Bayesian estimation of Earth's climate sensitivity and transient climate response from observational warming and heat content datasets
Bayesian estimation of Earth's climate sensitivity and transient climate response from observational warming and heat content datasets
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 climate sensitivity (S) and transient climate response (TCR). However, the S 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 S and TCR by using historic observations of surface warming, available since the mid-19th century, and ocean heat uptake, available 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 multi-decadal feedbacks. We extract posterior distributions by applying likelihood functions derived from different combinations of observational datasets. The resulting TCR distributions when using two preferred combinations of historic datasets both find a TCR of 1.5 (1.3 to 1.8 at 5-95g % range)g g C. We find the posterior probability distribution for S for our preferred dataset combination evolves from S of 2.0 (1.6 to 2.5)g g C on a 20-year response timescale to S of 2.3 (1.4 to 6.4)g g C on a 140-year response timescale, due to the impact of multi-decadal feedbacks. Our results demonstrate how multi-decadal feedbacks allow a significantly higher upper bound on S than historic observations are otherwise consistent with.
709-723
Goodwin, Philip
87dbb154-5c39-473a-8121-c794487ee1fd
Cael, B. B.
458442c7-574e-42dd-b2aa-717277e14eba
17 June 2021
Goodwin, Philip
87dbb154-5c39-473a-8121-c794487ee1fd
Cael, B. B.
458442c7-574e-42dd-b2aa-717277e14eba
Goodwin, Philip and Cael, B. B.
(2021)
Bayesian estimation of Earth's climate sensitivity and transient climate response from observational warming and heat content datasets.
Earth System Dynamics, 12 (2), .
(doi:10.5194/esd-12-709-2021).
Abstract
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 climate sensitivity (S) and transient climate response (TCR). However, the S 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 S and TCR by using historic observations of surface warming, available since the mid-19th century, and ocean heat uptake, available 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 multi-decadal feedbacks. We extract posterior distributions by applying likelihood functions derived from different combinations of observational datasets. The resulting TCR distributions when using two preferred combinations of historic datasets both find a TCR of 1.5 (1.3 to 1.8 at 5-95g % range)g g C. We find the posterior probability distribution for S for our preferred dataset combination evolves from S of 2.0 (1.6 to 2.5)g g C on a 20-year response timescale to S of 2.3 (1.4 to 6.4)g g C on a 140-year response timescale, due to the impact of multi-decadal feedbacks. Our results demonstrate how multi-decadal feedbacks allow a significantly higher upper bound on S than historic observations are otherwise consistent with.
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esd-12-709-2021
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Accepted/In Press date: 18 May 2021
Published date: 17 June 2021
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Funding Information:
Financial support. This research has been supported by the UK Research and Innovation (grant nos. NE/T010657/1 and NE/315R015953/1) and the Horizon 2020 (COMFORT project, grant no. 820989).
Funding Information:
Acknowledgements. Philip Goodwin acknowledges support from UKRI Natural Environmental Research Council grant NE/T010657/1. The authors acknowledge the use of the IRIDIS High Performance Computing Facility and associated support services at the University of Southampton in the completion of this work. B. B. Cael acknowledges support from the National Environmental Research Council (NE/315R015953/1) and the Horizon 2020 Framework Programme (820989, project COMFORT). The work reflects only the authors’ views; the European Commission and their executive agency are not responsible for any use that may be made of the information the work contains.
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Copyright 2021 Elsevier B.V., All rights reserved.
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Local EPrints ID: 449953
URI: http://eprints.soton.ac.uk/id/eprint/449953
ISSN: 2190-4979
PURE UUID: ac0dd239-d516-406c-9fb0-2c0ba3f269a8
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Date deposited: 29 Jun 2021 16:36
Last modified: 17 Mar 2024 03:32
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B. B. Cael
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