PhD position in Arctic snow modeling

European Geosciences Union e.V.; Quebec; On-site; CAD 30,000; Full time

Job summary

A leading research project at Université Laval seeks a PhD candidate to enhance the representation of wind slabs in Arctic snowpacks within the SVS2-Crocus model. The role requires a master's degree and offers substantial funding while collaborating with local communities and research teams.

Qualifications

• MSc degree in relevant field required.
• Experience in data analysis, modeling, or field work preferred.
• Skills in programming are essential for the role.

Responsibilities

• Enhance the SVS2-Crocus model's representation of the processes in Arctic snowpack.
• Conduct a measurement campaign in Ikaluktutiak to develop effective parameterisations.

Skills

Data analysis

Modeling

Field work

Programming (Python, R, Matlab)

Teamwork

Communication

Education

MSc degree in engineering, physics, environmental sciences or geography

Job description

Université Laval (UL) is the oldest French-speaking university in North America. It is home to some 47,000 students in 17 faculties, 60 departments and schools, and nearly 400 undergraduate and graduate programs in all fields of knowledge. Université Laval offers strong graduate programs in northern research. Although it is a French-speaking university, it is very common to complete graduate studies in English.

Cryospheric Sciences (CR)
Hydrological Sciences (HS)

Type

Full time

Level

Student / Graduate / Internship

Funding of 30,000 CAD/year available for 4 years, plus a supplement of 3,000 CAD/year from Université Laval's Faculty of Science and Engineering and teaching assistant contracts.

Preferred education

Master

Open until the position is filled

Posted

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

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.

How to apply

Required Qualifications and Skills
- 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)