Abstract
Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state‐of‐the‐art knowledge in an internally self‐consistent modeling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain‐specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low‐emissions SSP1‐1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850–1900, using an observationally based historical warming estimate of 0.8°C between 1850–1900 and 1995–2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above preindustrial in the long‐term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.
Highlights
Coupled Earth System Models (ESMs) have evolved for decades as primary climate research tools (Kawamiya et al, 2020)
Our findings suggest that users of reduced complexity models (RCMs) should carefully evaluate their RCM, its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections
While we examine future projections coming from the models, we do not explicitly compare them against future projections coming from another line of evidence because there is no obvious choice for such a line of evidence—apart from the “assessed ranges” of shared socio-economic pathway (SSP) scenarios that will be communicated in the forthcoming Intergovernmental Panel on Climate Change (IPCC) report
Summary
Coupled Earth System Models (ESMs) have evolved for decades as primary climate research tools (Kawamiya et al, 2020). They represent the state of the art of complex Earth system modeling. They are not the tool of choice to assess the full breadth of scenario and Earth system response uncertainty that has been identified in the scientific literature. While some ESMs perform large, perturbed physics experiments (e.g., Murphy et al, 2014) that aim to explore a range of potential Earth system long-term annual-average responses, the ability to capture full uncertainty ranges is limited. The ability to capture full uncertainty ranges is limited because these ESMs are relatively rigid in their structure—lacking the ability to completely explore uncertainties in vital components like the carbon cycle or effective radiative forcings
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