PhD position - Towards a better representation of wind slabs in Arctic snowpacks within the SVS2-Crocus model

Description

At high latitudes, snow covers the ground for most of the year. Due to its high albedo and low thermal conductivity, snow regulates air temperature near the surface, in addition to influencing the soil thermal regime. In the Arctic, snow cover is typically structured in two layers with contrasting physical properties. The lower layer consists of depth hoar, which is not very dense and is a poor heat conductor. The layer just above it is a wind slab – it is much denser and conducts heat more effectively. This layer is the focus of the proposed PhD project. While the processes responsible for the densification of this wind slab are known (fragmentation of snow grains under the effect of wind, sheltering effect of low vegetation, water vapor flux from the underlying layer), their relative importance in the Arctic is poorly documented. This results in an imperfect representation in the SVS2-Crocus snow model, which is currently being developed for the next version of Environment and Climate Change Canada's hydrometeorological forecasting platform.

This PhD project aims to enhance the SVS2-Crocus model's representation of the processes responsible for the densification of wind slab layers in the Arctic snowpack. First, various existing parameterisations will be tested using available Arctic snow datasets. Next, a measurement campaign will be conducted in Ikaluktutiak (Cambridge Bay, Canada), in close collaboration with the local community and another research team that is very active at the site. These in situ measurements will enable us to develop parameterisations of the effects of wind and vegetation on wind slabs, while also capturing their spatial variability. The candidate will also collaborate with another PhD student in our team who is working specifically on water vapour fluxes in snow, as well as with the Snow research centre in France.

Requirements and Conditions

- MSc degree in engineering, physics, environmental sciences or geography
- Desirable: experience in data analysis, modeling and/or field work
- Motivation, teamwork and communication skills
- Programming experience (Python, R, Matlab or equivalent)

Please email Prof. Daniel Nadeau (daniel.nadeau@gci.ulaval.ca) and Dr. Vincent Vionnet (Vincent.Vionnet@ec.gc.ca) with your CV, a short cover letter, examples of previous research (M.Sc. thesis or published articles), and the names of two references.