To investigate the effects of depositional and post-depositional processes on chemical records in the snowpack, seven monthly snow pits were sampled at the same site on the pass of Zhadang (ZD) glacier (30˚28.079' N, 90˚39.032' E; 5800ma.s.l.), Nyainqentanglha mountain, southern Tibetan Plateau, between April and October 2006. Meteorological data from an automatic weather station at the sampling site showed that the annual mean air temperature was –5.6˚C on the pass and that monthly air temperature was above 0˚C from June to August, indicating that snowmelt could occur in this high-elevation region during the summer. An analysis of δ18O and major-ion variability in snow pits suggests that glaciochemical recordswere influenced by both meltwater percolation in mid-summer (July and August) and seasonal deposition. Less negative δ18O values and high concentrations of major ions occurred during the spring. The trends of δ18O variations in the ZD snow pits were consistent with those in precipitation sampled at the nearby Nam Co station for all months except for July and August, suggesting that climate signals are well preserved in the snow-pit δ18O records during the non-summer months. However, these climate signals were destroyed by strong percolation of meltwater during mid-summer.

We report on the development of depth hoar and its relation to stable oxygen isotopic content in snow–firn stratigraphy in the percolation zone of Ürümqi glacier No. 1, eastern Tien Shan, China, during the period September 2004–August 2006. The essential condition for the development of depth hoar in the snow–firn pack is the temperature gradient. When the temperature gradient of the snow–firn pack reaches a maximum value of 13.0˚Cm–1 in mid-October, depth hoar begins to develop. By the end of March, the depth hoar might account for 25% of the total snow–firn pack depth. From April to June, as the weather becomes warm, the transport of water vapor diminishes and melting– regelation metamorphism replaces metamorphism caused by the temperature gradient. As a result, the depth hoar turns into coarse-grained firn. Fractionation of the oxygen isotopic content also occurs during formation of the depth hoar. The bottom 15 cm of the depth-hoar δ18O values were depleted in the lighter isotopic species as the snow sublimated from the lower to the upper crystals, and the δ values increased from –9.4% to –7.0% from 8 September 2004 to 25 January 2005. The upper 10 cm of the depth-hoar δ18O values were enriched in the lighter isotopic species and the δ values decreased from –6.8% to –9.3% during the same period.

This paper presents a new simple and efficient algorithm to retrieve the effective snow grain size and soot concentration from spectral reflectance on snow measured by optical instrument on a satellite. This algorithm was recently developed and will be used for integrated ice–atmosphere–ocean monitoring in the framework of the DAMOCLES program. The algorithm is based on an analytical approach to snow optics. In this approach snow is considered as a close-packed medium with irregularly shaped grains rather than with independent spherical particles. Unlike the known conventional algorithms, the developed algorithm uses no a priori snow optical model. The analytical nature of this algorithm provides a very fast inversion of the reflection data. The developed algorithm was realized and validated for the GLI and MODIS instruments. The algorithm can be generalized for other satellite instruments with appropriate spectral channels. Finally, the results of verifications using a computer simulation are discussed.

In this study, we report on the spatial and temporal distribution of seasonal snow depth derived from passive microwave satellite remote-sensing data (e.g. SMMR from 1978 to 1987 and SMM/ I from 1987 to 2006) in China. We first modified the Chang algorithm and then validated it using meteorological observation data, considering the influences from vegetation, wet snow, precipitation, cold desert and frozen ground. Furthermore, the modified algorithm is dynamically adjusted based on the seasonal variation of grain size and snow density. Snow-depth distribution is indirectly validated by MODIS snow-cover products by comparing the snow-extent area from this work. The final snow-depth datasets from 1978 to 2006 show that the interannual snow-depth variation is very significant. The spatial and temporal distribution of snow depth is illustrated and discussed, including the steady snow-cover regions in China and snow-mass trend in these regions. Though the areal extent of seasonal snow cover in the Northern Hemisphere indicates a weak decrease over a long period, there is no clear trend in change of snow-cover area extent in China. However, snow mass over the Qinghai–Tibetan Plateau and northwestern China has increased, while it has weakly decreased in northeastern China. Overall, snow depth in China during the past three decades shows significant interannual variation, with a weak increasing trend.

A detailed model of Alpine surface processes is used to simulate the amount of preferential deposition as well as redistribution of snow due to snowdrift for two alpine glaciers (Goldbergkees and Kleinfleißkees, Austrian Alps). The sequence of snow-cover modelling consists of the simulation of the wind field with a mesoscale atmospheric model, a three-dimensional finite-element drift module, an energy-balance module and a snowpack module. All modules with the exception of the wind-field model are integrated within the Alpine3D model frame. The drift module of Alpine3D distinguishes between saltation and suspension and is able to capture preferential deposition of snow precipitation and redistribution of previously deposited snow. Validation of the simulated snow depth is done using the spatially dense snow-probing dataset collected during a campaign in May 2003. Simulated snow depths agree with measurements during winter 2002/03 at locations with detailed snow-height monitoring, taking into account the high spatial variability of snow depth on the glacier. Moreover, comparison of snow accumulation from model results with detailed probing on 1 May 2003 for the total glacier area shows that Alpine3D is able to capture major patterns of spatial distribution of snow accumulation. For the first time, the Alpine3D approach of using high-resolution wind fields from a meteorological model and a physical description of snow transport could be validated for a very steep glacierized area and for a full accumulation season. The results show that drift is a dominant factor to be considered for detailed glacier mass balances. Another dominant factor not considered in this study may be snow redistribution due to avalanches.

Investigation into the depositional and post-depositional processes of atmospheric NH4+ on Ürümqi glacier No. 1 (UG1), China, was implemented within the Program for Glacier Processes Investigation (PGPI) campaign. Aerosol and surface snow samples were collected concurrently on a weekly basis from March 2004 to March 2005 in the UG1 accumulation zone at the headwaters of the Ürümqi river, eastern Tien Shan. All samples were analyzed for NH4+ and other chemical species. This paper investigates the seasonal variations of NH4+. A significant linear relationship (R2 = 0.70, N = 21, P < 0.01) between NH4+ concentrations in surface snow and aerosol was found during spring and summer, indicating that the warm–wet condition facilitates the air–snow exchange of NH4+. Humidity was found to be a significant meteorological factor influencing NH4+ in deposition in autumn and winter. The NH4+ concentration in aerosol clearly shows a trend similar to that in surface snow, suggesting that the variation of atmospheric NH4+ might have been preserved in the surface snow. The possible source of NH4+ is discussed in this paper.

Data of annual mean temperature, annual total precipitation and snow-cover area (SCA) in the winter season from 1982 to 2001 have been analyzed to examine the response of SCA to climate change in the Tarim basin, western China. The results show that over the entire basin SCA exhibits a slowly decreasing trend. The responses of SCA to temperature and precipitation in the northern, western and southern parts of the basin show a stronger effect of precipitation change on SCA than that of temperature. SCA has slowly increased below 2500ma.s.l., but has decreased at higher altitudes. The lowest-altitude zone was apt to be affected by precipitation, while the highest-altitude zone seems to have been influenced mainly by temperature. The middle zone from 2500 to 5000 m was the most sensitive to climate change. Snowfall and melt rates were higher in the 1990s than in the 1980s. In the winter season, SCA change was positively correlated with precipitation change but not with temperature change.

For a better understanding of snow metamorphosing processes and more precise snow-ice-core interpretations, it is necessary to know the extent of microscale spatial variability of isotopic and chemical distributions in a snowpack. This work presents an investigation on the horizontal heterogeneity of the isotopic and chemical distributions in a firn pack on East Rongbuk Glacier at Qomolangma (Mount Everest), central Himalaya. One pit wall of 1.2 ×1.2m2 at 6520ma.s.l. was sampled at intervals of 10 cm in a matrix pattern with a total of 144 samples collected. All the samples were analyzed for δ18O and ionic concentrations. Small horizontal isotopic and large chemical heterogeneities were found. The averaged coefficient of variation (CV) of the twelve 10 cm thick layers for δ18O is 0.052, and in the whole snow thickness of 120 cm it is 0.016, which is in the range of analytic precision and thus indicates complete homogeneity. However, the ionic distribution shows considerable heterogeneity. The averaged CV values of the 10 cm thick layers for ionic concentrations vary in the range 0.628–1.477 depending on the ions. Based on these CV values, the heterogeneity sequence is: Mg2+> Ca2+> K+> Na+> Cl–> SO42–> PO43–> NO3–> NH4+. The averaged CV values for all the ions, except for NH4+, decrease with increasing snow thickness, although the decreasing rates and extents are different. However, the CV values of different ions are still large and in the range 0.183–1.116 when the snow thickness increases to 120 cm. The heterogeneity sequence becomes: K+> Mg2+> Ca2+> NH4+> Na+> Cl–> PO43–> NO3–> SO42–. The CV average change with thickness is different for NH4+. From 20 to 100 cm it increases slightly with increasing thickness, but all the values are lower than the average of 10cm thick layers.

The investigation of spatial and temporal variability of the snow cover in northern Eurasia (snow depth, density, thermal characteristics, water equivalent) includes large-scale fieldwork, modelling and analysis of meteorological data of two winters (2004/05 and 2005/06) from 38 weather stations situated in different climatic conditions and physico-geographical zones. Common regularities and features of snow-cover variability are revealed for these winters, despite their contrasting temperature and precipitation regimes and differences from an average winter, as the time of appearance, duration and depth of snow cover, the number of snowfalls and date of melting. The modelling of snow-cover stratigraphy is based on viscous compression and recrystallization laws. Meteorological information (temperature, wind velocity and precipitation) is used as input for the model. The output is the specific snow-cover stratigraphy according to positioning in different physical–geographical regions and due to the possible variation as determined by winter temperature and precipitation regimes. The peculiarity of snow-cover stratigraphy at the regional scale depends on the meteorological conditions of its formation as well as on the character of landscapes. A satisfactory correlation of the modelled typical columns of the snow cover formed in 2004/05 and 2005/06 in different regions of Russia and of real columns is revealed.

The deposit structure of 20 very small to large avalanches that occurred in the Davos area, eastern Swiss Alps, during winters 2004/05 and 2005/06 was investigated. Snow-cover entrainment was significant in the majority of events and likely to have occurred in all cases. Evidence was found both for plough-like frontal entrainment (especially in wet-snow avalanches) and more gradual erosion along the base of dry-snow avalanches. Several of the dry-snow avalanches, both small and large, showed a fairly abrupt decrease in deposit thickness in the distal direction, often accompanied by changes in the granulometry and the deposit density. Combined with other observations (snow plastered onto tree trunks, deposit-less flow marks in bends, etc.) and measurements at instrumented test sites, this phenomenon is best explained as being due to a fluidized, low-density flow regime that formed mostly in the head of some dry-snow avalanches. The mass fraction of the fluidized deposits ranged from less than 1% to ∼25% of the total deposit mass. Fluidization appears to depend rather sensitively on snow conditions and path properties.

Observational and experimental evidence suggests that it is important to explicitly account for the fluidized flow regime in avalanche hazard mapping due to its high mobility, intermediate density and high velocity. We explore the differences from conventional runout modelling by implementing an extension of the Norem–Irgens–Schieldrop (NIS) rheology in a simple mass-point model. When the dispersive stresses and the excess pore pressure equal the overburden pressure, the flow height increases and the density diminishes until a new equilibrium is reached, determined by the different density dependencies of the two parameters of the dispersive stresses. Fluidization requires sufficiently steep terrain; when it occurs it leads to substantially higher velocities than compared to the dense-flow regime. The model parameters are strongly constrained by their physical meaning and vary little between widely different avalanches. However, in all test cases we obtained better agreement between simulated and observed runout distances and pressure effects than with conventional models.

The spatial and temporal variability of seasonal snow cover in glacierized catchments has important implications for the net mass balance of alpine glaciers. This study examines the relationship between changing snowpack volume, the resulting winter balance and the net mass balance of Storglaciären, northern Sweden. Using a conceptual model, the net seasonal snow input to the glacier is simulated daily for 16 years from 1990. From this the annual snow accumulation and winter balance are calculated. The model outputs are compared with snowlines delineated from classified aerial photographs, ASTER and Landsat 7 ETM+ satellite imagery, and with measured Storglaciären winter balances. The results of the model indicate variability in the winter balance over the study period, though there is a slightly negative trend overall. The highest winter balances and seasonal snow volumes occurred in the early 1990s and correspond with positive net mass balances. However, the slightly negative trend in winter balance and decreased net seasonal snow volumes suggested by the model, combined with the measured increasing trend in mass lost due to ablation, have resulted in decreasing glacier net mass balances and a corresponding rise in ELA over the study period.

The term ‘risk’ can be defined as the probability of unfavourable consequences or negative effects. Risk can be expressed by means of various indices, such as collective or social risk (possible number of dead), individual risk (probability of a person’s death within a certain territory during 1 year), probability of losses, etc. This paper is a case study of the small-scale assessment and mapping of individual avalanche risk focused on the two regions of Russia with the highest levels of avalanche activity: the northern Caucasus and the mountainous parts of Sakhalin island. The basic indices applied for individual avalanche risk estimation are: recurrence interval of avalanches (avalanche frequency), percentage of the whole investigated territory that is occupied by avalanche-prone areas, duration of avalanche danger period, probability of a person’s stay in an avalanche-prone area during 1 day (24 hours) and during 1 year, total population of the area and its density. The results of individual avalanche risk assessment, undertaken for the territory of Russia as a whole, show that its values generally do not exceed the admissible level (from 1×10–6 to 1×10–4). However, some areas of the northern Caucasus, including famous alpine skiing resorts (Krasnaya Poliana, Dombai, the Mount Elbrus region, etc.), and of Sakhalin, including the environs of towns (Kholmsk, Nevel’sk) and other smaller human settlements, are characterized by an unacceptable level of risk. In the aggregate, areas with an unacceptable (>1×10–4) level of individual avalanche risk comprise about 7% of the whole avalanche-prone territory of the northern Caucasus, those with an admissible level comprise 52% and those with an acceptable level (<1×10–6) 41%. The corresponding values for Sakhalin are 0.1%, 14.8% and 85.1%.

Determination of the spatial snow-depth distribution is important in potential avalanche-starting zones, both for avalanche prediction and for the dimensioning of permanent protection measures. Knowledge of the spatial distribution of snow is needed in order to validate snow depths computed from snowpack and snowdrift models. The inaccessibility of alpine terrain and the acute danger of avalanches complicate snow-depth measurements (e.g. when probes are used), so the possibility of measuring the snowpack using terrestrial laser scanning (TLS) was tested. The results obtained were compared to those of tachymetry and manual snow probing. Laser measurements were taken using the long-range laser profile measuring system Riegl LPM-i800HA. The wavelength used by the laser was 0.9 μm (near-infrared). The accuracy was typically within 30 mm. The highest point resolution was 30 mm when measured from a distance of 100 m. Tachymetry measurements were carried out using Leica TCRP1201 systems. Snowpack depths measured by the tachymeter were also used. The datasets captured by tachymetry were used as reference models to compare the three different methods (TLS, tachymetry and snow probing). This is the first time that the accuracy of TLS systems in snowy and alpine weather conditions has been quantified. The relative accuracy between the three measurement methods is bounded by a maximum offset of ±8 cm. Between TLS and the tachymeter the standard deviation is 1σ = 2 cm, and between manual probing and TLS it is up to 1σ = 10 cm, for maximum distances for the TLS and tachymeter of 300 m.

To investigate the environmental and climatic significance of the ice-core records from the Tien Shan, central Asia, the characteristics of ionic concentration and oxygen isotopic ratio (δ18O) as well as their variability are assessed from surface-snow samples as well as old-snow samples collected year-round at weekly intervals from November 2002 to October 2005 on Ürümqi glacier No. 1, eastern Tien Shan. The results indicate that the δ18O in surface-snow samples is reversely coincident with air temperature and insignificantly affected by post-depositional processes. Ionic concentrations in the wet-season (1 November to 31 March) snow are overall higher than those in dry-season (1 April to 31 October) snow, while the variability of relative ionic composition between dry seasons is slightly less than that between wet seasons. During dry seasons, surface-snow chemistry was mostly controlled by the chemical content entrained in some sporadic precipitations. When precipitation is absent, the effect of all post-depositional processes together elevated the ionic concentrations in surface snow. During wet seasons, the snow chemistry is determined mainly by the input of aerosols entrained in precipitation and the elution process from percolation of meltwater.

In an analog weather-forecasting procedure, recorded weather in the past analogs corresponding to the current weather situation is used to predict future weather. Consistent with the procedure, a theoretical framework is developed to predict weather at a specific site in the Pir Panjal range of the northwest Himalaya, India, using surface weather observations of the past ten winters (1991/92 to 2001/02) 3 days in advance. Weather predictions were made as snow day with quantitative snowfall category or no-snow day, for day1 through day3. As currently deployed, the procedure routinely provides a 3 day point weather forecast as guidance information to a weather and avalanche forecaster. Forecasts by analog model are evaluated by the various accuracy measures achieved for an independent dataset of three winters (2002/03 to 2004/05). The results indicate that weather forecasts by analog model are quite reliable, in that forecast accuracy corresponds closely to the relative frequencies of observed weather events. Moreover, qualitative weather (snow day or no-snow day) and quantitative categorical snowfall forecasts (quantitative snowfall category for snow day) are better than reference forecasts based on persistence and climatology for day1 predictions. Site-specific snowfall forecast guidance may play a major role in assessing avalanche danger, and accordingly formulating an avalanche forecast for a given area in advance.