Scan Science and Technology
Contact Leading Edge Experts & Companies
Avalanches
The Experts below are selected from a list of 115797 Experts worldwide ranked by ideXlab platform
Perry Bartelt – One of the best experts on this subject based on the ideXlab platform.
-
Point release wet snow Avalanches
Natural Hazards and Earth System Sciences Discussions, 2015Co-Authors: C. Vera Valero, Yves Buhler, Perry BarteltAbstract:Abstract. Wet snow Avalanches can initiate from large fracture slabs or small point releases. Point release wet snow Avalanches can reach dangerous proportions when they (1) initiate on steep and long avalanche paths and (2) entrain warm moist snow. In this paper we investigate the dynamics of point release wet snow Avalanches by applying a numerical model to simulate documented case studies on high altitude slopes in the Chilean Andes (33° S). The model predicts avalanche flow temperature as well as meltwater production, given the thermal initial conditions of the release mass and snowcover entrainment. As the release mass is small, avalanche velocity and runout are primarily controlled by snowcover temperature and moisture content. We demonstrate how the interaction between terrain and entrainment processes influence the production of meltwater and therefore lubrication processes leading to longer runout. This information is useful to avalanche forecasters. An understanding of wet snow avalanche dynamics is important to study how climate change scenarios will influence land usage in mountain regions in the near future.
-
Chapter 12 – Snow Avalanches
Snow and Ice-Related Hazards Risks and Disasters, 2015Co-Authors: Jurg Schweizer, Perry Bartelt, Alec Van HerwijnenAbstract:Snow Avalanches are a major natural hazard in most snow-covered mountain areas of the world. They are rapid, gravity-driven mass movements and are considered a meteorologically induced hazard. Snow Avalanches are one of the few hazards that can be forecast, and in situ measurements of instability are feasible. Advanced hazard-mitigation measures exist, such as land-use planning based on modeling avalanche dynamics. The most dangerous snow Avalanches start as a dry-snow, slab avalanche that is best described with a fracture mechanical approach. How fast and how far an avalanche flows is the fundamental question in avalanche engineering. Models of different levels of physical complexity enable the prediction of avalanche motion. Although the avalanche danger (probability of occurrence) for a given region can be forecast—in most countries with significant avalanche hazard, avalanche warnings are issued on a regular basis—the prediction of a single event in time and space is not (yet) possible.
-
MODELLING SMALL AND FREQUENT Avalanches
, 2014Co-Authors: Lisa Dreier, Thomas Feistl, Yves Buhler, Marc Christen, Walter Steinkogler, Perry BarteltAbstract:Numerical simulation tools are commonly used to model extreme events, that is Avalanches with return periods of 30 years or more. Recently, a new demand has arisen in avalanche engineering practice: the modelling of “small”, frequent Avalanches. These Avalanches with release volumes between 1,000 10,000 m 3 often threaten traffic infrastructure and ski runs. In this paper we apply a new physical avalanche model to simulate “small”, frequent Avalanches using high spatial resolution DEM data. The case studies consist of Avalanches documented in the Swiss accident database. For these Avalanches, we have reliable data concerning release location, fracture height, run-out distance and snow temperatures at time of release. Photographs provide information regarding snow cover entrainment. A set of model parameters was determined which depends on the avalanche flow type and hence on snow temperature. We explicitly avoided changing parameters according to avalanche size. The Avalanches were simulated according to the temperature classification scheme we established. We analyzed the impact of the release location, release height and entrainment on the avalanche run-out. Our results highlight the importance of release zone definition, release height, snow temperature and the difference between summer and winter terrain models for small-scale Avalanches. We plan to apply the findings of this study to produce a small-scale avalanche simulation tool intended to support persons in charge of ski resorts and traffic infrastructure.
Karl W Birkeland – One of the best experts on this subject based on the ideXlab platform.
-
meteorological variables associated with deep slab Avalanches on persistent weak layers
International Snow Science Workshop 2014 Proceedings Banff Canada, 2014Co-Authors: Alex Marienthal, Karl W Birkeland, Jordy Hendrikx, Kathryn M. IrvineAbstract:Deep slab Avalanches are a particularly challenging avalanche forecasting problem. These Avalanches are typically difficult to trigger, yet when they release they tend to propagate far and can result in large and destructive Avalanches. For this work we define deep slab Avalanches as those that fail on persistent weak layers deeper than 0.9m (3 feet), and that occur after February 1. We utilized a 44year record of avalanche control and meteorological data from Bridger Bowl Ski Area in southwest Montana to test the usefulness of meteorological variables for predicting seasons with deep slab Avalanches. While previous studies often exclusively use data from the days preceding deep slab cycles, we include meteorological metrics over the early months of the season when persistent weak layers form. We used classification trees for our analyses. Our results showed that seasons with Avalanches on deep persistent weak layers typically had drier early months, and often had maximum snow depth greater than 88cm in November, which provided ideal conditions for persistent weak layer development. This paper provides insights for ski patrollers, guides, and avalanche forecasters who seek to understand the seasonal conditions that are conducive to deep slab Avalanches on persistent weak layers later in the season.
-
storm snow Avalanches characteristics and forecasting
Proceedings 2012 International Snow Science Workshop Anchorage Alaska, 2012Co-Authors: Edward H. Bair, Karl W Birkeland, Ron Simenhois, Jeff DozierAbstract:At ski areas, a majority of Avalanches fail in storm snow. We investigate these Avalanches using stability tests and avalanche observations from California and Alaska. Collapse amplitudes during fracture, measured using particle tracking, were 1 mm for a failure layer of precipitation particles and 7 mm for a layer of unrimed sectored plates. Stability test results showed little dependence on slope angle, suggesting that both precipitation particles and older faceted crystals (persistent weak layers) fail as described by the anticrack model, with collapse providing energy. Using observations from avalanche control work at Mammoth Mountain, CA USA, a large coastal ski area where 9/10 Avalanches fail in storm snow, we examined Extended Column Test (ECT) results and their relation to avalanche activity. ECT propagation was a powerful predictor; days with ECTs that propagated had significantly more and larger Avalanches. Since other studies have shown that the ECT is an effective predictor of Avalanches involving persistent weak layers, we suggest that the ECT is an effective test to predict both types of Avalanches, those that fail in storm snow and those that fail on persistent weak layers.
-
meteorological and environmental observations from three glide avalanche cycles and the resulting hazard management technique
2010 International Snow Science Workshop, 2010Co-Authors: Ron Simenhois, Karl W BirkelandAbstract:Glide Avalanches are a significant hazard that threatens people and property in many snowy climates. They are hard to control, poorly understood, and extremely challenging to forecast. This paper presents meteorological and environmental data associated with three glide avalanche cycles. It also discusses hazard reduction techniques from an operational perspective and provides possible explanations why previous attempts to artificially trigger glide Avalanches rarely succeed. During Southeast Alaska’s winter of 09/10, we witnessed three glide avalanche cycles with over 35 total Avalanches. During those cycles we collected data on snowpack, precipitation, temperature, relative humidity, sky coverage and streamflow, as well as slope aspect, elevation, steepness, shape and ground cover. We also recorded visual snow surface observations leading to the transition of some of the glide cracks to Avalanches. Although glide avalanche activity is clearly somehow related to atmospheric events, we found no direct correlation between meteorological data and avalanche occurrences. However, we did find a rough correlation between snowpack, terrain and avalanche time distribution in two out of the three cycles. Our lack of reliable forecasting and control tools for glide Avalanches implies that limiting the potential destructive size of glide Avalanches throughout the entire winter may be the most effective approach to managing the hazard for some operations.
Jurg Schweizer – One of the best experts on this subject based on the ideXlab platform.
-
On the relation between avalanche occurrence and avalanche danger
level, 2019Co-Authors: Jurg Schweizer, Christoph Mitterer, Frank Techel, Andreas Stoffel, Benjamin ReuterAbstract:Abstract. In many countries with seasonally snow-covered mountain ranges warnings are issued to alert the public about imminent avalanche danger, mostly employing a 5-level danger scale. However, as avalanche danger cannot be measured, the charac-terization of avalanche danger remains qualitative. The probability of avalanche occurrence in combination with the ex-pected avalanche type and size decide on the degree of danger in a given forecast region (≳ 100 km2). To describe ava-lanche occurrence probability the snowpack stability and its spatial distribution need to be assessed. To quantify the rela-tion between avalanche occurrence and avalanche danger level we analyzed a large data set of visually observed ava-lanches from the region of Davos (Eastern Swiss Alps), all with mapped outlines, and compared the avalanche activity to the forecast danger level on the day of occurrence. The number of Avalanches per day strongly increased with increasing danger level confirming that not only the release probability but also the frequency of locations with a weakness in the snowpack where Avalanches may initiate from, increases within a region. Avalanche size did in general not increase with increasing avalanche danger level, suggesting that avalanche size may be of secondary importance compared to snowpack stability and its distribution when assessing the danger level. Moreover, the frequency of wet-snow Avalanches was found to be higher than the frequency of dry-snow Avalanches on a given day; also, wet-snow Avalanches tended to be larger. This finding may indicate that the danger scale is not used consistently with regard to avalanche type. Although, observed ava-lanche occurrence and avalanche danger level are subject to uncertainties, our findings on the characteristics of avalanche activity may allow revisiting the definitions of the European avalanche danger scale. The description of the danger levels can be improved, in particular by quantifying some of the many proportional quantifiers. For instance, ‘many Avalanches’, expected at danger level 4–High, means on the order of 10 Avalanches per 100 km2. Whereas our data set is one of the most comprehensive, visually observed avalanche records are known to be inherently incomplete so that our results often refer to a lower limit and should be confirmed using other similarly comprehensive data sets.
-
Forecasting snow Avalanches using avalanche activity data obtained through seismic monitoring
Cold Regions Science and Technology, 2016Co-Authors: A. Van Herwijnen, Matthias Heck, Jurg SchweizerAbstract:Abstract Accurate avalanche occurrence data are of crucial importance for avalanche forecasting, since recent avalanching provides direct evidence on snowpack instability. We therefore explore how avalanche activity data obtained through seismic monitoring can be used for avalanche forecasting. By visually inspecting data from a seismic sensor deployed in an avalanche starting zone, we obtained three avalanche catalogues for two entire winters and one period of 10 days with intense wet-snow avalanche activity. Avalanche activity was clustered in time for all catalogues, and diurnal periodicity was clearly present during spring. In winter, when dry-snow Avalanches predominantly release, rather weak long-term correlations on the order of several days were found between past and future avalanche activity. We investigated the performance of a simple model to predict future Avalanches based on past avalanche activity. Model performance was better in spring than in winter, especially for very short time scales of up to 3h , and for time scales around 24 h. Furthermore, the performance of our very simple model was comparable to the performance of more sophisticated models to forecast wet-snow avalanche release based on meteorological input variables. While it is clear that for operational avalanche forecasting automatic avalanche detection still has to be developed, overall this work shows that avalanche activity data obtained through seismic monitoring would yield very valuable data for wet-snow avalanche forecasting.
-
Chapter 12 – Snow Avalanches
Snow and Ice-Related Hazards Risks and Disasters, 2015Co-Authors: Jurg Schweizer, Perry Bartelt, Alec Van HerwijnenAbstract:Snow Avalanches are a major natural hazard in most snow-covered mountain areas of the world. They are rapid, gravity-driven mass movements and are considered a meteorologically induced hazard. Snow Avalanches are one of the few hazards that can be forecast, and in situ measurements of instability are feasible. Advanced hazard-mitigation measures exist, such as land-use planning based on modeling avalanche dynamics. The most dangerous snow Avalanches start as a dry-snow, slab avalanche that is best described with a fracture mechanical approach. How fast and how far an avalanche flows is the fundamental question in avalanche engineering. Models of different levels of physical complexity enable the prediction of avalanche motion. Although the avalanche danger (probability of occurrence) for a given region can be forecast—in most countries with significant avalanche hazard, avalanche warnings are issued on a regular basis—the prediction of a single event in time and space is not (yet) possible.