A review of air–ice chemical and physical interactions (AICI): liquids, quasi-liquids, and solids in snow

Snow in the environment acts as a host to rich chemistry and provides a matrix for physical exchange of contaminants within the ecosystem. The goal of this review is to summarise the current state of knowledge of physical processes and chemical reactivity in surface snow with relevance to polar regions. It focuses on a description of impurities in distinct compartments present in surface snow, such as snow crystals, grain boundaries, crystal surfaces, and liquid parts. It emphasises the microscopic description of the ice surface and its link with the environment. Distinct differences between the disordered air–ice interface, often termed quasi-liquid layer, and a liquid phase are highlighted. The reactivity in these different compartments of surface snow is discussed using many experimental studies, simulations, and selected snow models from the molecular to the macro-scale. Although new experimental techniques have extended our knowledge of the surface properties of ice and their impact on some single reactions and processes, others occurring on, at or within snow grains remain unquantified. The presence of liquid or liquid-like compartments either due to the formation of brine or disorder at surfaces of snow crystals below the freezing point may strongly modify reaction rates. Therefore, future experiments should include a detailed characterisation of the surface properties of the ice matrices. A further point that remains largely unresolved is the distribution of impurities between the different domains of the condensed phase inside the snowpack, i.e. in the bulk solid, in liquid at the surface or trapped in confined pockets within or between grains, or at the surface. While surface-sensitive laboratory techniques may in the future help to resolve this point for equilibrium conditions, additional uncertainty for the environmental snowpack may be caused by the highly dynamic nature of the snowpack due to the fast metamorphism occurring under certain environmental conditions. Due to these gaps in knowledge the first snow chemistry models have attempted to reproduce certain processes like the long-term incorporation of volatile compounds in snow and firn or the release of reactive species from the snowpack. Although so far none of the models offers a coupled approach of physical and chemical processes or a detailed representation of the different compartments, they have successfully been used to reproduce some field experiments. A fully coupled snow chemistry and physics model remains to be developed.

Snow shielding factors for cosmogenic nuclide dating inferred from long-term neutron detector monitoring

The depth-dependent attenuation of the secondary cosmic-ray particle flux due to snow cover and its effects on production rates of cosmogenic nuclides constitutes a potential source of uncertainty for studies conducted in regions characterized by frequent seasonal snow burial. Recent experimental and numerical modelling studies have yielded new constraints on the effect of hydrogen-rich media on the production rates of cosmogenic nuclides by low- and high-energy neutrons (<10(-3) MeV and >10(2) MeV, respectively). Here we present long-term neutron-detector monitoring data from a natural setting that we use to quantify the effect of snow cover on the attenuation of fast neutrons (0.1-10 MeV), which are responsible for the production of Ne-21 from Mg and Cl-36 from K. We use data measured between July 2001 and May 2008 at seven stations located throughout the Ecrins-Pelvoux massif (French Western Alps) and its surroundings, at elevations ranging from 200 to 2500 m a.s.l. From the cosmic-ray fluxes recorded during summer, when snow is absent, we infer an apparent attenuation length of 148 g cm(-2) in the atmosphere at a latitude of similar to 45 degrees N and for altitudes ranging from similar to 200 to 2500 m a.s.l. Using snow water-equivalent (SWE) values obtained through snow-coring campaigns that overlap in time the neutron monitoring for five stations, we show that fast neutrons are much more strongly attenuated in snow than predicted by a conventional mass-shielding formulation and the attenuation length estimated in the atmosphere. We suggest that such strong attenuation results from boundary effects at the atmosphere/snow interface induced by the high efficiency of water as a neutron moderator. Finally, we propose an empirical model that allows calculating snow-shielding correction factors as a function of SWE for studies using Ne-21 and Cl-36 analyses in Mg- and K-rich minerals, respectively. This empirical model is of interest for studies with a focus on cosmic-ray exposure dating, particularly if the target rocks are made up of mafic to ultramafic units where seasonal snow-cover is a common phenomenon.

Arctic moisture source for Eurasian snow cover variations in autumn

Eurasian fall snow cover changes have been suggested as a driver for changes in the Arctic Oscillation and might provide a link between sea-ice decline in the Arctic during summer and atmospheric circulation in the following winter. However, the mechanism connecting snow cover in Eurasia to sea-ice decline in autumn is still under debate. Our analysis is based on snow observations from 820 Russian land stations, moisture transport using a Lagrangian approach derived from meteorological re-analyses. We show that declining sea-ice in the Barents and Kara Seas (BKS) acts as moisture source for the enhanced Western Siberian snow depth as a result of changed tropospheric moisture transport. Transient disturbances enter the continent from the BKS region related to anomalies in the planetary wave pattern and move southward along the Ural mountains where they merge into the extension of the Mediterranean storm track.

Modelling the system behaviour of wet snow avalanches using an expert system approach for risk management on high alpine traffic roads

The presented approach describes a model for a rule-based expert system calculating the temporal variability of the release of wet snow avalanches, using the assumption of avalanche triggering without the loading of new snow. The knowledge base of the model is created by using investigations on the system behaviour of wet snow avalanches in the Italian Ortles Alps, and is represented by a fuzzy logic rule-base. Input parameters of the expert system are numerical and linguistic variables, measurable meteorological and topographical factors and observable characteristics of the snow cover. Output of the inference method is the quantified release disposition for wet snow avalanches. Combining topographical parameters and the spatial interpolation of the calculated release disposition a hazard index map is dynamically generated. Furthermore, the spatial and temporal variability of damage potential on roads exposed to wet snow avalanches can be quantified, expressed by the number of persons at risk. The application of the rule base to the available data in the study area generated plausible results. The study demonstrates the potential for the application of expert systems and fuzzy logic in the field of natural hazard monitoring and risk management.

Isotopic effects of nitrate photochemistry in snow: a field study at Dome C, Antarctica

Stable isotope ratios of nitrate preserved in deep ice cores are expected to provide unique and valuable information regarding paleoatmospheric processes. However, due to the post-depositional loss of nitrate in snow, this information may be erased or significantly modified by physical or photochemical processes before preservation in ice. We investigated the role of solar UV photolysis in the post-depositional modification of nitrate mass and stable isotoperatios at Dome C, Antarctica, during the austral summer of 2011/2012. Two 30 cm snow pits were filled with homogenized drifted snow from the vicinity of the base. One of these pits was covered with a plexiglass plate that transmits solar UV radiation, while the other was covered with a different plexiglass plate having a low UV transmittance. Samples were then collected from each pit at a 2–5 cm depth resolution and a 10-day frequency. At the end of the season, acomparable nitrate mass loss was observed in both pits for the top-level samples (0–7 cm) attributed to mixing with the surrounding snow. After excluding samples impacted by the mixing process, we derived an average apparent nitrogen isotopic fractionation (15" app/of role in driving the isotopic fractionation of nitrate in snow.We have estimated a purely photolytic nitrogen isotopic fractionation (15"photo) of -55.8 12.0 ‰ from the difference in the derived apparent isotopic ractionations of the two experimental fields, as both pits were exposed to similar physical processes except exposure to solar UV. This value is in close agreement with the 15" photo value of -47.9 6.8 ‰ derived in a laboratory experiment simulated for Dome C conditions (Berhanu et al., 2014). We have also observed an insensitivity of 15" with depth in the snowpack under the given experimental setup. This is due to the uniform attenuation of incoming solar UV by snow, as 15" is strongly dependent on the spectral distribution of the incoming light flux. Together with earlier work, the results presented here represent a strong body of evidence that solar UV photolysis is the most relevant post-depositional process modifying the stable isotope ratios of snow nitrate at low-accumulation sites, where many deep ice cores are drilled. Nevertheless, modeling the loss of nitrate in snow is still required before a robust interpretation of ice core records can be provided.

Lake-effect snow as the dominant control of mesic-forest distribution in Michigan, USA

1Recent studies demonstrated the sensitivity of northern forest ecosystems to changes in the amount and duration of snow cover at annual to decadal time scales. However, the consequences of snowfall variability remain uncertain for ecological variables operating at longer time scales, especially the distributions of forest communities. 2The Great Lakes region of North America offers a unique setting to examine the long-term effects of variable snowfall on forest communities. Lake-effect snow produces a three-fold gradient in annual snowfall over tens of kilometres, and dramatic edaphic variations occur among landform types resulting from Quaternary glaciations. We tested the hypothesis that these factors interact to control the distributions of mesic (dominated by Acer saccharum, Tsuga canadensis and Fagus grandifolia) and xeric forests (dominated by Pinus and Quercus spp.) in northern Lower Michigan. 3We compiled pre-European-settlement vegetation data and overlaid these data with records of climate, water balance and soil, onto Landtype Association polygons in a geographical information system. We then used multivariate adaptive regression splines to model the abundance of mesic vegetation in relation to environmental controls. 4Snowfall is the most predictive among five variables retained by our model, and it affects model performance 29% more than soil texture, the second most important variable. The abundance of mesic trees is high on fine-textured soils regardless of snowfall, but it increases with snowfall on coarse-textured substrates. Lake-effect snowfall also determines the species composition within mesic forests. The weighted importance of A. saccharum is significantly greater than of T. canadensis or F. grandifolia within the lake-effect snowbelt, whereas T. canadensis is more plentiful outside the snowbelt. These patterns are probably driven by the influence of snowfall on soil moisture, nutrient availability and fire return intervals. 5Our results imply that a key factor dictating the spatio-temporal patterns of forest communities in the vast region around the Great Lakes is how the lake-effect snowfall regime responds to global change. Snowfall reductions will probably cause a major decrease in the abundance of ecologically and economically important species, such as A. saccharum.