PhD in simulation of permafrost change and quantification of confidence in resulting data products

Posted: April 27, 2020 (update)
Anticipated start: Fall (September) term 2020, with flexibility in responding to COVID-19 related travel restrictions.   
Supervisory team: Stephan Gruber (Carleton University), Joe Melton (University of Victoria / Environment and Climate Change Canada), Trevor Lantz (University of Victoria) and Steve Kokelj (Northwest Territories Geological Survey).

This project will develop methods and tools for evaluating permafrost models with observational data. This is important because the lack of meaningful and quantitative evaluation of permafrost simulation results impedes the improvement of simulation tools and the use of their outputs for informing adaptation design or policy. This project will use the database compiled in NSERC PermafrostNet (PINGO) as a source of observational evidence to provide confidence in simulation-based permafrost climate services. With practical application of simulation results in mind, this project will comprehensively investigate how well ground temperature change and ground-ice loss can be predicted. For this, ensemble permafrost predictions will be analyzed in terms of error and uncertainty. Ensembles will use multiple re-analyses, downscaled heuristically, as driving climate, multiple models as well as multiple parameter and input data sets (e.g., estimated ground ice distribution, vegetation) for perturbed physics simulations in each model. Error and uncertainty will be statistically decomposed with respect to their likely origins to better inform model development and the use of model results. This quantitative evaluation will be complemented by investigating face validity, a concept developed to capture the trust that diverse experts, such as model developers, permafrost field scientists and northerners, place in simulation results based on subjective assessment. This will allow to better utilise the diverse expertise in the network for identifying and assessing known unknowns in simulations and to develop ways of communicating these to modelers and stakeholders. The combination of statistical evaluation with face validity will improve the dialogue between model developers and users of simulation results and thereby reduce barriers to the acceptance and uptake of simulation products.

This fully funded PhD studentship will be based at Carleton University in Ottawa, Canada. As part of NSERC PermafrostNet, the new Permafrost Partnership Network for Canada (, it will have an outstanding training environment.

The successful candidate will have (1) a master’s degree in a relevant discipline (e.g., geography, Earth science, geophysics, soil physics, atmospheric science, environmental engineering or geotechnical engineering); (2) demonstrated skill in programming and data analysis; (3) previous experience (or a demonstrated interest) in cold regions; as well as (4) excellent written communication in English.

This PhD studentship is fully funded for twelve months per year, for up to four years. International students are eligible to receive a bursary that will reduce their tuition to the amount paid by domestic PhD students.

To apply, Send a cover letter, c.v., copies of transcripts, a writing sample, and contact details for three references to Stephan Gruber ( Applications will be received until the position is filled.