Modelling the risk of ice jams in southern Quebec in the context of climate change
This project will develop a predictive model of the risk of ice jams for a representative sample of southern Quebec watersheds in the context of climate change.
This project will develop a predictive model of the risk of ice jams for a representative sample of southern Quebec watersheds in the context of climate change.
This project has highlighted combined climate events that should be prioritized in Quebec by targeting the information needs related to these events.
This project aims to produce and disseminate climate scenarios for assessing the impacts of greenhouse gases beyond 2100. Case studies will be done to illustrate their use in analyzing the climate vulnerabilities of mine site reclamation infrastructure.
This project will provide an analysis of the economic impacts of forest fires in the context of climate change in Quebec. It will also analyze the cost effectiveness of adaptation solutions to enable informed decision-making.
This project aims to answer the following question : Does the improved simulation of precipitation extremes with the new generation of regional climate models with 2.5 km resolution lead to an improvement in flooding simulations by a hydrological model in southern Quebec?
This project will offer support for the process of prioritizing public infrastructure components in terms of vulnerability to climate change, based on evidence.
Once completed, this project will provide a robust research tool for investigating various questions related to hydrology and climate change in Quebec. It will also offer a way for the hydrological modelling community in Quebec to work together and discuss new developments in the field.
The aim of this project is to minimize the biases of general circulation models before they are used to drive modelling, thus considerably improving the quality of regional climate model results.
This project aims to reduce snow-related uncertainty in pan-Canadian projections by leveraging the latest-generation CMIP6 GCM projection data. The research involves the use of a weighting method called ClimWIP to reduce the uncertainty of CMIP6 GCMs based on their performance, with a particular focus on accurately reproducing the annual maximum of the water equivalent of snow.
This project has increased knowledge of the components of Great Lakes water supply based on observations of their variability and associated uncertainties.