Regional Climate Models

PARC applies high-resolution climate projections to climate risk assessment and adaptation planning, demonstrating the advantages of Regional Climate Model (RCM) data for climate risk assessment. Click on the links below to access information about our current and recent projects.

There are Canadian data portals that provide access to outputs from the suite of climate models used by the IPCC (i.e., CMIP5 and CMIP6), and to runs of these models forced with three Representative Concentration Pathways (RCPs 2.6, 4.5 and 8.5). Use of data from these Global Climate Models (GCMs) enables users to evaluate the large range of changes in climate variables projected by various models and assuming different GHG emission scenarios. These portals are highlighted to the right:

  • Climate Atlas of Canada

    From the Prairie Climate Centre, the Climate Atlas "combines climate science, mapping, and storytelling together with Indigenous Knowledges and community-based research and video to inspire awareness and action".

  • Pacific Climate Impacts Consortium (PCIC)

    Based at the University of Victoria, PCIC is Canada's west coast regional climate centre and provides a comprehensive suite of meteorological and hydrologic data.

  • PAVICS

    Power Analytics and Visualization for Climate Science. Hosted by Ouranos, PAVICS provides a powerful virtual lab for processing and analysis of climate data.

  • ClimateData.ca

    The data portal of the Canadian Centre for Climate Services (CCCS).

The Need for High-resolution Data

While the above are of sufficient detail and quality for most applications, some adaptation plans and climate risk assessments require climate data of higher spatial and temporal resolution. Some climate impact assessments are based output from hydrological, geological and ecological models that require climate data at daily or sub-daily time scales and on a fine spatial grid.

Therefore, RCMs have become increasingly applied to regional climate impact and risk assessment (Giorgi et al., 2009). A RCM simulates the climate of a limited spatial domain (e.g., North America) on a fine grid (10 – 50 km). By reading output (boundary conditions) from a GCM, the RCM dynamically downscales the global simulation to a regional scale. This dynamical downscaling is especially advantageous in regions of complex topography, such as the Rocky Mountains, or for the simulation of processes, such as convective precipitation, at finer scales than a GCM grid.

The growing demand for regional climate projections is reflected in the 2019-2028 Strategic Plan of the World Climate Research Programme (WCRP) of the World Meteorological Organization. The WCRP intends to build stronger capability for ‘Bridging Climate Science and Society’ by providing a clear ‘entry point’ into WCRP activities including the Coordinated Regional Climate Downscaling Experiment (CORDEX).

Over the past decade, PARC’s research in climate risk assessment and adaptation planning has made increasing use of output from runs of RCMs. For example, during 2010-2017, the Climate Research Branch of Environment and Climate Change Canada funded PARC to develop high-resolution climate change projections for the Prairie Provinces using data derived from RCMs (Barrow and Sauchyn, 2017, 2019). With access to a cluster of supercomputers managed by the WestGrid regional partner of Compute Canada, we are running the National Center for Atmospheric Research (NCAR) Weather Research and Forecasting (WRF) model, which is widely used for regional climate studies. We also utilize RCM data from:

Our RCM Projects / Data in Action

Please click on the boxes below to see feature RCM projects.

Coming soon

Requesting RCM Data and Climate Modeling from PARC

PARC provides high-resolution climate projections and climate impact assessments to communities, private companies, government and non-governmental organizations, and as a cornerstone in our research. We are happy to discuss how we can assist with incorporating climate projections, interpretations, uncertainty or understanding into your projects.