Snow Cover Model SNOWPACK Research Articles

Geotextile protection of glacier: Observed and simulated impacts on energy and mass balance

The detailed physical processes involved in slowing glacier ablation by material cover remain poorly understood so far. In the present study, using the snow cover model SNOWPACK, the effect of geotextile cover on the energy and mass balance at the tongue of the Urumqi Glacier No. 1 (Chinese Tien Shan) was simulated between July 12, 2022 and August 31, 2022. The mass changes and the energy fluxes with and without material cover were compared. The results indicated that the geotextile covering reduced glacier ablation by approximately 68% compared to the ablation in the uncovered regions. The high solar reflectivity of the geotextile reduced the net short-wave radiation energy available for the melt by 45%. Thermal insulation of the geotextile reduced the sensible heat flux by 15%. In addition, the wet geotextile exerted a cooling effect through long-wave radiation and negative latent heat flux. This cooling effect reduced the energy available for ablation by 20%. Consequently, only 37% of the energy was used for melting compared to that used in the uncovered regions (67%). Sensitivity experiments revealed that the geotextile cover used at a thickness range of 0.045–0.090 m reduced the ice loss by approximately 68%–72%, and a further increase in the thickness of the geotextile cover led to little improvements. A higher temperature and greater wind speed increased glacier ablation, although their effects were small. When the precipitation was set to zero, it led to a significantly increased melt. Overall, the geotextile effectively protected the glacier tongue from rapid melting, and the observed results have provided inspiration for developing an effective and sustainable approach to protect the glaciers using geotextile cover.

Introducing CRYOWRF v1.0: multiscale atmospheric flow simulations with advanced snow cover modelling

Abstract. Accurately simulating snow cover dynamics and the snow–atmosphere coupling is of major importance for topics as wide-ranging as water resources, natural hazards, and climate change impacts with consequences for sea level rise. We present a new modelling framework for atmospheric flow simulations for cryospheric regions called CRYOWRF. CRYOWRF couples the state-of-the-art and widely used atmospheric model WRF (the Weather Research and Forecasting model) with the detailed snow cover model SNOWPACK. CRYOWRF makes it feasible to simulate the dynamics of a large number of snow layers governed by grain-scale prognostic variables with online coupling to the atmosphere for multiscale simulations from the synoptic to the turbulent scales. Additionally, a new blowing snow scheme is introduced in CRYOWRF and is discussed in detail. CRYOWRF's technical design goals and model capabilities are described, and the performance costs are shown to compare favourably with existing land surface schemes. Three case studies showcasing envisaged use cases for CRYOWRF for polar ice sheets and alpine snowpacks are provided to equip potential users with templates for their research. Finally, the future roadmap for CRYOWRF's development and usage is discussed.

Observations and simulations of new snow density in the drifting snow-dominated environment of Antarctica

AbstractOwing to drifting snow processes, snow accumulation and surface density in polar environments are variable in space and time. We present new field data of manual measurements, repeat terrestrial laser scanning and snow micro-penetrometry from Dronning Maud Land, Antarctica, showing the density of new snow accumulations. We combine these data with published drifting snow mass flux observations, to evaluate the performance of the 1-D, detailed, physics-based snow cover model SNOWPACK in representing drifting snow and surface density. For two sites in East Antarctica with multiple years of data, we found a coefficient of determination for the simulated drifting snow ofr2= 0.42 andr2= 0.50, respectively. The field observations show the existence of low-density snow accumulations during low wind conditions. Successive high wind speed events generally erode these low-density layers while producing spatially variable erosion/deposition patterns with typical length scales of a few metres. We found that a model setup that is able to represent low-density snow accumulating during low wind speed conditions, as well as subsequent snow erosion and redeposition at higher densities during drifting snow events was mostly able to describe the observed temporal variability of surface density in the field.

Effect of snowfall on changes in relative seismic velocity measured by ambient noise correlation

Abstract. In mountainous, cold temperate and polar sites, the presence of snow cover can affect relative seismic velocity changes (dV/V) derived from ambient noise correlation, but this relation is relatively poorly documented and ambiguous. In this study, we analyzed raw seismic recordings from a snowy flat field site located above Davos (Switzerland), during one entire winter season (from December 2018 to June 2019). We identified three snowfall events with a substantial response of dV/V measurements (drops of several percent between 15 and 25 Hz), suggesting a detectable change in elastic properties of the medium due to the additional fresh snow. To better interpret the measurements, we used a physical model to compute frequency-dependent changes in the Rayleigh wave velocity computed before and after the events. Elastic parameters of the ground subsurface were obtained from a seismic refraction survey, whereas snow cover properties were obtained from the snow cover model SNOWPACK. The decrease in dV/V due to a snowfall was well reproduced, with the same order of magnitude as observed values, confirming the importance of the effect of fresh and dry snow on seismic measurements. We also observed a decrease in dV/V with snowmelt periods, but we were not able to reproduce those changes with our model. Overall, our results highlight the effect of the snow cover on seismic measurements, but more work is needed to accurately model this response, in particular for the presence of liquid water in the snowpack.

Sensitivity of modeled snow stability data to meteorological input uncertainty

Abstract. To perform spatial snow cover simulations for numerical avalanche forecasting, interpolation and downscaling of meteorological data are required, which introduce uncertainties. The repercussions of these uncertainties on modeled snow stability remain mostly unknown. We therefore assessed the contribution of meteorological input uncertainty to modeled snow stability by performing a global sensitivity analysis. We used the numerical snow cover model SNOWPACK to simulate two snow instability metrics, i.e., the skier stability index and the critical crack length, for a field site equipped with an automatic weather station providing the necessary input for the model. Simulations were performed for a winter season, which was marked by a prolonged dry period at the beginning of the season. During this period, the snow surface layers transformed into layers of faceted and depth hoar crystals, which were subsequently buried by snow. The early-season snow surface was likely the weak layer of many avalanches later in the season. Three different scenarios were investigated to better assess the influence of meteorological forcing on snow stability during (a) the weak layer formation period, (b) the slab formation period, and (c) the weak layer and slab formation period. For each scenario, 14 000 simulations were performed, by introducing quasi-random uncertainties to the meteorological input. Uncertainty ranges for meteorological forcing covered typical differences observed within a distance of 2 km or an elevation change of 200 m. Results showed that a weak layer formed in 99.7 % of the simulations, indicating that the weak layer formation was very robust due to the prolonged dry period. For scenario a, modeled grain size of the weak layer was mainly sensitive to precipitation, while the shear strength of the weak layer was sensitive to most input variables, especially air temperature. Once the weak layer existed (case b), precipitation was the most prominent driver for snow stability. The sensitivity analysis highlighted that for all scenarios, the two stability metrics were mostly sensitive to precipitation. Precipitation determined the load of the slab, which in turn influenced weak layer properties. For cases b and c, the two stability metrics showed contradicting behaviors. With increasing precipitation, i.e., deep snowpacks, the skier stability index decreased (became less stable). In contrast, the critical crack length increased with increasing precipitation (became more stable). With regard to spatial simulations of snow stability, the high sensitivity to precipitation suggests that accurate precipitation patterns are necessary to obtain realistic snow stability patterns.

Comparison of modeled snow properties in Afghanistan, Pakistan, and Tajikistan

Abstract. Ice and snowmelt feed the Indus River and Amu Darya in western High Mountain Asia, yet there are limited in situ measurements of these resources. Previous work in the region has shown promise using snow water equivalent (SWE) reconstruction, which requires no in situ measurements, but validation has been a problem. However, recently we were provided with daily manual snow depth measurements from Afghanistan, Tajikistan, and Pakistan by the Aga Khan Agency for Habitat (AKAH). To validate SWE reconstruction, at each station, accumulated precipitation and SWE were derived from snow depth using the numerical snow cover model SNOWPACK. High-resolution (500 m) reconstructed SWE estimates from the Parallel Energy Balance Model (ParBal) were then compared to the modeled SWE at the stations. The Alpine3D model was then used to create spatial estimates at 25 km resolution to compare with estimates from other snow models. Additionally, the coupled SNOWPACK and Alpine3D system has the advantage of simulating snow profiles, which provides stability information. The median number of critical layers and percentage of faceted layers across all of the pixels containing the AKAH stations were computed. For SWE at the point scale, the reconstructed estimates showed a bias of −42 mm (−19 %) at peak SWE. For the coarser spatial SWE estimates, the various models showed a wide range, with reconstruction being on the lower end. A heavily faceted snowpack was observed in both years, but 2018, a dry year, according to most of the models, showed more critical layers that persisted for a longer period.

Validating modeled critical crack length for crack propagation in the snow cover model SNOWPACK

Abstract. Observed snow stratigraphy and snow stability are of key importance for avalanche forecasting. Such observations are rare and snow cover models can improve the spatial and temporal resolution. To evaluate snow stability, failure initiation and crack propagation have to be considered. Recently, a new stability criterion relating to crack propagation, namely the critical crack length, was implemented into the snow cover model SNOWPACK. The critical crack length can also be measured in the field with a propagation saw test, which allows for an unambiguous comparison. To validate and improve the parameterization for the critical crack length, we used data from 3 years of field experiments performed close to two automatic weather stations above Davos, Switzerland. We monitored seven distinct weak layers and performed in total 157 propagation saw tests on a weekly basis. Comparing modeled to measured critical crack length showed some discrepancies stemming from model assumption. Hence, we replaced two variables of the original parameterization, namely the weak layer shear modulus and thickness, with a fit factor depending on weak layer density and grain size. With these adjustments, the normalized root-mean-square error between modeled and observed critical crack lengths decreased from 1.80 to 0.28. As the improved parameterization accounts for grain size, values of critical crack lengths for snow layers consisting of small grains, which in general are not weak layers, become larger. In turn, critical weak layers appear more prominently in the vertical profile of critical crack length simulated with SNOWPACK. Hence, minimal values in modeled critical crack length better match observed weak layers. The improved parameterization of critical crack length may be useful for both weak layer detection in simulated snow stratigraphy and also providing more realistic snow stability information – and hence may improve avalanche forecasting.

Cold-to-warm flow regime transition in snow avalanches

Abstract. Large avalanches usually encounter different snow conditions along their track. When they release as slab avalanches comprising cold snow, they can subsequently develop into powder snow avalanches entraining snow as they move down the mountain. Typically, this entrained snow will be cold (T‾<-1 ∘C) at high elevations near the surface, but warm (T‾>-1 ∘C) at lower elevations or deeper in the snowpack. The intake of warm snow is believed to be of major importance to increase the temperature of the snow composition in the avalanche and eventually cause a flow regime transition. Measurements of flow regime transitions are performed at the Vallée de la Sionne avalanche test site in Switzerland using two different radar systems. The data are then combined with snow temperatures calculated with the snow cover model SNOWPACK. We define transitions as complete when the deposit at runout is characterized only by warm snow or as partial if there is a warm flow regime, but the farthest deposit is characterized by cold snow. We introduce a transition index Ft, based on the runout of cold and warm flow regimes, as a measure to quantify the transition type. Finally, we parameterize the snow cover temperature along the avalanche track by the altitude Hs, which represents the point where the average temperature of the uppermost 0.5 m changes from cold to warm. We find that Ft is related to the snow cover properties, i.e. approximately proportional to Hs. Thus, the flow regime in the runout area and the type of transition can be predicted by knowing the snow cover temperature distribution. We find that, if Hs is more than 500 m above the valley floor for the path geometry of Vallée de la Sionne, entrainment of warm surface snow leads to a complete flow regime transition and the runout area is reached by only warm flow regimes. Such knowledge is of great importance since the impact pressure and the effectiveness of protection measures are greatly dependent on the flow regime.

Spatio‐temporal aspects of snowpack runoff formation during rain on snow

AbstractRain on snow (ROS) is a complex phenomenon leading to repeated flooding in many regions with a seasonal snow cover. The potential to generate floods during ROS depends not only on the magnitude of rainfall but also on the areal extent of the antecedent snow cover and the spatio‐temporal interaction between meteorologic and snowpack properties. The complex interaction of these factors makes it difficult to accurately predict the effect of snow cover on runoff formation for an upcoming ROS event. In this study, the detailed physics‐based snow cover model SNOWPACK was used to assess the influence of snow cover properties on converting rain input to available snowpack runoff during 191 ROS events for 58 catchments in the Swiss Alps. Conditions identified by the simulations that led to excessive snowpack runoff were a large snow‐covered fraction, spatially homogeneous snowpack properties, prolonged rainfall events, and a strong rise in air temperature over the course of the event. These factors entail a higher probability of snowpack runoff occurring synchronously within the catchment, which in turn favours higher overall runoff rates. The findings suggest that during autumn and late spring, flooding due to ROS is more likely to happen, whereas during winter a coincidence of the above conditions in the study area is quite rare. For example, an autumn event which occurred in October 2011 resulted from a combination of spatially homogeneous snowpack conditions following a recent snowfall and high, but not exceptional rainfall, and led to major flooding. The results of this study provide key factors to assess in advance of an incoming ROS event and emphasize the importance of detailed snow monitoring for flood forecasting in snow‐affected watersheds.

Snow farming: conserving snow over the summer season

Abstract. Summer storage of snow for tourism has seen an increasing interest in the last years. Covering large snow piles with materials such as sawdust enables more than two-thirds of the initial snow volume to be conserved. We present detailed mass balance measurements of two sawdust-covered snow piles obtained by terrestrial laser scanning during summer 2015. Results indicate that 74 and 63 % of the snow volume remained over the summer for piles in Davos, Switzerland and Martell, Italy. If snow mass is considered instead of volume, the values increase to 83 and 72 %. The difference is attributed to settling and densification of the snow. Additionally, we adapted the one-dimensional, physically based snow cover model SNOWPACK to perform simulations of the sawdust-covered snow piles. Model results and measurements agreed extremely well at the point scale. Moreover, we analysed the contribution of the different terms of the surface energy balance to snow ablation for a pile covered with a 40 cm thick sawdust layer and a pile without insulation. Short-wave radiation was the dominant source of energy for both scenarios, but the moist sawdust caused strong cooling by long-wave emission and negative sensible and latent heat fluxes. This cooling effect reduces the energy available for melt by up to a factor of 12. As a result only 9 % of the net short-wave energy remained available for melt. Finally, sensitivity studies of the parameters thickness of the sawdust layer, air temperature, precipitation and wind speed were performed. We show that sawdust thickness has a tremendous effect on snow loss. Higher air temperatures and wind speeds increase snow ablation but less significantly. No significant effect of additional precipitation could be found as the sawdust remained wet during the entire summer with the measured quantity of rain. Setting precipitation amounts to zero, however, strongly increased melt. Overall, the 40 cm sawdust provides sufficient protection for mid-elevation (approx. 1500 m a.s.l.) Alpine climates and can be managed with reasonable effort.

On forecasting wet-snow avalanche activity using simulated snow cover data

Wet-snow avalanches are relatively poorly understood and difficult to forecast. By definition, water is required in the snow cover, thus assessing the liquid water content of the snow cover is of paramount importance for wet-snow avalanche forecasting. While evaluating wet-snow instability through field measurements is difficult, physically based snow cover models can be used to estimate the amount of liquid water within the snow cover using meteorological input. Recently, an index based on the liquid water content of the snow cover was suggested showing high potential to predict the onset of wet-snow avalanche activity. However, as the snow cover model was forced with data from automated weather stations (AWS) only a now-cast was possible. As snow cover conditions quickly change during snow melt, a forecast would be useful. For this study, we therefore force the 1-D physically based snow cover model SNOWPACK with data from the high-resolution numerical weather prediction model COSMO and investigate whether forecasting regional patterns of the onset of wet-snow avalanche activity is feasible. To validate the index, we compared simulations performed at the location of numerous AWS in the Swiss Alps with wet-snow avalanche observations from the corresponding region. Only by forcing SNOWPACK with data from automated weather stations up to the actual day and then adding the forecasted input data to produce a forecast led to results comparable to the simulations with station data only. While using this setup, the index was able to predict the onset of wet-snow avalanching with a probability of detection of >80% for three winters between 2013 and 2016 and for two different climate regions in Switzerland. However, the false alarm ratio was high (up to 80%), suggesting that further refinements of the classification method are needed.

Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment

Abstract. The assessment of flood risks in alpine, snow-covered catchments requires an understanding of the linkage between the snow cover, soil and discharge in the stream network. Here, we apply the comprehensive, distributed model Alpine3D to investigate the role of soil moisture in the predisposition of the Dischma catchment in Switzerland to high flows from rainfall and snowmelt. The recently updated soil module of the physics-based multilayer snow cover model SNOWPACK, which solves the surface energy and mass balance in Alpine3D, is verified against soil moisture measurements at seven sites and various depths inside and in close proximity to the Dischma catchment. Measurements and simulations in such terrain are difficult and consequently, soil moisture was simulated with varying degrees of success. Differences between simulated and measured soil moisture mainly arise from an overestimation of soil freezing and an absence of a groundwater description in the Alpine3D model. Both were found to have an influence in the soil moisture measurements. Using the Alpine3D simulation as the surface scheme for a spatially explicit hydrologic response model using a travel time distribution approach for interflow and baseflow, streamflow simulations were performed for the discharge from the catchment. The streamflow simulations provided a closer agreement with observed streamflow when driving the hydrologic response model with soil water fluxes at 30 cm depth in the Alpine3D model. Performance decreased when using the 2 cm soil water flux, thereby mostly ignoring soil processes. This illustrates that the role of soil moisture is important to take into account when understanding the relationship between both snowpack runoff and rainfall and catchment discharge in high alpine terrain. However, using the soil water flux at 60 cm depth to drive the hydrologic response model also decreased its performance, indicating that an optimal soil depth to include in surface simulations exists and that the runoff dynamics are controlled by only a shallow soil layer. Runoff coefficients (i.e. ratio of rainfall over discharge) based on measurements for high rainfall and snowmelt events were found to be dependent on the simulated initial soil moisture state at the onset of an event, further illustrating the important role of soil moisture for the hydrological processes in the catchment. The runoff coefficients using simulated discharge were found to reproduce this dependency, which shows that the Alpine3D model framework can be successfully applied to assess the predisposition of the catchment to flood risks from both snowmelt and rainfall events.

Snow fracture in relation to slab avalanche release: critical state for the onset of crack propagation

Abstract. The failure of a weak snow layer buried below cohesive slab layers is a necessary, but insufficient, condition for the release of a dry-snow slab avalanche. The size of the crack in the weak layer must also exceed a critical length to propagate across a slope. In contrast to pioneering shear-based approaches, recent developments account for weak layer collapse and allow for better explaining typical observations of remote triggering from low-angle terrain. However, these new models predict a critical length for crack propagation that is almost independent of slope angle, a rather surprising and counterintuitive result. Based on discrete element simulations we propose a new analytical expression for the critical crack length. This new model reconciles past approaches by considering for the first time the complex interplay between slab elasticity and the mechanical behavior of the weak layer including its structural collapse. The crack begins to propagate when the stress induced by slab loading and deformation at the crack tip exceeds the limit given by the failure envelope of the weak layer. The model can reproduce crack propagation on low-angle terrain and the decrease in critical length with increasing slope angle as modeled in numerical experiments. The good agreement of our new model with extensive field data and the ease of implementation in the snow cover model SNOWPACK opens a promising prospect for improving avalanche forecasting.

Simulating ice layer formation under the presence of preferential flow in layered snowpacks

Abstract. For physics-based snow cover models, simulating the formation of dense ice layers inside the snowpack has been a long-time challenge. Their formation is considered to be tightly coupled to the presence of preferential flow, which is assumed to happen through flow fingering. Recent laboratory experiments and modelling techniques of liquid water flow in snow have advanced the understanding of conditions under which preferential flow paths or flow fingers form. We propose a modelling approach in the one-dimensional, multilayer snow cover model SNOWPACK for preferential flow that is based on a dual domain approach. The pore space is divided into a part that represents matrix flow and a part that represents preferential flow. Richards' equation is then solved for both domains and only water in matrix flow is subjected to phase changes. We found that preferential flow paths arriving at a layer transition in the snowpack may lead to ponding conditions, which we used to trigger a water flow from the preferential flow domain to the matrix domain. Subsequent refreezing then can form dense layers in the snowpack that regularly exceed 700 kg m−3. A comparison of simulated density profiles with biweekly snow profiles made at the Weissfluhjoch measurement site at 2536 m altitude in the Eastern Swiss Alps for 16 snow seasons showed that several ice layers that were observed in the field could be reproduced. However, many profiles remain challenging to simulate. The prediction of the early snowpack runoff also improved under the consideration of preferential flow. Our study suggests that a dual domain approach is able to describe the net effect of preferential flow on ice layer formation and liquid water flow in snow in one-dimensional, detailed, physics-based snowpack models, without the need for a full multidimensional model.

Observations of capillary barriers and preferential flow in layered snow during cold laboratory experiments

Abstract. Data of liquid water flow around a capillary barrier in snow are still limited. To gain insight into this process, we carried out observations of dyed water infiltration in layered snow at 0 °C during cold laboratory experiments. We considered three different finer-over-coarser textures and three different water input rates. By means of visual inspection, horizontal sectioning, and measurements of liquid water content (LWC), capillary barriers and associated preferential flow were characterized. The flow dynamics of each sample were also simulated solving the Richards equation within the 1-D multi-layer physically based snow cover model SNOWPACK. Results revealed that capillary barriers and preferential flow are relevant processes ruling the speed of water infiltration in stratified snow. Both are marked by a high degree of spatial variability at centimeter scale and complex 3-D patterns. During unsteady percolation of water, observed peaks in bulk volumetric LWC at the interface reached ∼ 33–36 vol % when the upper layer was composed by fine snow (grain size smaller than 0.5 mm). However, LWC might locally be greater due to the observed heterogeneity in the process. Spatial variability in water transmission increases with grain size, whereas we did not observe a systematic dependency on water input rate for samples containing fine snow. The comparison between observed and simulated LWC profiles revealed that the implementation of the Richards equation reproduces the existence of a capillary barrier for all observed cases and yields a good agreement with observed peaks in LWC at the interface between layers.

Modelling hazardous surface hoar layers across western Canada with a coupled weather and snow cover model

Destructive snow avalanches in western Canada are often caused by failure in buried surface hoar layers. Numerical snow cover models can simulate the formation and evolution of these layers, which could help avalanche forecasters assess the location and timing of avalanches. To investigate this application, we compared modelled surface hoar layers with snow and avalanche observations from the Coast, Columbia, and Rocky Mountains of western Canada. Surface hoar formation and evolution was modelled by forcing the snow cover model SNOWPACK with data from a high-resolution numerical weather prediction model. Surface hoar formation was verified with daily snow surface observations at 88 observation sites over two winters, and the evolution of buried layers was verified with avalanche observations and persistent weak layer assessments from 67 avalanche forecast regions. The frequency of surface hoar formation was over-predicted by 40%, although since modelled crystal sizes were moderately correlated with observed sizes, the more hazardous layers were often distinguished. A structural stability index in SNOWPACK often identified surface hoar layers during storm slab avalanche activity, but identifying layers during persistent slab avalanche activity was more difficult. Model limitations included uncertain meteorological inputs, errors in SNOWPACK's snow surface energy balance, and representing the necessary spatial scales. Despite these limitations, the coupled model resolved differences between major Canadian mountain ranges and could improve avalanche forecasts in data-sparse regions.

Snow instability evaluation: calculating the skier-induced stress in a multi-layered snowpack

Abstract. The process of dry-snow slab avalanche formation can be divided into two phases: failure initiation and crack propagation. Several approaches tried to quantify slab avalanche release probability in terms of failure initiation based on shear stress and strength. Though it is known that both the properties of the weak layer and the slab play a major role in avalanche release, most previous approaches only considered slab properties in terms of slab depth, average density and skier penetration. For example, for the skier stability index, the additional stress (e.g. due to a skier) at the depth of the weak layer is calculated by assuming that the snow cover can be considered a semi-infinite, elastic, half-space. We suggest a new approach based on a simplification of the multi-layered elasticity theory in order to easily compute the additional stress due to a skier at the depth of the weak layer, taking into account the layering of the snow slab and the substratum. We first tested the proposed approach on simplified snow profiles, then on manually observed snow profiles including a stability test and, finally, on simulated snow profiles. Our simple approach reproduced the additional stress obtained by finite element simulations for the simplified profiles well – except that the sequence of layering in the slab cannot be replicated. Once implemented into the classical skier stability index and applied to manually observed snow profiles classified into different stability classes, the classification accuracy improved with the new approach. Finally, we implemented the refined skier stability index into the 1–D snow cover model SNOWPACK. The two study cases presented in this paper showed promising results even though further verification is still needed. In the future, we intend to implement the proposed approach for describing skier-induced stress within a multi-layered snowpack into more complex models which take into account not only failure initiation but also crack propagation.

Seasonal and diurnal cycles of liquid water in snow—Measurements and modeling

AbstractEvaluating and improving snow models and outflow predictions for hydrological applications is hindered by the lack of continuous data on bulk volumetric liquid water content (θw) and storage capacity of the melting snowpack. The combination of upward looking ground‐penetrating radar and conventional snow height sensors enable continuous, nondestructive determinations of θw in natural snow covers from first surficial wetting until shortly before melt out. We analyze diurnal and seasonal cycles of θw for 4 years in a flat study site and for three melt seasons on slopes and evaluate model simulations for two different water transport schemes in the snow cover model SNOWPACK. Observed maximum increases in θw during a day are below 1.7 vol % (90th percentile) at the flat site. Concerning seasonal characteristics of θw, less than 10% of recorded data exceed 5 vol % at the flat site and 3.5 vol % at slopes. Both water transport schemes in SNOWPACK underestimate maximum θw at the flat site systematically for all observed melt seasons, while simulated θw maxima on slopes are accurate. Implementing observed changes in θw per day in outflow predictions increases model performance toward higher agreement with lysimeter measurements. Hence, continuously monitoring θw improves our understanding of liquid water percolation and retention in snow, which is highly relevant for several aspects of the cryosphere such as avalanche formation, catchment hydrology, and ice sheet mass balances.

Meteorological, elevation, and slope effects on surface hoar formation

Abstract. Failure in layers of buried surface hoar crystals (frost) can cause hazardous snow slab avalanches. Surface hoar crystals form on the snow surface and are sensitive to micro-meteorological conditions. In this study, the role of meteorological and terrain factors was investigated for three layers of surface hoar in the Columbia Mountains of Canada. The distribution of crystals over different elevations and aspects was observed on 20 days of field observations during a period of high pressure. The same layers were modelled over simplified terrain on a 2.5 km horizontal grid by forcing the snow cover model SNOWPACK with forecast weather data from a numerical weather prediction model. Modelled surface hoar growth was associated with warm air temperatures, high humidity, cold surface temperatures, and low wind speeds. Surface hoar was most developed in regions and elevation bands where these conditions existed, although strong winds at high elevations caused some model discrepancies. SNOWPACK simulations on virtual slopes systematically predicted smaller surface hoar on south-facing slopes. In the field, a complex combination of surface hoar and sun crusts were observed, suggesting the simplified model did not adequately resolve the surface energy balance on slopes. Overall, a coupled weather–snow cover model could benefit avalanche forecasters by predicting surface hoar layers on a regional scale over different elevation bands.

Evaluation of a snow avalanche possibly triggered by a local earthquake at Vallée de la Sionne, Switzerland

Snow avalanches are moving sources of infrasonic and seismic energy. They can be triggered by many different mechanisms that include the shaking produced by earthquakes. The forces induced by an earthquake can cause an increase in the load down the slope and can also decrease the shear strength and both effects can cause the release of an avalanche. This phenomenon represents an important hazard associated with earthquakes in snow-covered mountain areas with high seismicity.On 6 December 2010 a snow avalanche was released at the experimental site of Vallée de la Sionne (VDLS) in Switzerland seconds after a local earthquake of magnitude ML 3.1 with the hypocenter in France, approximately 43km from the avalanche starting zone. The seismic and infrasound signals generated by the earthquake and the snow avalanche were recorded by an array of sensors installed at VDLS. This paper analyses these data and shows that the avalanche was possibly triggered by the earthquake. This analysis also allows us to determine the characteristics of the avalanche (type and path). The infrasound data shows that the time of the avalanche release coincided with the arrival of the seismic waves of the earthquake. We calculate the values of the ground vibration parameters (PGD, PGV, PGA, PSA, Ia and TD) measured at the release area of the avalanche and compare them with those of two other earthquakes that did not trigger an avalanche. To evaluate the influence of the snowpack stratigraphy with the effectiveness of the earthquakes to trigger an avalanche, we simulate the snow cover using the one-dimensional snow cover model SNOWPACK. The weather and snow cover conditions of the days on which these events occurred are compared and used to evaluate the snowpack stability and the consequent likelihood of avalanche activity. The snowpack stability is the primary factor that determines whether an avalanche may be triggered by minor earthquakes. We conclude that when the snowpack is only marginally stable then the displacement caused by even a small earthquake could be enough to trigger an avalanche. Furthermore, the analysis of the other two, even stronger, earthquakes shows that in stable conditions no avalanche was triggered.