Abstract
Abstract. Climate model emulators have a crucial role in assessing warming levels of many emission scenarios from probabilistic climate projections based on new insights into Earth system response to CO2 and other forcing factors. This article describes one such tool, MCE, from model formulation to application examples associated with a recent model intercomparison study. The MCE is based on impulse response functions and parameterized physics of effective radiative forcing and carbon uptake over ocean and land. Perturbed model parameters for probabilistic projections are generated from statistical models and constrained with a Metropolis–Hastings independence sampler. Some of the model parameters associated with CO2-induced warming have a covariance structure, as diagnosed from complex climate models of the Coupled Model Intercomparison Project (CMIP). Perturbed ensembles can cover the diversity of CMIP models effectively, and they can be constrained to agree with several climate indicators such as historical warming. The model's simplicity and resulting successful calibration imply that a method with less complicated structures and fewer control parameters offers advantages when building reasonable perturbed ensembles in a transparent way. Experimental results for future scenarios show distinct differences between CMIP-consistent and observation-consistent ensembles, suggesting that perturbed ensembles for scenario assessment need to be properly constrained with new insights into forced response over historical periods.
Highlights
Climate model emulators, or simple climate models, are numerical tools for representing the complex Earth system in reduced dimensions using aggregated variables, such as global mean surface temperature (GMST) and global CO2 uptake over ocean and land
To demonstrate a typical application of the Minimal CMIP Emulator (MCE) model, a number of scenario experiments that mirror those of CMIP Phase 6 (CMIP6) were conducted, including idealized abrupt-4xCO2 and 1pctCO2, as well as historical–future scenarios based on the Shared Socioeconomic Pathways (SSPs; Riahi et al, 2017)
While the Prior distributions cover the Coupled Model Intercomparison Project (CMIP) atmosphere–ocean general circulation models (AOGCMs) effectively, the Constrained distributions are confined to lower sensitivity values – greater λ and smaller Transient climate response (TCR) and equilibrium climate sensitivity diagnosed from abrupt-4xCO2 (ECSG), which is attributed to the observed GMST and ocean heat content (OHC) constraints
Summary
Simple climate models, are numerical tools for representing the complex Earth system in reduced dimensions using aggregated variables, such as global mean surface temperature (GMST) and global CO2 uptake over ocean and land. Complex formulations are generally more capable of emulation, they are not necessarily advantageous for emulating individual CMIP models and representing their uncertainty ranges For thermal response, this has been confirmed by the author’s previous studies (Tsutsui, 2017, 2020), which have demonstrated that a simple IRM can accurately emulate a variety of CMIP models in terms of temperature response to CO2 forcing and provide a basis of parameter sampling that covers model diversity. This has been confirmed by the author’s previous studies (Tsutsui, 2017, 2020), which have demonstrated that a simple IRM can accurately emulate a variety of CMIP models in terms of temperature response to CO2 forcing and provide a basis of parameter sampling that covers model diversity These findings imply that less complex emulators are suitable for knowledge transfer in a transparent way.
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