Methods for Constraining Climate Projections (CMIP6) over Canada to Support the Hydrological Community
The use of an approach to constrain climate projection ensembles has become a priority research topic with the publication of CMIP6 data showing greater sensitivity and more dispersion of the climate than CMIP5.
Project details
Principal(s) investigator(s)
Context
The downscaling of regional climate models by climate projections typically uses driving data from an ensemble of global climate models to provide uncertainty estimates based on the performance of global climate models. Recently, several studies (Liang et al., 2020; Bruner et al., 2020) have shown that the uncertainty of these regional scale projections can be reduced by constraining the choice of global climate models according to their ability to reproduce historical climate conditions in specific geographic regions. In particular, Bruner et al. (2020) have shown that uncertainty is reduced by constraining the choice of global climate models based on their observed climate performance (also called emerging constraints) and their intermodel independence for certain European regional domains.
In this project, the emerging constraints approach will be applied to recent CMIP6 data for a pan-Canadian domain. The objective is to assess whether the approach will reduce uncertainty and thus improve flood mapping for the future.
Objective(s)
This project has three objectives :
-
To develop an overview of the most recent advances (literature review and personal communications) concerning emerging constraints in order to select the method(s) to be applied;
-
To reduce the uncertainty of climate projections by applying emerging constraints tailored to Canada; and
-
To enable an informed choice of global climate models for driving data, representing the uncertainty spectrum while selecting the most plausible climate trajectories.
Methodology
This project will be completed in two phases. The first phase will be to explore, select and adapt various constraint methods to select and weight the global climate models of the CMIP6 ensemble. This first phase will provide a sub-ensemble of plausible climate trajectories for Canada. This method is inspired in particular by Liang et al. (2020) and what has been done for Europe through the EUCP Atlas of constrained climate projections. The use of such an approach is all the more important since CMIP6 shows greater sensitivity and more dispersion of the climate than CMIP5.
The second phase will focus on studying the potentially reduced uncertainty for key variables such as precipitation and temperature by examining, for example, the impact of atmospheric circulation (Zappa and Shepherd, 2017) selected from climate trajectories provided by the constrained sub-ensemble.
Expected results
This project aims to develop a constrained sub-ensemble of simulations from the CMIP6 ensemble, tailored for Canada. This ensemble will make it possible to better select the driving models needed for regional modelling and can be used directly in hydrology.
Benefits for adaptation
Benefits for adaptation
Better knowledge and use of the climate data used to develop climate services.
The key results will be disseminated to the wider scientific community through Environment and Climate Change Canada’s data portals and through the Ouranos network of researchers.
Funding
Other participants
- Dominique Paquin, Ouranos
- Marie-Pier Labonté, Ouranos
- Martin Leduc, Ouranos
- Isabelle Chouinard, Ouranos
- John Scinnoca, Centre canadien de la modélisation et de l'analyse climatique
Related projects
