We studied how air moves within snow in Arctic regions and how this affects the snow's structure. Using a new method that links two computer models, we found that cold weather can trigger air movement inside the snow, creating vertical channels and changing the snow's density and temperature. These changes are not captured by traditional models, so our work helps improve how snow and climate processes are simulated in cold environments.

Our research focuses in understanding snow processes at the surface-atmosphere interface, and their influence at larger scales. The use of our advanced numerical model, which includes blowing snow equations, proved to be valuable in predicting the observed ice crystal concentration number at an alpine site. We further demonstrate the effect of blowing snow particles in precipitation and erosion-deposition patterns. Finally, secondary ice production mechanisms are also treated.

This work presents the first high-resolution dataset of wet-snow properties for satellite applications. With it, we validate links between Sentinel-1 backscatter and snowmelt stages and investigate scattering mechanisms through a radiative transfer model. We disclose the influence of liquid water content and surface roughness at different melting stages and address future challenges, such as capturing large-scale scattering mechanisms and enhancing radiative transfer modules for wet snow.

Cornices are overhanging snow accumulations that form on mountain crests. Using wind-tunnel experiments and high-speed photography, the study tracks particle trajectories around cornices and finds distinct differences between edge and surface deposition. A static adhesion model for edge deposition was developed and validated to predict how particle size and shape affect adhesion. The work clarifies the microdynamics of early cornice growth and provides a foundation for avalanche modeling.

Global warming provokes permafrost to thaw, damaging landscapes and infrastructure. This study explores methods to slow this thawing at an alpine site. We investigate different methods based on passive and active cooling. The best approach mixes both methods and manages heat flow, potentially allowing excess energy to be used locally.

Wind-driven airborne transport of snow is a frequent phenomenon in snow-covered regions and a process difficult to study in the field as it is unfolding over large distances. Thus, we use a ring wind tunnel with infinite fetch positioned in a cold laboratory to study the evolution of the shape and size of airborne snow. With the help of stable water isotope analyses, we identify the hitherto unobserved process of airborne snow metamorphism that leads to snow particle rounding and growth.

Information about atmospheric variables is needed to produce simulations of mountain snowpacks. We present a model that can represent processes that shape mountain snowpack, focusing on the accumulation of snow. Simulations show that this model can simulate the complex path that a snowflake takes towards the ground and that this leads to differences in the distribution of snow by the end of winter. Overall, this model shows promise with regard to improving forecasts of snow in mountains.

Observations over several winters at two boreal sites in eastern Canada show that rain-on-snow (ROS) events lead to the formation of melt–freeze layers and that preferential flow is an important water transport mechanism in the sub-canopy snowpack. Simulations with SNOWPACK generally show good agreement with observations, except for the reproduction of melt–freeze layers. This was improved by simulating intercepted snow microstructure evolution, which also modulates ROS-induced runoff.

Snow saltation – the transport of snow close to the surface – occurs when the wind blows over a snow-covered surface with sufficient strength. This phenomenon is represented in some climate models; however, with limited accuracy. By performing numerical simulations and a detailed analysis of previous works, we show that snow saltation is characterized by two regimes. This is not represented in climate models in a consistent way, which hinders the quantification of snow transport and sublimation.

The challenge of running geophysical models is often compounded by the question of where to obtain appropriate data to give as input to a model. Here we present the HICAR model, a simplified atmospheric model capable of running at spatial resolutions of hectometers for long time series or over large domains. This makes physically consistent atmospheric data available at the spatial and temporal scales needed for some terrestrial modeling applications, for example seasonal snow forecasting.

Snow cornices lead to the potential risk of causing snow avalanche hazards, which are still unknown so far. We carried out a wind tunnel experiment in a cold lab to investigate the environmental conditions for snow cornice accretion recorded by a camera. The length growth rate of the cornices reaches a maximum for wind speeds approximately 40 % higher than the threshold wind speed. Experimental results improve our understanding of the cornice formation process.

Most current generation climate and weather models have a relatively simplistic description of snow and snow–atmosphere interaction. One reason for this is the belief that including an advanced snow model would make the simulations too computationally demanding. In this study, we bring together two state-of-the-art models for atmosphere (WRF) and snow cover (SNOWPACK) and highlight both the feasibility and necessity of such coupled models to explore underexplored phenomena in the cryosphere.

This paper presents an Eulerian–Lagrangian snow transport model implemented in the fluid dynamics software OpenFOAM, which we call snowBedFoam 1.0. We apply this model to reproduce snow deposition on a piece of ridged Arctic sea ice, which was produced during the MOSAiC expedition through scan measurements. The model appears to successfully reproduce the enhanced snow accumulation and deposition patterns, although some quantitative uncertainties were shown.

High Alpine catchments are dominated by the melting of seasonal snow cover and glaciers, whose amount and seasonality are expected to be modified by climate change. This paper compares the performances of different types of models in reproducing discharge among two catchments under present conditions and climate change. Despite many advantages, the use of simpler models for climate change applications is controversial as they do not fully represent the physics of the involved processes.

Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.

This study describes and evaluates a new downscaling scheme that addresses the need for hillslope-scale atmospheric forcing time series for modelling the local impact of regional climate change on the land surface in mountain areas. The method has a global scope and is able to generate all model forcing variables required for hydrological and land surface modelling. This is important, as impact models require high-resolution forcings such as those generated here to produce meaningful results.

This study presents an extensive study of climate change impacts on river temperature in Switzerland. Results show that, even for low-emission scenarios, water temperature increase will lead to adverse effects for both ecosystems and socio-economic sectors throughout the 21st century. For high-emission scenarios, the effect will worsen. This study also shows that water seasonal warming will be different between the Alpine regions and the lowlands. Finally, efficiency of models is assessed.