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Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic
Z Nicholls1,2, M Meinshausen1,2,3, J Lewis1
1Australian-German Climate & Energy College University of Melbourne Parkville VIC Australia.
Earth'S Future
|July 5, 2021
Summary
Reduced complexity models (RCMs) are crucial for climate projections. Phase 2 of RCMIP shows that RCMs constrained by benchmarks better reflect climate realities, aiding efforts to limit global warming.
Area of Science:
- Climate Science
- Earth System Modeling
- Climate Change Research
Background:
- Climate science has advanced significantly, with Earth System Models (ESMs) as key tools.
- ESMs face computational limits and structural rigidity, hindering the capture of diverse uncertainties.
- Reduced Complexity Models (RCMs) offer computational efficiency and flexibility for spanning various climate dynamics.
Purpose of the Study:
- To present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2).
- To conduct the first comprehensive intercomparison of probabilistically calibrated RCMs.
- To assess RCM performance against key benchmark ranges from specialized research communities.
Main Methods:
- Probabilistic calibration of RCMs using benchmark ranges.
- Intercomparison of multiple RCMs under the SSP1-1.9 low-emissions scenario.
- Analysis of peak warming projections based on observational historical warming estimates.
Main Results:
- RCMs constrained by benchmarks demonstrate improved fidelity to those benchmarks.
- Median peak warming projections across RCMs under SSP1-1.9 range from 1.3 to 1.7°C.
- Historical warming estimate between 1850-1900 and 1995-2014 was 0.8°C.
Conclusions:
- Constraining RCMs with benchmarks is crucial for reliable climate projections.
- Further development of methodologies to constrain projection uncertainties is vital for meeting climate goals.
- Users of RCMs must evaluate model skill against benchmarks and consider incorporating diverse projection sources.
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