The CMIP6 multi-model ensembles technical documentation
This is the technical documentation for the multi-model ensembles of Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models (GCMs) provided on the Canadian Climate Data and Scenarios (CCDS) website. The documentation provides a description of the CMIP6 multi-model ensemble datasets, ensemble methodology, and a list of models included in the ensembles.
On this page
- Overview
- Data and processing
- Global gridded datasets
- Tabular datasets
- Map datasets and plots
- Time series datasets and plots
- List of models in ensembles
- Dataset licence
Overview
Climate projections vary across GCMs due to differences in the representation and approximation of earth systems and processes, and natural variability and uncertainty regarding future climate drivers. As a result, it is common practice to use a multi-model ensemble, or average across many GCMs, as opposed to using a single GCM in isolation. For this purpose, the Canadian Climate Data and Scenarios (CCDS) site has global and national multi-model ensembles for a suite of variables, scenarios, future time periods, and percentiles.
Provided on CCDS are four types of products based on the CMIP6 multi-model GCM ensembles regridded to a common 1x1 degree grid resolution: time series datasets and plots, maps and associated datasets, tabular datasets, and global gridded datasets. Results are available for six Shared Socioeconomic Pathways (SSPs), four future periods, and up to five percentiles of the CMIP6 ensemble distribution (see Table 1 for more details). Projected changes are expressed as anomalies according to a historical reference period of 1995-2014. Please see Table 1 for a description of the main characteristics of each product.
Table 1. The characteristics of products produced with the CMIP6 multi-model ensemble.
Variables and units |
Temperature: K for global gridded datasets, °C for all other datasets and products Precipitation: kg/m2/s for global gridded datasets, % change relative to the historical reference period for all other datasets and products |
Results |
Results expressed as anomalies (projected changes relative to a historical reference time period): time series datasets and plots, map datasets and plots, and tabular datasets Results expressed as raw (actual) values: global gridded datasets |
Geographic area |
Global: time series datasets, map datasets, and global gridded datasets Canada: time series and map plots, and tabular datasets Canadian provinces and territories: tabular datasets |
Spatial resolution |
1x1 degree grid resolution |
Temporal resolution |
Monthly, seasonal, and annual Seasons are defined using standard meteorological seasons:
|
Time period |
Historical reference period: 1995-2014 Historical simulation:
Future projections: Global gridded datasets and time series datasets and plots: 2015-2100 Map datasets and plots and tabular datasets: 20-year averages of projected change for four future time periods:
|
Percentiles |
Time series plots and tabular datasets: 25th, 50th (median), and 75th Map plots and datasets: 5th, 25th, 50th (median), 75th, and 95th Time series and global gridded datasets: none |
Emission scenarios |
SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-6.0, and SSP5-8.5 |
Data and processing
Data download and interpolation
Daily CMIP6 GCM datasets were downloaded from the Earth System Grid Federation (ESGF) online database in NetCDF format. Each model simulation was interpolated to a common 1x1 degree global grid prior to any analysis or processing using the Climate Data Operators (CDO) version 1.9.3 bilinear interpolation function (‘remapbil’). See Table 2 for a list of included models.
Programs and languages
CDO was used to calculate the CMIP6 multi-model ensemble statistics (functions: ‘ensmean’ or ‘enspctl’), time periods (functions: ‘timmean’, ‘selyear’, ‘yearmean’), and anomalies, while R version 4.1.0. was used to produce the time series and map plots as well as the tabular data. The number of models in each ensemble differ according to model availability for each SSP and variable. See Table 2 for additional details. All scripts were executed on a Unix system in a Bourne-again shell (bash) environment. Only one realization member from each model was included in the multi-model ensembles, giving each model equal weight.
Calculation of anomalies
Projected changes in climate are provided as anomalies according to a historical reference period of 1995-2014 for all anomaly datasets and products. Anomalies (n) are calculated by subtracting the mean over the historical reference period (µ) from original values at the time of interest (x) using the following expression:
Projected anomalies (n) for a future time period are calculated by subtracting the mean over the historical reference period (μ) from the mean of the projected values of the future time period (x) using the following expression:
Ensemble statistics, specifically the 5th, 25th, 50th (median), 75th, and 95th percentiles, are provided as a statistical measure to demonstrate some of the range of uncertainty across model projections. Percentiles for each SSP and time period were calculated with CDO function ‘enspctl’.
Global gridded datasets
Global gridded datasets are available at a monthly temporal time scale as raw (actual) values for the multi-model ensembles and for the individual CMIP6 models used to create the ensembles. Historical simulations (1850-2014) and model projections for the six SSPs (2015-2100) (when available) are available for download on the common 1x1 degree global grid. See Table 1 for additional product details and Table 2 for the ensemble model list.
Tabular datasets
Tabular datasets of future projected changes in temperature and precipitation are available for Canada and Canadian provinces and territories at annual and seasonal time scales. Tabular data are calculated with areal means based on a common 1x1 degree grid using land points. See Table 1 for additional product details and Table 2 for the ensemble model list.
Map datasets and plots
National maps of future projected changes in temperature and precipitation are available at annual and seasonal time scales. The associated anomaly datasets (global) are also available for download. See Table 1 for additional product details and Table 2 for the ensemble model list.
Time series datasets and plots
Time series plots are available for Canada at annual and seasonal time scales. The areal mean of the time series was computed on the common 1x1 degree grid using land points. The time series plots display the range of model simulations (i.e., model spread) extending from the historical time period (1900-2014) to future projected changes (2015-2100) for the six SSPs. See Table 1 for additional product details. The time series plots also incorporate boxplots that display the 25th, 50th (median), and 75th percentiles of model distribution for 2081-2100 for each SSP. Global time series datasets of the multi-model ensemble mean are also available for download. See Table 2 for the ensemble model list.
List of models in ensembles
Table 2. The list of the models included in the CMIP6 multi-model ensembles of temperature and precipitation for each SSP. The number of models used to compute the multi-model ensembles may differ for each SSP.
# | CMIP6 model name | Historical | SSP1-1.9 | SSP1-2.6 | SSP2-4.5 | SSP3-7.0 | SSP4-6.0 | SSP5-8.5 |
---|---|---|---|---|---|---|---|---|
1 | AWI-CM-1-1-MR | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
2 | BCC-CSM2-MR | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
3 | CAMS-CSM1-0 | Historical, Yes | SSP1-1.9, Yes | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
4 | CanESM5 | Historical, Yes | SSP1-1.9, Yes | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, Yes | SSP5-8.5, Yes |
5 | CESM2-WACCM | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
6 | CESM2 | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
7 | CIESM | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, No | SSP4-6.0, No | SSP5-8.5, Yes |
8 | CMCC-CM2-SR5 | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
9 | EC-Earth3-Veg | Historical, Yes | SSP1-1.9, Yes | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
10 | EC-Earth3 | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
11 | FGOALS-f3-L | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
12 | FGOALS-g3 | Historical, Yes | SSP1-1.9, Yes | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, Yes | SSP5-8.5, Yes |
13 | FIO-ESM-2-0 | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, No | SSP4-6.0, No | SSP5-8.5, Yes |
14 | GFDL-CM4 | Historical, Yes | SSP1-1.9, No | SSP1-2.6, No | SSP2-4.5, Yes | SSP3-7.0, No | SSP4-6.0, No | SSP5-8.5, Yes |
15 | GFDL-ESM4 | Historical, Yes | SSP1-1.9, Yes | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
16 | INM-CM4-8 | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
17 | INM-CM5-0 | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
18 | IPSL-CM6A-LR | Historical, Yes | SSP1-1.9, Yes | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, Yes | SSP5-8.5, Yes |
19 | KACE-1-0-G | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
20 | KIOST-ESM | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, No | SSP4-6.0, No | SSP5-8.5, Yes |
21 | MIROC6 | Historical, Yes | SSP1-1.9, Yes | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, Yes | SSP5-8.5, Yes |
22 | MPI-ESM1-2-HR | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
23 | MPI-ESM1-2-LR | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
24 | MRI-ESM2-0 | Historical, Yes | SSP1-1.9, Yes | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, Yes | SSP5-8.5, Yes |
25 | NESM3 | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, No | SSP4-6.0, No | SSP5-8.5, Yes |
26 | NorESM2-LM | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
27 | NorESM2-MM | Historical, Yes | SSP1-1.9, No | SSP1-2.6, Yes | SSP2-4.5, Yes | SSP3-7.0, Yes | SSP4-6.0, No | SSP5-8.5, Yes |
Number of models | Historical, 27 | SSP1-1.9, 8 | SSP1-2.6, 26 | SSP2-4.5, 27 | SSP3-7.0, 22 | SSP4-6.0, 5 | SSP5-8.5, 27 |
Dataset licence
Open Government Licence - Canada (http://open.canada.ca/en/open-government-licence-canada)
Individual model datasets and all related derived products, including the multi-model ensembles, are subject to the terms of use of the source organization.