab instabilities and the patterns that commonly precede deep persistent slab avalanche activity. By identifying these patterns, we provide an improved understanding of deep persistent slab avalanches and an additional tool to anticipate the timing of these difficult-to-predict events.
Subject
General Earth and Planetary Sciences
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