# 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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