The ever increasing demand for robust, higher resolution, multi-faceted climate change information motivates a reinvigorated modelling effort designed to produce Canadian focused projections. In this talk I will describe our plans to develop an integrated modelling system that forms the basis the climate information value chain in Canada. The modelling system relies on a modernized software infrastructure that enables collaborative development and application of the models. On this foundation we are building the next generation global Canadian Earth System Model version 6, and I will describe key progress and challenges in this effort. CanESM6 will be based on the GEM dynamical core, CCCma climate physics including the CLASSIC land surface, and a customized version of the NEMO4 ocean model. We plan to extensively downscale projections and seasonal predictions from CanESM6 to regional scales using CanRCM6 for the atmosphere. A new system, the Canadian Three Oceans Downscaling System (CanTODS), is planned to allow consistent downscaling of projections and predictions across Canada’s coastal domain. We ultimately aim to couple CanRCM and CanTODS to produce the Canadian Regional Earth System Model. The global to regional scale climate information produced by our integrated climate modelling system will be further bias corrected, statistically downscaled, and developed into user friendly climate products and indicators by our colleagues in Environment and Climate Change Canada, and regional climate consortia. We welcome the opportunity to explore co-developing our modelling systems and their outputs to ensure that the climate information produced is of optimal utility for end users.
Dr. Neil C. Swart is a climate scientist specializing in earth system modelling at the Canadian Centre for Climate Modelling and Analysis, where he coordinates the team that builds the Canadian Earth System Model (CanESM), which is widely deployed for climate modelling applications including contributing to Coupled Model Intercomparison Project (CMIP) and other major, internationally-coordinated projects. Dr. Swart's research focuses on model evaluation, the detection and attribution of climate change, and studying key sources of uncertainty in model projections.