20 Oct 2020

20 Oct 2020

Review status: this preprint is currently under review for the journal ESD.

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

Philip Goodwin1 and B. B. Cael2 Philip Goodwin and B. B. Cael
  • 1School of Ocean and Earth Science, University of Southampton, SO13 3ZH, UK
  • 2National Oceanography Centre, Southampton, SO13 3ZH, UK

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 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.

Philip Goodwin and B. B. Cael

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Login for authors/editors] [Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Philip Goodwin and B. B. Cael

Model code and software

WASP-ESM/WASP_Earth_System_Model: WASP_ESM_v3.0 Philip Goodwin, BB Cael

Philip Goodwin and B. B. Cael


Total article views: 600 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
492 101 7 600 37 13 13
  • HTML: 492
  • PDF: 101
  • XML: 7
  • Total: 600
  • Supplement: 37
  • BibTeX: 13
  • EndNote: 13
Views and downloads (calculated since 20 Oct 2020)
Cumulative views and downloads (calculated since 20 Oct 2020)

Viewed (geographical distribution)

Total article views: 363 (including HTML, PDF, and XML) Thereof 362 with geography defined and 1 with unknown origin.
Country # Views %
  • 1
Latest update: 05 Mar 2021
Short summary
The `climate sensitivity' is a key measure of how sensitive Earth's climate is to human release of greenhouse gasses, such as from fossil fuels. However, there is still uncertainty in the value of the climate sensitivity, in part because different climate feedbacks operate over multiple timescales. This study assesses hundreds of millions of climate simulations against historical observations to reduce uncertainty in climate sensitivity and future climate warming.