Machine learning, AI, climatology
QAUJIKKAUT: an on-line advanced foresight tool of extreme meteorological events and natural hazards in Nunavik
Director: Thierry Badard
Climate change can have serious consequences for the sustainable development of northern communities and for tourism, industrial and governmental activities in the North. Appropriate decision-making for mitigating and adapting to these impacts can be achieved by the collection and analysis of data related to these impacts and also by the study of the factors driving them.
The objective of the Qaujikkaut ("warning" in Inuktitut) project is to develop an online tool for early warning of extreme weather events and natural hazards in Nunavik. This tool will be based on real-time data from the SILA network of environmental monitoring stations operated by the Centre for Northern Studies (CEN) and the Ministère de l'Environnement et de la Lutte contre les changements climatiques (MELCC – Department of Environment) in Nunavik.
The main objective of the successful candidate will be to perform predictive modelling and achieve advanced foresight of problematic environmental conditions in Nunavik. Using the Qaujikkaut database set up y other students, and machine learning and artificial intelligence approaches such as Decision Tree Learning (Rokach and Maimon, 2008), the Ph.D. student will develop algorithms for detecting beforehand extreme meteorological events and related natural hazards based on climate indicators and their thresholds. He/She will be supervised by Thierry Badard and co-supervised by François Laviolette and Richard Fortier.