Multi-model ensemble scenarios

Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, there is no single best climate model. Rather, using results from an ensemble of models (e.g., taking the average) is best practice as an ensemble takes into account model uncertainty of model projections and provides more reliable climate projections.Reference 1Reference 2Reference 3Reference 4

The IPCC WGI Interactive Atlas provides multi-model ensemble results created from the latest generation of climate models for the world, divided into 58 regions. For application to Canadian impact studies and adaptation planning, the regional boundaries of the Atlas are less than optimal. Therefore, multi-model ensembles results specific to Canada are available here.

Best practice:

Given the range of natural climate variability and uncertainties regarding future greenhouse gas emission pathways and climate responses, changes projected by one climate model should not be used in isolation. Rather, it is good practice to consider a range of projections from multiple climate models (ensembles) and emission scenarios.

While probabilities are not associated with particular climate change scenarios, the use of a range of scenarios helps convey to users the extent of the range of potential outcomes as a result of different possible emission pathways.

CMIP6 multi-model ensemble on CCDS

The IPCC Sixth Assessment Report (AR6) provides results for a multi-model ensemble using CMIP6 models. Regional boundaries for Canada are divided into two main sections, North-Western North America (NWN) and North-Eastern North America (NEN). The NWN region encompases Alaksa, while the NEN region excludes much of Canada’s East coast. Both regions do not extend far enough south to include all of southern Canada, especially in the NEN region.

CCDS includes results from multi-model ensembles specific to Canada comprised of CMIP6 models. The data is available for historical simulations and six Shared Socioeconomic Pathways (SSPs): SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-6.0, and SSP5-8.5. The number of models in each ensemble differ according to model availability for each SSP and variable.

For more information on the models used in the CMIP6 ensemble, please see the technical notes.

CMIP5 multi-model ensemble on CCDS

A new feature as of the IPCC Fifth Assessment Report (AR5) is the Atlas of Global and Regional Climate Projections (Annex 1--IPCC, 2013), which provides a synthesis of results from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble.

For application to Canadian impact studies and adaptation planning, the regional boundaries of the Atlas are less than optimal: western Canada is combined with the western United States and Alaska, and eastern Canada is combined with Greenland and Iceland (but separated from western Canada).

Therefore, CCDS includes multi-model ensemble results generated specific to Canada, using output from 29 CMIP5 models from which results were available for historical simulations and three Representative Concentration Pathways (RCPs), RCP2.6, RCP4.5, and RCP8.5. Results for RCP6.0 are also available, but from fewer models, so this scenario is not included for multi-model results presented on CCDS.

For further details on the 29 models used in the CMIP5 ensemble, please see CMIP5 technical notes.

What are climate models?

Models of the Earth’s climate, often called global climate models (GCMs) or earth system models (ESMs), are fundamental tools for the global climate science community. Climate models are complex configurations of computer code constructed by scientists that specialize in a wide array of disciplines including mathematics, physics, chemistry, biochemistry, hydrology, and many more. These models are comprised of component sets of code that represent different parts of the climate system (atmosphere, ocean, land surface, ice, ecosystems, etc.) and are coupled together to simulate Earth’s climate. Climate models have been worked on and improved for decades and today’s models require some of the fastest supercomputers in the world to run.

Climate models are self-contained models of the climate system and therefore, the only input they need to run is information about changes in greenhouse gases and other climate drivers. This information is contained in scenarios representing a range of different assumptions about changes in climate drivers. The main purpose of a climate model is to project future climate system responses to input from a specified scenario. To this end, models are developed and tested using observational data and physical understanding to represent the essential features of the climate system and its response to changes in greenhouse gas amounts, land-use change, and other influences that lead to a changing climate. A model's performance is evaluated by measuring how close model simulations can come to historical observations of Earth’s climate under the influence of historical climate forcing. The ability of a climate model to recreate the past to a reasonable degree provides confidence in its ability to project future climate change.

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