Economics Research Seminar Series: Mengheng Li, UTS

Research topic: Constrain equilibrium climate sensitivity via Bayesian composite likelihood  

Mengheng Li, University of Technology Sydney 

Topic

Constrain equilibrium climate sensitivity via Bayesian composite likelihood  

abstract

The equilibrium climate sensitivity (ECS) is a pivotal parameter in climate science and other disciplines. This study estimates ECS as a common equilibrium parameter across energy balance models (EBMs). Fitting EBMs to the counter-factual data simulated from 31 climate models under a CO2 quadrupling experiment, we introduce a Bayesian composite likelihood approach to simultaneously integrate and estimate all the constituent EBMs. Complementing methods based on storylines and emergent constraints commonly employed by climate scientists, our econometric alternative provides a data-driven ECS estimator. We find an ECS estimate of 3.65K, characterized by a unimodal and right-skewed posterior distribution that facilitates uncertainty quantification. Our approach also yields a 95% credible interval of (2.5K, 5K), consistent with, yet tighter than and closer to the upper end of the “very likely” range of ECS reported by the IPCC.  

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