Towards robust community assessments of the Earth's climate sensitivity

Abstract. The eventual planetary warming in response to elevated atmospheric carbon dioxide concentrations is not precisely known. The uncertainty in climate sensitivity (S) primarily results from uncertainties in net physical climate feedback, usually denoted as λ. Multiple lines of evidence can constrain this feedback parameter: proxy-based and model evidence from past equilibrium climates; process-based understanding of the physics underlying changes; and recent observations of temperature change, top-of-the-atmosphere energy imbalance, and ocean heat content. However, despite recent advances in combining these lines of evidence, the estimated range of S remains large. Here, using a Bayesian framework, we discuss three sources of uncertainty – uncertainty in the evidence, structural uncertainty in the model used to interpret this evidence, and differing prior knowledge and/or beliefs – and show how these affect the conclusions we may draw from a single line of evidence. We then propose strategies to combine multiple lines of evidence. We end with three recommendations. First, we suggest that a Bayesian random-effects meta-analysis be used to estimate the evidence and its uncertainty from the published literature. Second, we advocate that the organizers of future assessments clearly specify an interpretive model or a group of candidate models and, in the latter case, use Bayesian model averaging to more heavily weight models that best fit the evidence. Third, we recommend that expert judgment be incorporated via solicitations of priors on model parameters.

Authors

Institutions

Publication Details

Journal
Earth System Dynamics
Published
2025-02-26
DOI
https://doi.org/10.5194/esd-16-317-2025
Citations
1
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.11

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Towards robust community assessments of the Earth's climate sensitivity

Mark J. Webb, Kate Marvel
1 citations
Earth System Dynamics
Climate variability and models
1.11
article

Towards robust community assessments of the Earth's climate sensitivity

Mark J. Webb, Kate Marvel
article en
1 citations

Abstract

Abstract. The eventual planetary warming in response to elevated atmospheric carbon dioxide concentrations is not precisely known. The uncertainty in climate sensitivity (S) primarily results from uncertainties in net physical climate feedback, usually denoted as λ. Multiple lines of evidence can constrain this feedback parameter: proxy-based and model evidence from past equilibrium climates; process-based understanding of the physics underlying changes; and recent observations of temperature change, top-of-the-atmosphere energy imbalance, and ocean heat content. However, despite recent advances in combining these lines of evidence, the estimated range of S remains large. Here, using a Bayesian framework, we discuss three sources of uncertainty – uncertainty in the evidence, structural uncertainty in the model used to interpret this evidence, and differing prior knowledge and/or beliefs – and show how these affect the conclusions we may draw from a single line of evidence. We then propose strategies to combine multiple lines of evidence. We end with three recommendations. First, we suggest that a Bayesian random-effects meta-analysis be used to estimate the evidence and its uncertainty from the published literature. Second, we advocate that the organizers of future assessments clearly specify an interpretive model or a group of candidate models and, in the latter case, use Bayesian model averaging to more heavily weight models that best fit the evidence. Third, we recommend that expert judgment be incorporated via solicitations of priors on model parameters.

Earth System DynamicsVol. 16(1)
Goddard Institute for Space Studies (US), Met Office (GB)
National Aeronautics and Space Administration, Met Office
Openalex Percentile: Top 27%
Climate variability and models
1.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Towards robust community assessments of the Earth's climate sensitivity — Mark J. Webb, Kate Marvel · Earth System Dynamics (2025) | TGRS Research Map | TGRS