Snow Cover Model Research Articles

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.

The measurements of snow cover volume in the area of Szrenicki Cirque

The purpose of this project is to determine a fast way of calculating the volume and distribution of snow mantle, which is located in wide terrain concavities in mountain areas. Our study area was so-called Szrenicki Cirque (Kocioł Szrenicki), which is the nival recess, located in Karkonosze Mountains, Poland. We analyzed modern technologies, that are designed to generate 3D-models: terrain laser scanning and close-range photogrammetry (including structure-from-motion technique). There were two major reasons for our research. First, analyzing if a structure-frommotion based software is capable of creating a 3D model of snow cover since potential tie points for adjoin pictures are scarce. The second was to establish the quality and accuracy of this model in relation to potentially more accurate terrestrial laser scanning results. An important issue was also is to estimate the fastest, simplest and least expensive methodology that can be implemented as a daily task of Karkonosze National Park workers. A proper, fast, safe and accurate method of calculating the snow cover volume would incise the safety and avalanche risk evaluation in the vicinity of Karkonosze Mountains. In addition, the developed method can be used to monitor the risk of local spring floods.

Wind tunnel experiments: saltation is necessary for wind-packing

ABSTRACTWind-packed snow in the form of slabs or crusts is an important part of alpine and polar snow covers. Yet, the formation process of such layers is poorly understood. For example, it remains unclear whether drifting snow is necessary for wind-packing or not. A better understanding of wind-packing could improve snow-cover models and avalanche danger forecasts and contribute to the assessment of mass balances in polar regions. We designed a closed-circuit, obround wind tunnel to study the process of wind crust formation. A SnowMicroPen was used to measure how the hardness of the snow evolved. The results show that no crust forms without saltation. Drifting snow is a necessary but not sufficient condition for wind-packing. The dynamics of erosion and deposition appear to be equally important.

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.

Distributed snow and rock temperature modelling in steep rock walls using Alpine3D

Abstract. In this study we modelled the influence of the spatially and temporally heterogeneous snow cover on the surface energy balance and thus on rock temperatures in two rugged, steep rock walls on the Gemsstock ridge in the central Swiss Alps. The heterogeneous snow depth distribution in the rock walls was introduced to the distributed, process-based energy balance model Alpine3D with a precipitation scaling method based on snow depth data measured by terrestrial laser scanning. The influence of the snow cover on rock temperatures was investigated by comparing a snow-covered model scenario (precipitation input provided by precipitation scaling) with a snow-free (zero precipitation input) one. Model uncertainties are discussed and evaluated at both the point and spatial scales against 22 near-surface rock temperature measurements and high-resolution snow depth data from winter terrestrial laser scans.In the rough rock walls, the heterogeneously distributed snow cover was moderately well reproduced by Alpine3D with mean absolute errors ranging between 0.31 and 0.81 m. However, snow cover duration was reproduced well and, consequently, near-surface rock temperatures were modelled convincingly. Uncertainties in rock temperature modelling were found to be around 1.6 °C. Errors in snow cover modelling and hence in rock temperature simulations are explained by inadequate snow settlement due to linear precipitation scaling, missing lateral heat fluxes in the rock, and by errors caused by interpolation of shortwave radiation, wind and air temperature into the rock walls.Mean annual near-surface rock temperature increases were both measured and modelled in the steep rock walls as a consequence of a thick, long-lasting snow cover. Rock temperatures were 1.3–2.5 °C higher in the shaded and sunny rock walls, while comparing snow-covered to snow-free simulations. This helps to assess the potential error made in ground temperature modelling when neglecting snow in steep bedrock.

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.

Use of machine learning techniques for modeling of snow depth

Snow exerts significant regulating effect on the land hydrological cycle since it controls intensity of heat and water exchange between the soil-vegetative cover and the atmosphere. Estimating of a spring flood runoff or a rain-flood on mountainous rivers requires understanding of the snow cover dynamics on a watershed. In our work, solving a problem of the snow cover depth modeling is based on both available databases of hydro-meteorological observations and easily accessible scientific software that allows complete reproduction of investigation results and further development of this theme by scientific community. In this research we used the daily observational data on the snow cover and surface meteorological parameters, obtained at three stations situated in different geographical regions: Col de Porte (France), Sodankyla (Finland), and Snoquamie Pass (USA). Statistical modeling of the snow cover depth is based on a complex of freely distributed the present-day machine learning models: Decision Trees, Adaptive Boosting, Gradient Boosting. It is demonstrated that use of combination of modern machine learning methods with available meteorological data provides the good accuracy of the snow cover modeling. The best results of snow cover depth modeling for every investigated site were obtained by the ensemble method of gradient boosting above decision trees – this model reproduces well both, the periods of snow cover accumulation and its melting. The purposeful character of learning process for models of the gradient boosting type, their ensemble character, and use of combined redundancy of a test sample in learning procedure makes this type of models a good and sustainable research tool. The results obtained can be used for estimating the snow cover characteristics for river basins where hydro-meteorological information is absent or insufficient.

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.

Modelling wet snow avalanche runout to assess road safety at a high-altitude mine in the central Andes

Abstract. Mining activities in cold regions are vulnerable to snow avalanches. Unlike operational facilities, which can be constructed in secure locations outside the reach of avalanches, access roads are often susceptible to being cut, leading to mine closures and significant financial losses. In this paper we discuss the application of avalanche runout modelling to predict the operational risk to mining roads, a long-standing problem for mines in high-altitude, snowy regions. We study the 35 km long road located in the "Cajón del rio Blanco" valley in the central Andes, which is operated by the Codelco Andina copper mine. In winter and early spring, this road is threatened by over 100 avalanche paths. If the release and snow cover conditions can be accurately specified, we find that avalanche dynamics modelling is able to represent runout, and safe traffic zones can be identified. We apply a detailed, physics-based snow cover model to calculate snow temperature, density and moisture content in three-dimensional terrain. This information is used to determine the initial and boundary conditions of the avalanche dynamics model. Of particular importance is the assessment of the current snow conditions along the avalanche tracks, which define the mass and thermal energy entrainment rates and therefore the possibility of avalanche growth and long runout distances.

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.

Assessing wet snow avalanche activity using detailed physics based snowpack simulations

AbstractWater accumulating on microstructural transitions inside a snowpack is often considered a prerequisite for wet snow avalanches. Recent advances in numerical snowpack modeling allow for an explicit simulation of this process. We analyze detailed snowpack simulations driven by meteorological stations in three different climate regimes (Alps, Central Andes, and Pyrenees), with accompanying wet snow avalanche activity observations. Predicting wet snow avalanche activity based on whether modeled water accumulations inside the snowpack locally exceed 5–6% volumetric liquid water content is providing a higher prediction skill than using thresholds for daily mean air temperature, or the daily sum of the positive snow energy balance. Additionally, the depth of the maximum water accumulation in the simulations showed a significant correlation with observed avalanche size. Direct output from detailed snow cover models thereby is able to provide a better regional assessment of dangerous slope aspects and potential avalanche size than traditional methods.

Influence of Initial Snowpack Properties on Runoff Formation during Rain-on-Snow Events

Abstract Rain-on-snow (ROS) events have caused severe floods in mountainous areas in the recent past. Because of the complex interactions of physical processes, it is still difficult to accurately predict the effect of snow cover on runoff formation for an upcoming ROS event. In this study, a detailed physics-based energy balance snow cover model (SNOWPACK) was used to assess snow cover processes during more than 1000 historical ROS events at 116 locations in the Swiss Alps. The simulations of the mass and energy balance, liquid water flow, and the temporal evolution of structural properties of the snowpack were used to analyze runoff formation characteristics during ROS events. Initial liquid water content and snow depth at the onset of rainfall were found to influence the temporal dynamics, intensities, and cumulative amount of runoff. The meteorological forcing is modulated by processes within the snowpack, leading to an attenuation of runoff intensities for intense and short rain events and an amplifying effect for longer rain events. The timing of runoff generation relative to the rainfall seems to be strongly dependent on initial liquid water content, snow depth, and rainfall intensities. As these snowpack and meteorological conditions usually exhibit a strong seasonality, cumulative runoff generation during ROS also varies seasonally. ROS events with intensified snowpack runoff were found to be most common during late snowmelt season, with several such events also occurring in late autumn. These results demonstrate the strong influence of initial snowpack properties on runoff formation during ROS events in the Swiss Alps.

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.

Wet meadow ecosystems contribute the majority of overwinter soil respiration from snow‐scoured alpine tundra

AbstractWe measured soil respiration across a soil moisture gradient ranging from dry to wet snow‐scoured alpine tundra soils throughout three winters and two summers. In the absence of snow accumulation, soil moisture variability was principally determined by the combination of mesotopographical hydrological focusing and shallow subsurface permeability, which resulted in a patchwork of comingled ecosystem types along a single alpine ridge. To constrain the subsequent carbon cycling variability, we compared three measures of effective diffusivity and three methods to calculate gradient method soil respiration from four typical vegetation communities. Overwinter soil respiration was primarily restricted to wet meadow locations, and a conservative estimate of the rate of overwinter soil respiration from snow‐scoured wet meadow tundra was 69–90% of the maximum carbon dioxide (CO2) respired by seasonally snow‐covered soils within this same catchment. This was attributed to higher overwinter soil temperatures at wet meadow locations relative to fellfield, dry meadow, and moist meadow communities, which supported liquid water and heterotrophic respiration throughout the winter. These results were corroborated by eddy covariance‐based measurements that demonstrated an average of 272 g C m−2 overwinter carbon loss during the study period. As a result, we updated a conceptual model of soil respiration versus snow cover to express the potential for soil respiration variability from snow‐scoured alpine tundra.

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.

Snow instability patterns at the scale of a small basin

AbstractSpatial and temporal variations are inherent characteristics of the alpine snow cover. Spatial heterogeneity is supposed to control the avalanche release probability by either hindering extensive crack propagation or facilitating localized failure initiation. Though a link between spatial snow instability variations and meteorological forcing is anticipated, it has not been quantitatively shown yet. We recorded snow penetration resistance profiles with the snow micropenetrometer at an alpine field site during five field campaigns in Eastern Switzerland. For each of about 150 vertical profiles sampled per day a failure initiation criterion and the critical crack length were calculated. For both criteria we analyzed their spatial structure and predicted snow instability in the basin by external drift kriging. The regression models were based on terrain and snow depth data. Slope aspect was the most prominent driver, but significant covariates varied depending on the situation. Residual autocorrelation ranges were shorter than the ones of the terrain suggesting external influences possibly due to meteorological forcing. To explore the causes of the instability patterns we repeated the geostatistical analysis with snow cover model output as covariate data for one case. The observed variations of snow instability were related to variations in slab layer properties which were caused by preferential deposition of precipitation and differences in energy input at the snow surface during the formation period of the slab layers. Our results suggest that 3‐D snow cover modeling allows reproducing some of the snow property variations related to snow instability, but in future work all relevant micrometeorological spatial interactions should be considered.

Improved snow cover model in terrestrial ecosystem models over the Qinghai–Tibetan Plateau

Snow cover is an important land surface variable, especially in the Qinghai–Tibetan Plateau, and profoundly impacts plant phenology, growth, soil respiration and net ecosystem production. However, few studies have been conducted to examine the reliability of current snow cover models in the Qinghai–Tibetan Plateau. This study examined three snow cover models (SnowMAUS, revised SnowMAUS, and SnowFrostIce) across 23 meteorological stations covering a variety of altitudes. All three models substantially overestimated snow cover depth and numbers of days with snow cover because they ignored the impact of wind speed. Based on SnowMAUS, this study has incorporated equations dealing with wind speed impacts to develop a new model (SnowWind). Moreover, the parameter inversion method was improved by separating snow cover calculations into two processes (snow accumulation and melting) and estimating the parameters of the two processes separately. The results showed that SnowWind can estimate snow cover dynamics with reasonable precision of snow cover presence or absence and, to a large extent, snow cover depth. The better inversion method also improved the number of constrained parameters and model performance. Regional estimates of snow cover are comparable with those derived from satellite-based snow cover products with regard to snow cover days. This result shows the SnowWind model is an alternative approach that makes it possible to simulate sow cover and depth over large areas.

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.