Slab Avalanches Research Articles

Numerical investigation of crack propagation regimes in snow fracture experiments

A snow slab avalanche releases after failure initiation and crack propagation in a highly porous weak snow layer buried below a cohesive slab. While our knowledge of crack propagation during avalanche formation has greatly improved over the last decades, it still remains unclear how snow mechanical properties affect the dynamics of crack propagation. This is partly due to a lack of non-invasive measurement methods to investigate the micro-mechanical aspects of the process. Using a DEM model, we therefore analyzed the influence of snow cover properties on the dynamics of crack propagation in weak snowpack layers. By focusing on the steady-state crack speed, our results showed two distinct fracture process regimes that depend on slope angle, leading to very different crack propagation speeds. For long experiments on level terrain, weak layer fracture is mainly driven by compressive stresses. Steady-state crack speed mainly depends on slab and weak layer elastic moduli as well as weak layer strength. We suggest a semi-empirical model to predict crack speed, which can be up to 0.6 times the slab shear wave speed. For long experiments on steep slopes, a supershear regime appeared, where the crack propagation speed reached approximately 1.6 times the slab shear wave speed. A detailed micro-mechanical analysis of stresses revealed a fracture principally driven by shear. Overall, our findings provide new insight into the micro-mechanics of dynamic crack propagation in snow, and how these are linked to snow cover properties.Graphical

SLABS: An improved probabilistic method to assess the avalanche risk on backcountry ski tours

The main danger to which backcountry skiers are exposed are dry slab avalanches triggered by skiers themselves. In this paper we present a new probabilistic method to assess the avalanche risk when planning a ski tour: SLABS (Screening the Likelihood of Avalanches on Backcountry Ski tours). The SLABS method is the first fully statistically derived probabilistic method for backcountry skiing. We used a data set with GPS (Global Positioning System) tracks of backcountry ski tours (57.8 thousand km) and a data set of 1250 accidents recorded in Switzerland during the last 20 winter seasons. A GAM (Generalised Additive Model) with binomial link discriminating between accidents and non-accidents was fitted to these data. As predictors the model uses a non-linear relation with the slope angle, and a linear relation with the danger level, the elevation and the aspect. Conditions with elevated and high risk were defined such that the accident prevention rate is 80% and 60%, respectively. A comparison of the SLABS method with the Graphical Reduction Method (GRM), the Professional Reduction Method (PRM) and the Quantitative Reduction Method (QRM) shows that it offers more freedom of movement for a given accident prevention rate. It is the first time that probabilistic methods are compared in terms of their trade-off between accident prevention and freedom of movement. Because the SLABS method is not suited for mental arithmetic it is implemented in the website www.skitourenguru.ch. This website evaluates on a daily basis the avalanche risk along thousands of backcountry tours throughout the Alps to help skiers plan their next tour. For a single slope the risk assessment of SLABS provides a starting point that has to be supplemented with local observations.

Quantifying short-term changes in snow strength due to increasing liquid water content above hydraulic barriers

The rapid weakening of snow layers that accumulate infiltrating liquid water is a well-known, but poorly quantified, mechanism for wet-snow slab avalanche formation. Therefore, quantifying this mechanical process is a crucial part of forecasting these snow avalanches accurately. Currently, studies do not agree on how snow strength should change as a function of volumetric liquid water content (θ) and whether this relationship differs between snow types. Furthermore, strength measurements taken at or above θ=7% in snow are rare, so there is limited understanding at this end of the θ continuum. These levels of saturation can occur in the snow immediately above hydraulic barriers and are considered important for wet-snow slab avalanches to initiate. To address this knowledge gap, a blade hardness gauge (BHG, a.k.a. thin blade penetrometer) and SLF snow sensor were used to take 349 targeted paired measurements of strength and θ, respectively, in the snow above 19 manually wetted hydraulic (capillary) barriers. Using a multiple regression analysis, we developed an expression for the blade hardness of manually wetted snow as a function of θ, crystal form, and blade hardness prior to wetting (R2=0.85). To understand these results in terms of a common measure of snow strength, we also performed a comparison of the BHG and a shear frame in dry snow. The two instruments are highly linearly correlated (R2=0.94), allowing us to interpret our regression in terms of shear strength when compressive stress is low. Our results demonstrate that short-term (< 2 h) changes in snow strength due to increasing θ can differ between snow layers. These differences can be empirically modelled using easily measured dry snow properties (i.e. crystal form and blade hardness), which could allow avalanche forecasters to be more selective when identifying failure layers in advance of a wetting event.

A theoretical framework for dynamic anticrack and supershear propagation in snow slab avalanches

Snow slab avalanches release after the failure and collapse of a weak layer buried below a cohesive snow slab. The initial failure is induced by local overloading of the slab, such that the passage of a skier. This results in the propagation of a subsidence, known as a collapse wave or anticrack. The slab may eventually break and detach from the rest of the snowpack and start to slide down, provided that the slope is steep enough to enable gravity to overcome the friction at the interface between the slab and the failed weak layer.The approach to anticracks so far has mostly focused on (i) static configurations for the bending slab while the weak layer collapses, thereby leading to analytical conditions for the onset of an anticrack because of the metastability of the snowpack, and (ii) the observation of anticrack propagation as a result of numerical simulation methods (DEM, FEM, MPM) and field experiments (PST). The only theoretical framework to date, based on a simple modelling of the bending of the slab during the weak layer collapse, led to the well-known Heierli (2005) model which suggested an explicit solution for the propagation speed in steady state. It, however, could not account for the weak layer properties, was not mathematically bounded for certain values of the physical constants involved, and could not explain the newly uncovered “supershear” transition for steep slopes.In this paper, a new model for the stationary propagation of anticracks is set up, so as to account for the anticrack speed regime on the one hand, and the supershear regime on the other hand, the existence of which has been recently revealed and ascertained by numerical simulations. The results presented here seem consistent with most of the available data, and highlight the role that the compaction of the weak layer can play in reducing the anticrack speed. On the contrary, by storing energy upon failure and suddenly releasing it at the crack tip, the weak layer elasticity could help justify the higher speeds sometimes observed in both regimes. Finally, a more accurate model is proposed, based on the modelling of both the slab and the weak layer as Timoshenko beams; although its complexity prevents us from solving it analytically, it provides enlightening insights into the mechanical processes at work at the interface between both layers, from a strength-of-materials perspective.This analysis is a first step towards a better understanding of the underlying mechanisms of propagation of cracks in slab avalanches, and towards more accurate avalanche size and occurrence predictions.

A Depth‐Averaged Material Point Method for Shallow Landslides: Applications to Snow Slab Avalanche Release

AbstractShallow landslides pose a significant threat to people and infrastructure. Despite significant progress in the understanding of such phenomena, the evaluation of the size of the landslide release zone, a crucial input for risk assessment, still remains a challenge. While often modeled based on limit equilibrium analysis, finite or discrete elements, continuum particle‐based approaches like the Material Point Method (MPM) have more recently been successful in modeling their full 3D elasto‐plastic behavior. In this paper, we develop a depth‐averaged Material Point Method (DAMPM) to efficiently simulate shallow landslides over complex topography based on both material properties and terrain characteristics. DAMPM is a rigorous mechanical framework which is an adaptation of MPM with classical shallow water assumptions, thus enabling large‐deformation elasto‐plastic modeling of landslides in a computationally efficient manner. The model is here demonstrated on the release of snow slab avalanches, a specific type of shallow landslides which release due to crack propagation within a weak layer buried below a cohesive slab. Here, the weak layer is considered as an external shear force acting at the base of an elastic‐brittle slab. We verify our model against previous analytical calculations and numerical simulations of the classical snow fracture experiment known as Propagation Saw Test. Furthermore, large scale simulations are conducted to investigate cross‐slope crack propagation and the complex interplay between weak layer dynamic failure and slab fracture. In addition, these simulations allow us to evaluate and discuss the shape and size of avalanche release zones over different topographies. Given the low computational cost compared to 3D MPM, we expect our work to have important operational applications in hazard assessment, in particular for the evaluation of release areas, a crucial input for geophysical mass flow models. Our approach can be easily adapted to simulate both the initiation and dynamics of various shallow landslides, debris and lava flows, glacier creep and calving.

Using video detection of snow surface movements to estimate weak layer crack propagation speeds

Abstract Dry-snow slab avalanches release due to crack propagation in a weak snow layer under a cohesive snow slab. Crack propagation speeds can provide insights into the potential size of avalanches and inform fracture and avalanche release models. Despite their importance, slope-scale crack speed measurements from real avalanches are limited. Further, most existing slope-scale measurements utilize the appearance of slab fractures on the snow surface. However, we have no evidence that the appearance of surface cracking is a good indicator of the weak layer crack propagation tip. Here we present a novel method to estimate crack propagation speed from snow surface movements in avalanche videos. Our technique uses changes in frame pixel intensity, allowing us to detect the location of weak layer cracks well before slab fractures appear on the snow surface. We use field experiments and numerical simulations to validate our method before applying it to five avalanches. Our estimates show that cracks propagate faster up and down the slope than in the cross-slope direction; this suggests that different propagation regimes likely govern crack propagation up/down the slope, cross-slope and in flat terrain.

Snowpack and avalanche characterization over the 2021–2022 winter season in Sisimiut, West Greenland

In Greenland, snow avalanches have been recognized as a significant hazard and a risk to communities for decades. However, prior to this study, no formal avalanche database nor avalanche forecasting service existed in Greenland. This study was conducted over the 2021–2022 snow season to advance snow science research in Greenland and provide the town of Sisimiut with an avalanche bulletin service based on snowpack stability, weather conditions, and avalanche activity monitoring data within the Sisimiut backcountry. Snowpack stratigraphies were assessed and stability tests were performed periodically using standardized methods, and the results were linked with daily weather monitoring and avalanche event characterization. The observed avalanche activity was dominated by slab avalanches, accounting for 96% of the registered events. Instabilities were mainly driven by specific temperature patterns, strong winds, and rain episodes. During cold and calm periods, slow kinetic growth of snow crystals in low-density layers was observed. Abrupt thermal increases were recurrent, resulting in softening of superficial slabs with consequent reactivation of buried weak layers, thus reducing snowpack stability. On the other hand, prolonged warmer temperatures lowered the thermal gradient within the snowpack, leading to rounding and bonding of weak layer grains, thus recovering the snowpack stability. As observed on three occasions, rain events caused the formation of persistent weak layers and should be considered a warning for future snowpack instability. As a result of this study, we retroactively linked local weather patterns with snowpack instability and provided the first periodical avalanche bulletin service for Sisimiut.

A closed-form model for layered snow slabs

Abstract. We propose a closed-form analytical model for the mechanical behavior of stratified snow covers for the purpose of investigating and predicting the physical processes that lead to the formation of dry-snow slab avalanches. We represent the system of a stratified snow slab covering a collapsible weak layer by a beam composed of an arbitrary number of layers supported by an anisotropic elastic foundation in a two-dimensional plane-strain model. The model makes use of laminate mechanics and provides slab deformations, stresses in the weak layer, and energy release rates of weak-layer anticracks in real time. The quantities can be used in failure models of avalanche release. The closed-form solution accounts for the layering-induced coupling of bending and extension in the slab and of shear and normal stresses in the weak layer. It is validated against experimentally recorded displacement fields and a comprehensive finite-element model indicating very good agreement. We show that layered slabs cannot be homogenized into equivalent isotropic bodies and reveal the impact of layering on bridging with respect to weak-layer stresses and energy release rates. It is demonstrated that inclined propagation saw tests allow for the determination of mixed-mode weak-layer fracture toughnesses. Our results suggest that such tests are dominated by mode I when cut upslope and comprise significant mode II contributions when cut downslope. A Python implementation of the presented model is publicly available as part of the Weak Layer Anticrack Nucleation Model (WEAC) software package under https://github.com/2phi/weac (last access: 28 March 2023) and https://pypi.org/project/weac (last access: 28 March 2023, Rosendahl and Weißgraeber, 2022).

Temporal evolution of crack propagation characteristics in a weak snowpack layer: conditions of crack arrest and sustained propagation

Abstract. For a slab avalanche to release, we need sustained crack propagation in a weak snow layer beneath a cohesive snow slab – a process we call dynamic crack propagation. Field measurements on crack propagation are very scarce. We therefore performed a series of crack propagation experiments, up to 9 m long, over a period of 10 weeks and analysed these using digital image correlation techniques. We derived the elastic modulus of the slab (0.5 to 50 MPa), the elastic modulus of the weak layer (50 kPa to 1 MPa) and the specific fracture energy of the weak layer (0.1 to 1.5 J m−2) with a homogeneous and a layered-slab model. During crack propagation, we measured crack speed, touchdown distance, and the energy dissipation due to compaction and dynamic fracture (5 mJ m−2 to 0.43 J m−2). Crack speeds were highest for experiments resulting in full propagation, and crack arrest lengths were always shorter than touchdown lengths. Based on these findings, an index for self-sustained crack propagation is proposed. Our data set provides unique insight and valuable data to validate models.

What weather variables are important for wet and slab avalanches under a changing climate in a low-altitude mountain range in Czechia?

Abstract. Climate change impact on avalanches is ambiguous. Fewer, wetter, and smaller avalanches are expected in areas where snow cover is declining, while in higher-altitude areas where snowfall prevails, snow avalanches are frequently and spontaneously triggered. In the present paper, we (1) analyse trends in frequency, magnitude, and orientation of wet- and slab-avalanche activity during 59 winter seasons (1962–2021) and (2) detect the main meteorological and snow drivers of wet and slab avalanches for winter seasons from 1979 to 2020 using machine learning techniques – decision trees and random forest – with a tool that can balance the avalanche-day and non-avalanche-day dataset. In terms of avalanches, low to medium–high mountain ranges are neglected in the literature. Therefore we focused on the low-altitude Czech Krkonoše mountain range (Central Europe). The analysis is based on an avalanche dataset of 60 avalanche paths. The number and size of wet avalanches in February and March have increased, which is consistent with the current literature, while the number of slab avalanches has decreased in the last 3 decades. More wet-avalanche releases might be connected to winter season air temperature as it has risen by 1.8 ∘C since 1979. The random forest (RF) results indicate that wet avalanches are influenced by 3 d maximum and minimum air temperature, snow depth, wind speed, wind direction, and rainfall. Slab-avalanche activity is influenced by snow depth, rainfall, new snow, and wind speed. Based on the balanced RF method, air-temperature-related variables for slab avalanches were less important than rain- and snow-related variables. Surprisingly, the RF analysis revealed a less significant than expected relationship between the new-snow sum and slab-avalanche activity. Our analysis allows the use of the identified wet- and slab-avalanche driving variables to be included in the avalanche danger level alerts. Although it cannot replace operational forecasting, machine learning can allow for additional insights for the decision-making process to mitigate avalanche hazard.

Laboratory set-up for surface hoar layer growth over rounded grain snow

Growth of surface hoar (SH) crystals by deposition of water vapour onto the snow surface and their subsequent burial by snowfall leads to the formation of a persistent weak SH layer in mountain snowpack of Greater Himalayas. The mechanical properties and failure behaviour of SH layers are critical for avalanche hazard assessment as failure of buried SH layers is frequently the primary cause for the release of dry snow slab avalanches. However, extraction of snow samples containing sandwiched SH layer and their transportation to cold laboratory for experimentation is extremely difficult due to the fragile nature of SH layer. To overcome this limitation, we developed a setup that mimics the natural environmental conditions under which the SH crystals grow. The setup consists of a hot (Th = 1oC) and a cold (Tc = − 25oC) environmental chambers which are connected via an air-duct. The warm air from hot chamber is driven over a water bath through the air-duct towards the cold chamber. A sieved snow sample of desired dimension, which act as the base snow layer, is placed just below the air-duct outlet inside the cold chamber. Difference between the temperature and water vapour pressure of the air at duct outlet, and the surface of base snow layer, resulted in the deposition of water vapour and growth of SH crystals on the exposed snow surface. The growth of SH crystals was primarily observed in the direction normal to the snow surface while their typical shapes were predominantly plates, sector plates and dendrite. With the present setup, an SH layer of ∼10 mm thickness over a base snow layer of surface area 0.07 m2 could be grown within a time interval of ∼13 hr. The average growth rate of SH layer is found to be in the range of ∼0.5 − 0.9 mm hr−1 and the accommodation coefficient of water vapour derived from the analysis of growth measurements varied between α = 0.54 − 0.94 under different experimental conditions. Comparison of cumulative mass of deposited water vapour with measured SH layer thickness also yielded an apparent SH density of 42.5 kg m−3. The strength values (0.6 − 2.2 kPa) of snow samples with artificially grown sandwiched SH layer prepared in this study matches closely with weak layer strength reported in literature thereby indicating the usefulness of present experimental setup for investigating the multi-axial failure behaviour of surface hoar under controlled conditions.

Modeling weak snow layer fracture in propagation saw test using an ice column model

ABSTRACT Fracture initiation and propagation in a weak snow layer are two primary processes of the slab avalanche formation process. This study proposes a model for the weak snow layer and investigates the fracture propagation process. The weak snow layer is conceptualized as columns of ice sandwiched between two strong layers of snow. The strong layers are modeled as linear elastic, whereas the ice is characterized as a damaging elastoplastic material. The effective mechanical properties of the model weak layer are examined using finite element analysis and are close to the snow properties reported in the literature. This model is used in numerical propagation saw tests (PSTs) to investigate the fracture propagation process in the weak snow layer. Critical crack length (CCL) and fracture propagation speed (FPS) in PST simulations are obtained by tracking the crack tip and are in good agreement with the previously reported results. An insight into the fracture propagation process in the weak snow layer is presented through energy variation analysis in PST simulations and shown that the FPS during dynamic fracture propagation varies with the top slab’s elastic modulus, the weak layer’s fracture energy, and inertia of the overlying slab.

Predicting mixed mode damage propagation in snowpack using the extended cohesive damage element method

A novel extended cohesive damage element method is used to develop a numerical snowpack model to study the fundamental damage mechanisms of snowpack under external drivers and to investigate multiple mixed mode damage propagation within snowpack. A new mixed mode damage criterion is introduced to account for tensile and shear fractures as well as compressive crushing together with shear crack for approximating the mixed mode damage initiation and propagation in the weak layer in snowpack. A propagation saw test (PST) is considered to understand basic damage involution in snowpack under self-weight related bending. The nonlinear fracture modelling prediction agrees with the PST sample well. This paper provides an alternative approach as a predictive method using the extended cohesive damage element for potentially forecasting slab avalanches in snow terrain according to weather forecast and planned human activities in the future.

Transition from sub-Rayleigh anticrack to supershear crack propagation in snow avalanches

Snow slab avalanches, characterized by a distinct, broad fracture line, are released following anticrack propagation in highly porous weak snow layers buried below cohesive slabs. The anticrack mechanism is driven by the volumetric collapse of the weak layer, which leads to the closure of crack faces and to the onset of frictional contact. Here, on the basis of snow fracture experiments, full-scale avalanche measurements and numerical simulations, we report the existence of a transition from sub-Rayleigh anticrack to supershear crack propagation. This transition follows the Burridge–Andrews mechanism, in which a supershear daughter crack nucleates ahead of the main fracture front and eventually propagates faster than the shear wave speed. Furthermore, we show that the supershear propagation regime can exist even if the shear-to-normal stress ratio is lower than the static friction coefficient as a result of the loss of frictional resistance during collapse. This finding shows that snow slab avalanches have fundamental similarities with strike-slip earthquakes.

Satellite detection of snow avalanches using Sentinel-1 in a transitional snow climate

Snow avalanches endanger lives and infrastructure in mountainous regions worldwide. Consistent and accurate datasets of avalanche events are critical for improving hazard forecasting and understanding the spatial and temporal patterns of avalanche activity. Remote sensing-based identification of avalanche debris allow for the acquisition of continuous and spatially consistent avalanches datasets. This study utilizes expert manual interpretations of Sentinel-1 synthetic aperture radar (SAR) satellite backscatter images to identify avalanche debris and compares those detections against historical field records of observed avalanches in the transitional snow climates of Wyoming and Utah, USA. We explore and quantify the ability of an expert using Sentinel-1 (a SAR satellite) images to detect avalanche debris on a dataset comprised exclusively of dry slab avalanches. This research utilized four avalanche cycles with 258 field reported avalanches. Due to individual avalanches appearing in multiple overlapping Sentinel-1 images this resulted in 506 potential detections of avalanches in our SAR images, representing the possibility of multiple detections of a single avalanche event in different images. The overall probability of detection (POD) for avalanches large enough to destroy trees or bury a car (i.e., ≥D3 on the destructive size scale) was 65%. There was a significant variance in the POD among the 13 individual SAR image pairs considered (15–86%). Additionally, this study investigated the connection between successful avalanche detections and SAR-specific, topographic, and avalanche type variables. The most correlated variables with higher detection rates were avalanche path lengths, destructive size of the avalanche, incidence angles for the incoming microwaves, average path slope angle, and elapsed time between the avalanche and a Sentinel-1 satellite image acquisition. This study provides a quantification of the controlling variables in the likelihood of detecting avalanches using Sentinel-1 backscatter temporal change detection techniques, as specifically applied to a transitional snow climate.

Performance of manual and automatic detection of dry snow avalanches in Sentinel-1 SAR images

Radar satellite-borne snow avalanche detection has rapidly grown into an important method for monitoring of avalanche activity over large spatial and long temporal scales. With increased application of Sentinel-1 data for avalanche detection, the need for improved performance evaluation arises. In this study, we make use of a unique dataset of field-based avalanche observations from eight adjacent avalanche paths at lake Tyin in central Norway. The dataset is a complete record of 318 dry slab avalanches that released during the winters 2016–2020, with information on release timing and extent. The dataset thus allows for detailed evaluation of the performance of automatic and manual avalanche detection in Sentinel-1 images, were both techniques make use of relative temporal backscatter intensity increase in case of an avalanche. Both automatic and manual detection underperform compared to previous studies with a probability of detection (POD) of 5.9% (false alarm rate (FAR) of 5.9%) and 11.3% (FAR of 19.27%) respectively. From the low relative backscatter intensity contrast of field-observed dry slab avalanches, it becomes evident that a higher backscatter contrast between avalanches and surrounding is needed for detectability in Sentinel-1 images. Neither the lag time between avalanche release and detection in a Sentinel-1 image, nor local incidence angle can explain the low POD's. Moreover, an analysis of meteorological conditions prior a during avalanche release and/or detection can explain the low POD's, given that differing snow conditions influence radar backscatter intensity. Finally, we cannot rule out that the small dataset of field-observed avalanches and the one-directional slope aspect of the study area influence our results, however, we believe that a physical limit of detectability of dry snow avalanches in C-band radar satellite data is reached.

Crack propagation speeds in weak snowpack layers

AbstractFor the release of a slab avalanche, crack propagation within a weak snowpack layer below a cohesive snow slab is required. As crack speed measurements can give insight into underlying processes, we analysed three crack propagation events that occurred in similar snowpacks and covered all scales relevant for avalanche release. For the largest scale, up to 400 m, we estimated crack speed from an avalanche movie; for scales between 5 and 25 m, we used accelerometers placed on the snow surface and for scales below 5 m, we performed a propagation saw test. The mean crack speeds ranged from 36 ± 6 to 49 ± 5 m s−1, and did not exhibit scale dependence. Using the discrete element method and the material point method, we reproduced the measured crack speeds reasonably well, in particular the terminal crack speed observed at smaller scales. Finally, we used a finite element model to assess the speed of different elastic waves in a layered snowpack. Results suggest that the observed cracks propagated as mixed mode closing cracks and that the flexural wave of the slab is responsible for the energy transfer to the crack tip.

Reconstructing the Snow Avalanche of Coll de Pal 2018 (SE Pyrenees)

Developments in mountain areas prone to natural hazards produce undesired impacts and damages. Thus, disaster assessment is mandatory to understand the physics of dangerous events and to make decisions to prevent hazardous situations. This work focusses on the practical implementation of methods and tools to assess a snow avalanche that affected a road at the Coll de Pal in 2018 (SE Pyrenees). This is a quite common situation in mountain roads and the assessment has to focus specially in the avalanche–road interaction, on the return periods considered and on the dynamics of the phenomena. This assessment presents the field recognition, snow and weather characterization and numerical modelling of the avalanche. Field campaigns revealed evidences of the avalanche triggering, runout trajectory and general behavior. An unstable situation of the snowpack due to a relatively large snowfall fallen some days before over a previous snowpack with weak layers, caused the avalanche triggering when an additional load was added by a strong wind-drift episode. A medium size (&lt;2500 m3) soft slab avalanche, corresponding to a return period of 15–20 years, occurred and crossed the road of the Coll de Pal pass. The event was reproduced numerically by means of the 2D-SWE based numerical tool Iber aiming to analyze the avalanche behavior. Results of the simulation corresponded with the observations (runout trajectory and snow deposit); thus, relevant information about the avalanche dynamics could be obtained. Identified differences probably come from the terrain elevation data, which represent “snow free” topography and do not consider the snowpack on the terrain.

Micro-mechanical insights into the dynamics of crack propagation in snow fracture experiments

Dry-snow slab avalanches result from crack propagation in a highly porous weak layer buried within a stratified and metastable snowpack. While our understanding of slab avalanche mechanisms improved with recent experimental and numerical advances, fundamental micro-mechanical processes remain poorly understood due to a lack of non-invasive monitoring techniques. Using a novel discrete micro-mechanical model, we reproduced crack propagation dynamics observed in field experiments, which employ the propagation saw test. The detailed microscopic analysis of weak layer stresses and bond breaking allowed us to define the crack tip location of closing crack faces, analyze its spatio-temporal characteristics and monitor the evolution of stress concentrations and the fracture process zone both in transient and steady-state regimes. Results highlight the occurrence of a steady state in crack speed and stress conditions for sufficiently long crack propagation distances (> 4 m). Crack propagation without external driving force except gravity is possible due to the local mixed-mode shear-compression stress nature at the crack tip induced by slab bending and weak layer volumetric collapse. Our result shed light into the microscopic origin of dynamic crack propagation in snow slab avalanche release that eventually will improve the evaluation of avalanche release sizes and thus hazard management and forecasting in mountainous regions.

Using avalanche problems to examine the effect of large-scale atmosphere–ocean oscillations on avalanche hazard in western Canada

Abstract. Numerous large-scale atmosphere–ocean oscillations including the El Niño–Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the Pacific North American Teleconnection Pattern (PNA), and the Arctic Oscillation (AO) are known to substantially affect winter weather patterns in western Canada. Several studies have examined the effect of these oscillations on avalanche hazard using long-term avalanche activity records from highway avalanche safety programmes. We present a new approach for gaining additional insight into these relationships that uses avalanche problem information published in public avalanche bulletins during the winters of 2010 to 2019. For each avalanche problem type, we calculate seasonal prevalence values for each forecast area, elevation band, and season, which are then included in a series of beta mixed-effects regression models to explore both the overall and regional effects of the Pacific-centered oscillations (POs; including ENSO, PDO, and PNA) and AO on the nature of avalanche hazard in the study area. We find significant negative effects of PO on the prevalence of storm slab avalanche problems, wind slab avalanche problems, and dry loose avalanche problems, which agree reasonably well with the known impacts of PO on winter weather in western Canada. The analysis also reveals a positive relationship between AO and the prevalence of deep persistent slab avalanche problems, particularly in the Rocky Mountains. In addition, we find several smaller-scale patterns that highlight that the avalanche hazard response to these oscillations varies regionally. Even though our study period is short, our study shows that the forecaster judgement included in avalanche problem assessments can add considerable value for these types of analyses. Since the predictability of the most important atmosphere–ocean oscillations is continuously improving, a better understanding of their effect on avalanche hazard can contribute to the development of informative seasonal avalanche forecasts in a relatively simple way.