Bayesian estimation of Earth’s climate sensitivity and transient climate response from observational warming and heat content datasets

Goodwin, Philip; Cael, B.B. ORCID: https://orcid.org/0000-0003-1317-5718. 2021 Bayesian estimation of Earth’s climate sensitivity and transient climate response from observational warming and heat content datasets. Earth System Dynamics. https://doi.org/10.5194/esd-2020-79

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Abstract/Summary

Future climate change projections, impacts and mitigation targets are directly affected by how sensitive Earth’s global mean surface temperature is to anthropogenic forcing, expressed via the effective climate sensitivity (ECS) and transient climate response (TCR). However, the ECS and TCR are poorly constrained, in part because historic observations and future climate projections consider the climate system under different response timescales with potentially different climate feedback strengths. Here, we evaluate ECS and TCR by using historic observations of surface warming, since the mid-19th century, and ocean heat uptake, since the mid 20th century, to constrain a model with independent climate feedback components acting over multiple response timescales. Adopting a Bayesian approach, our prior uses a constrained distribution for the instantaneous Planck feedback combined with wide-ranging uniform distributions of the strengths of the fast feedbacks (acting over several days) and slow feedbacks (acting over decades). We extract posterior distributions by applying likelihood functions derived from different combinations of observational datasets. The resulting TCR distributions are similar when using different historic datasets: from a TCR of 1.5 (1.3 to 1.7 at 5–95 % range) °C, up to 1.7 (1.4 to 2.0) °C. However, the posterior probability distribution for ECS on a 100-year response timescale varies depending on which combinations of temperature and heat content anomaly datasets are used: from ECS of 2.2 (1.5 to 4.5) °C, for datasets with less historic warming, up to 2.8 (1.8 to 6.1) °C, for datasets with more historic warming. Our results demonstrate how differences between historic climate reconstructions imply significant differences in expected future global warming.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.5194/esd-2020-79
ISSN:	21904979
Date made live:	02 Mar 2021 14:39 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/529803

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