Snow sublimation is a fundamental process that affects the snow crystal structure and is important for ice-core interpretation, remote sensing, snow hydrology and chemical processes in snow. Prior studies have shown that sublimation can change the isotopic content of the remaining snow; these studies have inferred sublimation rates using field data, and were unable to control many of the environmental parameters that determine sublimation rate (e.g. temperature, relative humidity, snow microstructure). We present sublimation rate measurements on snow samples in the laboratory, where we have controlled many of these parameters simultaneously. We use the same experimental apparatus to determine sublimation rate, investigate the isotopic effects of sublimation, and study the isotopic exchange between vapor and solid. Our results suggest that pore spaces in snow are almost always at saturation vapor pressure; undersaturation may be possible in large pore spaces or in regions of rapid interstitial airflow. We present a revised formulation for determining the mass-transfer coefficient for snow as a linear function of Reynolds number (hm = 0.566Re + 0.075), estimate the fractionation coefficient for sublimating snow, and provide evidence for isotopic exchange between vapor and solid.

Long-term data of winter air temperature and precipitation were analyzed and the correlation between them investigated in order to identify the factors influencing snow reduction during the recent warmer winters in the heavy-snowfall areas in Japan. A high negative correlation between winter precipitation and air temperature was identified in the heavy-snowfall areas on the Sea of Japan side in the center of the main island (Honshu). It was confirmed that precipitation is mainly caused by cold winter monsoons, and thus correlates to a large extent with air temperature in these areas. The precipitation decrease can be considered an effective factor for the recent reduction in snow as well as the snowfall to precipitation ratio. This should be taken into account for a better prediction of snow reduction in relation to global warming.

To consider the large-scale characteristics of blowing-snow sublimation and its importance in the hydrological cycle in the cryosphere, we investigated the sublimation of blowing snow particles on a global scale using the global datasets of the European Centre for Medium-RangeWeather Forecasts (ECMWF) re-analysis data and the International Satellite Land Surface Climatology Project (ISLSCP) Initiative I data for 1987. The sublimation fluxes of blowing snow particles were estimated globally with 2.5˚ resolution at 6 hour intervals. We found that the sublimation of blowing snow particles occurs more widely in the Northern Hemisphere than in the Southern Hemisphere, does not increase monotonously with latitude, and becomes more active in the polar coast regions and highlands, although the annual mean sublimation fluxes of the Northern and Southern Hemispheres are almost equal. In addition, we confirmed the characteristic seasonal changes in the area of sublimation in the Northern Hemisphere. Although we need to incorporate continuous parameters from systematic ground-based studies of the structure of blowing snow in specific fields to reduce uncertainty regarding the characteristics of blowing snow, our results point to a need to review the current understanding of the hydrological cycle.

A simple physical model describing the temperature-gradient metamorphism of snow is presented. This model, based on Kelvin’s equation and Fick’s law, takes into account the local variation of the saturating vapour pressure with temperature. It can determine locally whether the ice is condensing or subliming, depending on both the pressure and temperature fields in the snow structure. This model can also explain the formation of facets that occurs during the metamorphism. Using X-ray microtomographic images of snow samples obtained under low to moderate temperature-gradient conditions, this model has been tested and compared to the reaction-limited model proposed in a previous work.

A distributed mass-balance modeling approach is required to assess the impact of future climate scenarios on water availability in glaciated basins. Accurate estimation of water stored within the snow, firn and ice of such basins requires knowledge of the distributed snow and ice mass balance throughout the year. In this study, we estimate the annual mass balance and runoff for Haut Glacier d′Arolla, Switzerland, from 2000 to 2006. Our estimations are based on observed elevation changes from three digital elevation models (DEMs) derived from aerial photographs in September 1999 and 2005, and October 2006. In addition to these estimations, we implement a combined field observation and a distributed mass-balance modeling approach. An energy-balance model driven by meteorological variables from automatic weather stations inside the catchment area, including gravitational snow transport, is run for the period 2005–06. The model results are validated with direct snow water equivalent measurements as well as with runoff measurements. Combining the mass-balance measurements, energy-balance calculations and measured runoff, we estimate the contribution from ice melt to the runoff for this period to be 25–30%, the contribution from snowmelt 50–60% and the contribution from rain 15–25%. Our model results also show that the snow distribution affects both snow and ice melt. It is therefore important for water resources management to understand the distribution of snow in alpine catchments, as it seems to be the controlling factor for the timing of streamflow throughout the year as well as for the total availability of water.

The numerical solution to a time-dependent two-dimensional problem of an avalanche impact against a wall is presented. The height of the wall is much larger than the flow depth. Compressibility of the moving snow as well as the effect of gravity is taken into account. Calculations are made for an impact of low-density avalanches with densities <100 kgm–3 obeying the equation of state for a mixture of two gases (air and gas of ice/snow particles). The pressure, density and velocity distributions in the flow as functions of time and space coordinates are calculated, as well as the variation of the flow depth. In particular, the flow height at the wall, the pressure at the wall and the pressure distribution on the slope near the wall are given, demonstrating peaks and falls due to compression shocks and rarefaction waves.

A snowmelt model is used for the weekly forecast of daily discharges in the Kaunas reservoir, Lithuania. The results are used to feed a risk-based decision-making model developed by the first author for dam operation during floods. Physically based calibration of a degree-day model is carried out and coupled with flow routing using Nash’s instantaneous unit hydrograph theory. Temperature forecast is used as the driving variable. Due to the relative smoothness of snowmelt over time and the considerable basin size, the model provides acceptable results. Kalman filtering is then used to merge the estimates from the snowmelt model with those from an Arima flow model, resulting in better forecasting than that using each method alone. Uncertainty analysis of the snowmelt-model results is then carried out, showing considerable influence of the main parameter degree-day and of soil moisture conditions. Therefore these must be accurately estimated for forecasting purposes during flood events.

The three-parameter hydraulic model of snow avalanche dynamics including the coefficients of dry and turbulent friction and the coefficient of new-snow-mass entrainment was investigated. The ‘Domestic’ avalanche site in Elbrus region, Caucasus, Russia, was chosen as the model avalanche range. According to the model, the fixed avalanche run-out can be achieved with various combinations of model parameters. At the fixed value of the coefficient of entrainment me , we have a curve on a plane of the coefficients of dry and turbulent friction. It was found that the family of curves ( me is a parameter) are crossed at the single point. The value of the coefficient of turbulent friction at the cross-point remained practically constant for the maximum and average avalanche run-outs. The conclusions obtained are confirmed by the results of modelling for six arbitrarily chosen avalanche sites: three in the Khibiny mountains, Kola Peninsula, Russia, two in the Elbrus region and one idealized site with an exponential longitudinal profile. The dependences of run-out on the coefficient of dry friction are constructed for all the investigated avalanche sites. The results are important for the statistical simulation of avalanche dynamics since they suggest the possibility of using only one random model parameter, namely, the coefficient of dry friction, in the model. The histograms and distribution functions of the coefficient of dry friction are constructed and presented for avalanche sites Nos 22 and 43 (Khibiny mountains) and ‘Domestic’, with the available series of field data.

This paper presents a sequential evaluation of snow microstructure and its associated thermal conductivity under the influence of a temperature gradient. Temperature gradients from 28 to 45 Km–1 were applied to snow samples having a density range 180–320 kgm–3. The experiments were conducted inside a cold room in a specially designed heat-flux apparatus for a period of 4weeks. A constant heat flux was applied at the base of the heat-flux apparatus to produce a temperature gradient in the snow sample. A steady-state approach was used to estimate the effective thermal conductivity of snow. Horizontal and vertical thick sections were prepared on a weekly basis to obtain snow micrographs. These micrographs were used to obtain snow microstructure using stereological tools. The thermal conductivity was found to increase with increase in grain size, bond size and grain and pore intercept lengths, suggesting a possible correlation of thermal conductivity with snow microstructure. Thermal conductivity increased even though surface area and area fraction of ice were found to decrease. The outcome suggests that changes in snow microstructure have significant control on thermal conductivity even at a constant density.

Since 1996, a dense network of Alpine automatic weather and snow-measurement (Interkantonales Mess- und Informationssystem (IMIS)) stations has been in operational use for local and regional avalanche warning. The measurements of the IMIS stations are assumed to be representative for spatially extended regions around the measuring sites for applications in avalanche risk management. In this study, the regional representativeness of these stations with regard to the daily amount of new snow is investigated. The results show that the amount of daily new snow is spatially correlated in a range of ∼5–55 km. Regarding simultaneous observations of daily new snow measurements, which are ∼5–10 km apart, the probability of detection (POD) is given as 0.5±0.03. In this paper, the POD of an automatic warning network is introduced as an indicator of the representativeness of point measurement information for avalanche warning applications. The results of this study may mark a reference value for verification of spatially distributed Alpine meteorological models which evaluate the amount of daily new snow in the Swiss Alps.

Especially for animals inhabiting alpine areas, winter environmental conditions can be limiting. Cold temperatures, hampered food availability and natural perils are just three of many potential threats that mountain ungulates face in winter. Understanding their sensitivity to climate variability is essential for game management. Here we focus on analyzing the influence of snow and weather conditions on the mortality pattern of Alpine chamois. Our mortality data are derived from a systematic assessment of 6500 chamois that died of natural causes over the course of 13 years. We use population- and habitat-specific data on snow, climate and avalanche danger to identify the key environmental factors that essentially determine the spatio-temporal variations in chamois mortality. Initially, we show that most fatalities occurred in winter, with a peak around March, when typically snow depths were highest. Death causes related to poor general conditions were the major component of seasonal variations. As for the interannual variations in mortality, snow depth and avalanche risk best explained the occurrence of winters with increased numbers of fatalities. Finally, analyzing differences in mortality rates between populations, we identified sun-exposed winter habitats with little snow accumulation as favourable for alpine chamois.

The currently adopted approach for avalanche-hazard mapping in Switzerland includes avalanche-dynamics modelling coupled with estimation of the greatest annual 3 day snowfall depth, H72, for high-return periods, used as the release depth. New advances in avalanche dynamics show that this approach can be improved using models with mass entrainment, requiring in turn a statistical definition of the erodible snow cover. We propose a regional approach, based on index value, to evaluate release depth and erodible snow cover for large-return periods. The territory of Switzerland is divided into seven climatologically homogeneous regions. Generalized extreme value (GEV) distributions for the growth factors coupled with index-value estimation based on altitude provide an accurate estimate of snow depths, also for large-return periods. RAMMS, a two-dimensional avalanche-dynamics model including snow entrainment, is used for hazard mapping for a site used as an example of the Swiss procedure. The regional approach allows the boundary conditions for hazard mapping to be set using an entrainment model, and also provides statistical uncertainty of the design release and erosion depth, thus aiding in applying uncertainty analysis to hazard-mapping procedure.

A physical model for the snow/firn densification process (Salamatin and others, 2006) and Martinerie and others’ (1992, 1994) correlation for the firn density at the pore closure are employed to perform a scale analysis and computational experiments in order to deduce simplified relations for the close-off depth and ice age in quasi-stationary ice formation conditions. The critical snow density at which ice-grain rearrangement stops is used to take into account variability of snow structures subjected to densification. The results obtained are validated on a representative set of ice-core data from 22 sites which covers wide ranges of present-day temperatures and ice accumulation rates. A simple analytical approximation for the density–depth profile is proposed.

The influence of a dam on granular avalanches was investigated. Small-scale laboratory experiments were designed to study the effectiveness of dams built to protect against large-scale dense snow avalanches. These experiments consisted of releasing a granular mass that first flowed down an inclined channel, then hit and overflowed a dam spanning the channel exit and finally spread out on an inclined unconfined run-out zone. First, we measured the volume retained upstream of the obstacle and the overrun length downstream of the obstacle. In the avalanche regime studied here, no simple relation was found between the volume retained and the run-out shortening resulting from the obstacle. The results highlighted that the avalanche run-out was also shortened by complex local energy dissipation. Second, we report the study of the granular deposit propagating upstream of the dam. We show that there was a change in behaviour from an overflow-type regime for low dam heights to a bore regime for higher dam heights. Finally, we show that this change in behaviour directly influenced the local energy dissipation and the resulting avalanche run-out shortening downstream of the dam.

This paper analyzes the effect of forest canopy on snow water equivalent during two consecutive snow seasons in a mixed beech–fir stand in the Pyrenees. The results confirm that the forest canopy is a dominant influence on snowpack distribution during the accumulation and melting periods. In general, a noticeable decrease in snow water equivalent and an increase in variability among observations are detected with increasing density of the forest canopy. The influence of the forest canopy on melting rates is complex and highly dependent on the dominant climatic conditions. Similar conclusions are reached for both of the snow seasons for which measurements are available, but several differences are also recorded. This study highlights the important influence of climatic conditions observed during the snow season on the relationship between stand characteristics and snowpack dynamics.

Two inverse methods are proposed as a means of estimating the thermal diffusivity of snow and firn from continuous measurements of their temperature. The first method is applicable to shallow depths where temperature experiences diurnal variations, and is based on the fact that phase and amplitude of these diurnal variations are functions of the thermal diffusivity. The second method is applicable to the deeper part of the firn layer, and is based on a simple least-squares estimation technique. The methods applied here differ from various methods used for borehole paleothermometry in that observations are continuous in time and performance constraints on model/data misfit can be applied over a finite temporal period. Both methods are tested on temperature records from thermistor strings operating in the upper 2.5 m of firn on iceberg C16 (Ross Sea, Antarctica) from 2004 to 2007. Results of the analysis show promise in identifying melting events and the movement and refreezing of meltwater within the snow/firn layer.

To assess the seasonal stability of the δ18O stratigraphy in winter snowpacks in the Canadian Rocky Mountains, snow pits were sampled over three accumulation seasons at two field sites. These sites, Opabin and Haig Glaciers, are ~160km apart at similar elevations and represent windward and lee-slope environments respectively. At both sites, snow pits were sampled at one glacier and one forefield location throughout each accumulation season. Intra-seasonal changes in δ18O at each site were examined to determine the extent of post-depositional modification of isotope stratigraphies. At both glacier sites, there was minimal temporal change before the onset of spring melt in all years. In addition, the similar structure of δ18O profiles from both glacier sites suggests that regional controls govern the isotopic composition of solid-phase precipitation across the study area. At forefield locations, the absence of an insulating layer of ice at the base of the snowpack allowed for vapour transport and post-depositional modification of the seasonal δ18O signal. This did not result in consistent changes to the mean δ18O, deuterium excess and δD–δ18O regression line slopes in the lower layers of snow, and the observed smoothing of δ18O profiles was less than that simulated by applying a diffusion model to these snowpacks.

Avalanche forecasting is a complex process involving the assimilation of multiple data sources to make predictions over varying spatial and temporal resolutions. Numerically assisted forecasting often uses nearest-neighbour methods (NN), which are known to have limitations when dealing with high-dimensional data. We apply support vector machines (SVMs) to a dataset from Lochaber, Scotland, UK, to assess their applicability in avalanche forecasting. SVMs belong to a family of theoretically based techniques from machine learning and are designed to deal with high-dimensional data. Initial experiments showed that SVMs gave results that were comparable with NN for categorical and probabilistic forecasts. Experiments utilizing the ability of SVMs to deal with high dimensionality in producing a spatial forecast show promise, but require further work.

In this study, the three-dimensional (3-D) microstructure of polar firn is investigated by means of X-ray microfocus computer tomography (mCT). Basic topological properties including the Euler and coordination numbers are derived from the reconstructed 3-D volume images. It is shown that sample volumes of about 4 cm3 are representative for polar firn in terms of their connectivity. The connectivity function defined as the change of Euler number with structure size is calculated via image-processing routines. It is used to split the ice phase at small bridges into single crystallite agglomerates. The bond-size distributions and the mean size of the agglomerates are estimated. All μCT measurements were carried out on the uppermost 9 m of a shallow firn core (B35) drilled during the 2005/06 field campaign at Kohnen station, Dronning Maud Land (DML), Antarctica. The results are compared with estimates from classical two-dimensional (2-D) surface section observations. The 3-D approach confirms the linear relationship between coordination number and density which hitherto has only been derived from 2-D observations. Layers of buried snow dunes show a stronger connectivity than layers of moderate crystal size and density. The formation of agglomerates made of crystallites is a common feature of polar firn in DML. It is proposed that the growth of agglomerates leads to reduced critical densities for the transition between the densification regime of grain boundary sliding and plastic deformation.

Specific features of the physics of blown sand and PVC particles were investigated in wind-tunnel experiments. The fluctuations in particle concentration over time were derived from image processing of high-speed films (500 Hz). Spectral analysis of these time series showed a slowly decreasing slope within a frequency range that could be larger than the inertial sub-range of the free stream. A specific transport regime also appears in the lower part of the flow for frequencies less than 10 Hz. The role of turbulence in the generation of this regime is discussed using a simple theoretical model able to describe the aerodynamic behavior of a particle.