Master & SIE Projects

The Research Unit ‘Snow Avalanches and Prevention’ investigates the formation and dynamics of avalanches, its research group ‘Avalanche Dynamics and Risk Management’ aims to identify the processes involved in snow avalanche flows and in avalanche-structure interactions for better hazard assessment.

The aim of this master thesis is to analyse and physically interpret full-scale avalanche measurements collected at the “Vallée de la Sionne” test site (VS). Avalanche dynamics parameters such as velocity, pressure and flow depth are measured at the site on a 20m high steel pylon. Since 2017 a high-speed camera monitors the interaction between the pylon and avalanches characterized by different snow properties and regimes. In this contest, you will extract the following information form the high-speed camera images:

• The 2D velocity field generate by the avalanche around the pylon;
• The avalanche particle size distribution in the denser region of the avalanche;
• The characteristics of the turbulent field, which develops in powder snow avalanches.

The data extracted from the high-camera data will be compared to pressure, velocity and temperature measurements at the pylon to provide a physical interpretation of the underlying processes governing the interaction between avalanches and infrastructures.

You are a skilful Matlab or Python programmer with basic knowledge on fluid or granular flows and velocimetry techniques. You have experience in handling large data sets. You have good oral and written communication skills, in particular in English. You are well organized and like to work in a team.

During your stay in Davos you will work in close collaboration with the scientific staff of the avalanche dynamics team. The duration of the thesis is 6 months and starts from spring 2019.

Contact: Betty Sovilla, [email protected]

How to prepare an optimal ski run for alpine skiing? Ski runs require several hours of resting time to reach adequate hardness and resistance for skiing. This hardening is mainly caused by sintering of the snow. Sintering is the growing and strengthening of bonds between ice grains and results in a distinct hardening of the snow. Because of the large impact of the weather condition on sintering, adequate planning and timing of piste preparation is a big challenge for ski resort operators. Speed and duration of sintering depends on snow characteristics and energy exchange between snow surface and atmosphere.

In order to investigate the sintering process on ski runs we are proposing a Master thesis starting in fall 2019. The thesis combines field measurements in the Ski resorts of Lenzerheide and Davos (GR) (snow and meteorological measurements) with process based simulations with the numerical physically based snow-cover model SNOWPACK. This will help us to improve our understanding of snow sintering and to develop guidelines for improved piste preparation.

The student has a passion for snow and skiing and is motivated and competent to plan and perform field work on ski runs safely and self-reliantly. He/she has experience with data analysis and is also motivated to work with complex physical computer models. A driving license and German skills would be of advantage.

Individuals who are available from 01.10.2019 and hold a bachelor’s degree in mechanical engineering, material science or civil and environmental engineering are encouraged to apply. The student will be supported by staff from the ski resort and from the SLF

Since the 1960s, stable water isotopes in polar snow and ice have been used as proxies for both local and global temperature records. The interpretation of ice core data and the comparison with atmospheric model results implicitly rely on the assumption that the snowfall precipitation signal is perfectly preserved in the snow-ice matrix ignoring snow-vapor exchanges between surface snow and atmospheric water vapor. However, a recent study carried out on top of the Greenland Ice Sheet combining continuous atmospheric water vapor isotope observations with daily snow surface sampling documented a clear day-to-day variation of surface snow isotopic composition in-between precipitation events. This effect was interpreted as being caused by uptake of the synoptic driven atmospheric water vapor isotope signal by individual snow crystals undergoing snow metamorphism. However, the impact of this process on the isotopetemperature reconstruction is not yet sufficiently understood, but crucial, compared to interstitial diffusion, and will alter the isotope mean value. In order to understand the basic mechanism governing the interaction between snow and atmosphere, the physical complexity of experiments have to reduce. Therefore, the goal of this Master Thesis is to perform defined experimental runs in the cold laboratory and wind channel at SLF Davos. You will work in an innovative interdisciplinary project and make significant contributions to the advancement of stable water isotope research in snow and ice.

>> Know more about the project

The task consists of running SNOWPACK simulations at two local weather stations as well as a (small) number of grid points from the COSMO meteorological forecast model and has the following steps:

1) Setting-up the model simulations including quality control of the input data;

2) Producing the model simulations and visualizing the results; 3) Interpreting the results with respect to avalanche danger and melt behavior;

4) Comparing the results to available observations;

5) Compiling a scientific report. The work can (partly) be executed in Livigno and own observations may be taken as conditions and logistics permit.

If you are interested, please contact Prof. Michael Lehning, ([email protected])

In recent years, a number of critical parameters, which should indicate snow cover instability, have been proposed. Some of these parameters such as conventional stability indices, counting critical snow layer features (threshold sum approach) or an assessment of the deformation rate are already implemented in SNOWPACK. Some newer ones such as weak layer fracture propagation energy or critical cut length should be implemented in the context of the work proposed with help of the experts at SLF or ALPsolut. The main part of the work is then devoted to testing these indices against observations and making an assessment report. The work will be carried out partly at SLF Davos to ensure access to relevant data and know how.

If you are interested, please contact Prof. Michael Lehning, ([email protected])

Snow cover variability is known to be one of the most important parameters influencing avalanche formation; this is even more relevant for skied slopes. The task consists in characterizing the snow cover characteristics on more versus less skied slopes by using NIR-photograpy, snow penetrometer profiles and classical snow observations. The work is organized in three parts:

1) collecting snow cover data;

2) Analysis of the collected data and characterization of the snow cover and snow stability characteristics;

3) Compiling a scientific report.

If you are interested, please contact Prof. Michael Lehning, ([email protected])

Wind slabs are hard layers at the surface of a snowpack. We hypothesize that they are formed either by moisture bearing winds and/or by mechanical compaction of new or surface snow. The goal of the thesis is to investigate in more detail under what meteorological conditions wind slabs are formed. During the past 20 years, more than 500 snow profiles were taken close to automatic weather stations. The student’s task will be to identify potential wind slabs in the profiles and to combine these observations with the meteorological data from the weather stations. The student will then analyse this data set for correlations between weather conditions and the formation of wind slabs. This data-mining project involves searching for relevant data and analysing it using statistical methods and software.

If you are interested, please contact Prof. Michael Lehning ([email protected]), Dr Charles Fierz ([email protected]) or Christian Sommer ([email protected])

Snow profiles are inherently subjective as the observations recorded cannot be repeated nor reproduced. Moreover, the observations are of categorical nature and describe properties of each layer recognized in the snowpack. It is therefore quite difficult to compare quantitatively observed snow profiles with modelled ones. Nevertheless, Lehning et al. (2001) proposed an objective method prone to fill that gap, introducing an agreement score ranging from 0 for no agreement at all to 1 for perfect match. However, first applications of the method suggest that scores below 0.5 are rarely found even though the compared profiles may look quite dissimilar. If this impression is correct, the agreement score should be mapped to this range to give meaningful results. We therefore need to quantify the real dynamic range of the agreement score with respect to various properties of the snowpack.

To answer this question, we propose to randomly construct virtual snow profiles to be compared to model results, requiring that the relative difference in Snow Water Equivalent (SWE) of both objects is less than 20 %. In addition, a few “rules” are needed to avoid unrealistic layers (e.g. new snow of density 400 kg m-3).  Alternatively, one could select randomly observed profiles from the SLF data base to be compared with simulation results, again requiring almost identical SWE.

Lehning, M., Fierz, C., and Lundy, C. 2001. An objective snow profile comparison method and its application to SNOWPACK, Cold Reg. Sci. Technol., 33, 253-261, http://dx.doi.org/10.1016/S0165-232X(01)00044-1.

If you are interested, please contact Prof. Michael Lehning  ([email protected]), or Dr. Charles Fierz ([email protected]), as soon as possible.

From observations in the discontinuous Antarctic sea ice zone, one can infer that riming of precipitation (snow) crystals is a common process. The process appears to be under-represented in current climate or meteorological models but could be a major source of snow mass deposition on sea ice in Antarctica. The thesis quantitatively investigates the importance of this process by calculating scavenging capacities of precipitation particles and evaporation capacities of ocean leads. The calculations will be done analytically based on relationships known from cloud physics and using simple model approaches for the atmospheric boundary layer over snow-covered sea ice and open water. The calculations will be validated against existing data on rimed precipitation particles.

If you are interested, please contact Prof. Michael Lehning ([email protected]), Dr. Katerine Leonard as soon as possible.

Recent expeditions to the North Pole and into the Antarctic sea ice collected snow micropenetrometer profiles of snow structure together with snow density profiles and some information on snow optical grainsize. The purpose of the thesis is to analyze the data and extract key optical and mechanical parameters. The focus will be to see in how far systematic differences between the Arctic and Antarctic snow cover exist. The arctic sea ice snow cover is typically thin and snow depth does not vary a lot spatially. The Antarctic snow cover on the other hand is much thicker and also more variable. This thesis will make use of a unique data set to compare and contrast the snow characteristics of these remote and rapidly changing regions. The results may help to explain the dynamics of sea ice formation and destruction in these different regimes, as well as aiding in the interpretation of remote sensing data.

If you are interested, please contact Prof. Michael Lehning  ([email protected]) or Dr. Hendrik Huwald ([email protected]) as soon as possible.