CMIP5

1. Overview of CMIP5 Climate Scenarios

  • Purpose: Provides climate projections based on global climate models (GCMs).

  • Developed by: Program for Climate Model Diagnosis and Intercomparison (PCMDI)

  • Geographic Coverage: Global, with specific projections for Canada

  • Time Coverage:

    • Historical data: 1900–2005

    • Future projections: 2006–2100

  • Resolution: 1° x 1° global grid (~110 km)

  • Emissions Scenarios:

    • RCP2.6 (low emissions, aggressive mitigation)

    • RCP4.5 (moderate emissions stabilization)

    • RCP8.5 (high emissions, worst-case scenario)

Key Climate Variables Modeled

Variable

Unit

Projected Change Metrics

Mean Temperature

°C

Absolute temperature change

Precipitation

mm/day

% change relative to 1986-2005

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. Data and Processing

CMIP5 projections were compiled from 29 global climate models, each simulating future conditions under different greenhouse gas (GHG) emission pathways.

  • Data Source:

    • CMIP5 climate models archived at PCMDI (Program for Climate Model Diagnosis and Intercomparison).

  • Data Format:

    • Monthly, seasonal, and annual averages.

    • Multi-model ensemble approach used to improve reliability.

2.1 Multi-Model Ensemble Approach

  • Ensures robust climate projections by combining multiple GCMs.

  • Each model contributes one ensemble member (single realization).

  • Equal weighting assigned across models ("one model, one vote").

  • Percentiles provided (5th, 25th, 50th, 75th, 95th) to capture uncertainty.

2.2 Climate Projections (2021-2100)

  • Projected climate changes are expressed as "anomalies" relative to 1986-2005.

  • Four 20-year projection periods are analyzed:

    • 2021-2040

    • 2041-2060

    • 2061-2080

    • 2081-2100

2.3 Uncertainty Representation

  • Natural variability + model differences contribute to spread in projections.

  • Probability distribution given for projected changes.

  • Scenarios are not forecasts but "what-if" simulations based on different GHG pathways.

3. Reference Period & Baseline

  • All anomalies calculated relative to the 1986–2005 reference period.

  • This allows for direct comparison across different models and time periods.

  • Sea ice, snow depth, and wind speed projections extend from 1900-2100.

  • Temperature and precipitation data span 1901-2100.

4. List of Climate Models Used

The CMIP5 dataset includes simulations from 29 global climate models, each contributing to the ensemble.

Model Name

Institution

CanESM2

Environment Canada

GFDL-CM3

NOAA-GFDL (USA)

HadGEM2-ES

UK Met Office

CESM1-CAM5

NCAR (USA)

IPSL-CM5A-LR

IPSL (France)

NorESM1-M

Norwegian Climate Centre

MPI-ESM-LR

MPI (Germany)

MIROC5

JAMSTEC (Japan)

BCC-CSM1.1

Beijing Climate Center (China)

CSIRO-Mk3-6-0

CSIRO (Australia)

(Full list available in Table 2 of CMIP5 documentation.)

5. Best Practices for Using CMIP5 Data

  • Use a multi-model approach to account for uncertainty.

  • Analyze different RCP scenarios to understand potential future climate ranges.

  • Compare percentile projections (5th-95th) to assess variability.

  • Do not treat individual model outputs as predictions—focus on trends and ranges.

Use Limitations

  • CMIP5 projections are subject to model biases and uncertainty.

  • Local climate change impacts may require downscaling techniques.

  • Not suitable for short-term weather forecasting (focus is on climate trends).

6. Applications of CMIP5 Data

CMIP5 data is widely used in climate impact assessments, adaptation planning, and policy development.

6.1 Scientific Research & Climate Modeling

  • Understanding regional temperature and precipitation trends.

  • Studying Arctic sea ice decline and ocean circulation changes.

  • Evaluating changes in extreme weather events.

6.2 Government Policy & Adaptation Planning

  • Guiding national climate policies (e.g., Canada’s Net-Zero Strategy).

  • Providing data for IPCC climate assessment reports.

  • Developing climate resilience strategies for infrastructure.

6.3 Industry Applications

  • Energy sector: Planning for hydropower variability and energy demand shifts.

  • Agriculture: Evaluating drought risk, heat stress, and precipitation changes.

  • Insurance & Risk Management: Assessing climate-related financial risks.

7. Future Considerations: Transition to CMIP6

  • CMIP5 was superseded by CMIP6 (2020), which includes updated models and emissions scenarios.

  • CMIP6 provides improved representation of carbon cycle feedbacks and aerosol interactions.

  • However, CMIP5 remains valuable for long-term trend analysis and climate scenario comparisons.

8. Data Access & References

8.1 Where to Access CMIP5 Data

  • Environment Canada CMIP5 Portal:

    • Climate Model Data

  • PCMDI CMIP5 Archive:

    • PCMDI Website

  • IPCC Reports Based on CMIP5:

    • IPCC AR5 Climate Scenarios

9. Conclusion

The CMIP5 dataset remains one of the most widely used climate projection resources, supporting scientific research, government policy, and industry adaptation planning.

Its multi-model approach, emissions scenarios (RCP2.6, RCP4.5, RCP8.5), and probabilistic climate projections provide valuable insights into long-term temperature, precipitation, and extreme weather trends.

As climate science evolves, CMIP6 will eventually replace CMIP5, but CMIP5 data remains crucial for continuity in climate assessments and historical comparisons.

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