CMIP6
1. Overview of CMIP6 Climate Scenarios
Purpose: Provides global climate projections based on state-of-the-art climate models.
Developed by: Program for Climate Model Diagnosis and Intercomparison (PCMDI)
Geographic Coverage: Global, with specific projections for Canada.
Time Coverage:
Historical data: 1900–2014
Future projections: 2015–2100
Resolution: 1° x 1° global grid (~110 km)
Emissions Scenarios (Shared Socioeconomic Pathways - SSPs):
SSP1-2.6 (Low emissions, strong mitigation - Paris Agreement target)
SSP2-4.5 (Intermediate stabilization pathway)
SSP3-7.0 (High-end emissions, fossil-fuel dominated)
SSP5-8.5 (Worst-case scenario, high fossil-fuel use and no mitigation)
Key Climate Variables Modeled
Variable
Unit
Projected Change Metrics
Mean Temperature
°C
Absolute temperature change
Precipitation
mm/day
% change relative to 1995-2014
Wind Speed
m/s
% change in wind intensity
Snow Depth
m
% change in snow accumulation
Sea Ice Thickness
m
Reduction in Arctic ice thickness
Sea Ice Concentration
%
% of grid cell covered by sea ice
2. CMIP6 Data and Processing
2.1 Data Collection and Interpolation
Data Source:
Monthly CMIP6 datasets downloaded from the Earth System Grid Federation (ESGF) database.
Data Format:
Processed in NetCDF format and interpolated to a common 1° x 1° global grid.
Ensemble Weighting:
Only one realization per model is included, giving each model equal weight.
2.2 Calculation of Climate Anomalies
Baseline Period: 1995-2014 (reference period for calculating anomalies).
Projected Anomalies: Future values minus the historical mean from 1995-2014.
Uncertainty Representation: Percentile projections (5th, 25th, 50th, 75th, 95th) to capture spread.
2.3 Future Time Periods Analyzed
2021-2040 (Near-term)
2041-2060 (Mid-century)
2061-2080 (Late 21st century)
2081-2100 (End-of-century)
3. List of Climate Models Used
The CMIP6 dataset includes over 30 global climate models, each contributing to the multi-model ensemble.
Model Name
Institution
CanESM5
Environment Canada
GFDL-CM4
NOAA-GFDL (USA)
HadGEM3-GC31-LL
UK Met Office
CESM2-WACCM
NCAR (USA)
IPSL-CM6A-LR
IPSL (France)
NorESM2-LM
Norwegian Climate Centre
MPI-ESM1-2-HR
MPI (Germany)
MIROC6
JAMSTEC (Japan)
BCC-CSM2-MR
Beijing Climate Center (China)
CMCC-CM2-SR5
CMCC (Italy)
(Full model list available in Table 2 of the CMIP6 documentation.)
4. Differences Between CMIP6 and CMIP5
Feature
CMIP5
CMIP6
Emission Pathways
RCPs (RCP2.6, RCP4.5, RCP8.5)
SSPs (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5)
Model Resolution
~1.5° to 2°
~1°
Historical Baseline
1986-2005
1995-2014
Ocean & Ice Modeling
Coarser resolution
Higher resolution, better sea-ice representation
Aerosols & Carbon Cycle
Simplified feedbacks
Interactive carbon cycle and aerosols
5. Applications of CMIP6 Data
CMIP6 data is widely used for climate impact assessments, adaptation planning, and policymaking.
5.1 Scientific Research & Climate Modeling
Studying regional temperature and precipitation changes.
Analyzing Arctic sea ice loss and ocean circulation shifts.
Modeling extreme weather patterns and climate variability.
5.2 Government Policy & Adaptation Planning
Guiding Canada’s climate adaptation strategies.
Providing data for IPCC AR6 assessments.
Developing resilient infrastructure based on projected climate risks.
5.3 Industry Applications
Energy Sector: Planning for hydropower variability and extreme weather risks.
Agriculture: Evaluating drought risk, heat stress, and precipitation trends.
Insurance & Risk Management: Assessing financial risks due to climate change.
6. Best Practices for Using CMIP6 Data
Use a multi-model approach to reduce bias and uncertainty.
Analyze different SSP scenarios to assess climate risks.
Focus on ensemble median and percentiles (5th-95th) rather than individual models.
Downscaling may be needed for localized impact studies.
Use Limitations
CMIP6 projections are not forecasts but scenario-based simulations.
Regional biases exist in some models, especially for precipitation.
Short-term weather variability (e.g., seasonal forecasts) requires additional data sources.
7. Future Considerations: Transition to CMIP7
CMIP7 is expected to further refine models, improve high-resolution projections, and update emission scenarios based on post-2025 climate policy trends.
Future enhancements will likely include improved cloud representation, aerosol interactions, and better simulation of extreme events.
8. Data Access & References
8.1 Where to Access CMIP6 Data
Environment Canada CMIP6 Portal:
PCMDI CMIP6 Archive:
Earth System Grid Federation (ESGF) Database:
9. Conclusion
The CMIP6 dataset represents the most advanced and comprehensive climate projection resource, supporting scientific research, government policy, and industry adaptation planning.
With higher-resolution models, improved physics, and new socio-economic pathways (SSPs), CMIP6 provides more accurate and actionable climate insights than its predecessor, CMIP5.
As climate science evolves, CMIP6 will play a critical role in guiding climate resilience efforts worldwide, supporting data-driven decision-making for a more sustainable future.
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