Observational estimate of climate sensitivity from changes in the rate of ocean heat uptake and comparison to CMIP5 models
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Climate sensitivity is estimated based on 0–2,000 m ocean heat content and surface temperature observations from the second half of the 20th century and first decade of the 21st century, using a simple energy balance model and the change in the rate of ocean heat uptake to determine the radiative restoration strength over this time period. The relationship between this 30–50 year radiative restoration strength and longer term effective sensitivity is investigated using an ensemble of 32 model configurations from the Coupled Model Intercomparison Project phase 5 (CMIP5), suggesting a strong correlation between the two. The mean radiative restoration strength over this period for the CMIP5 members examined is 1.16 Wm−2K−1, compared to 2.05 Wm−2K−1 from the observations. This suggests that temperature in these CMIP5 models may be too sensitive to perturbations in radiative forcing, although this depends on the actual magnitude of the anthropogenic aerosol forcing in the modern period. The potential change in the radiative restoration strength over longer timescales is also considered, resulting in a likely (67 %) range of 1.5–2.9 K for equilibrium climate sensitivity, and a 90 % confidence interval of 1.2–5.1 K.
KeywordsClimate sensitivity Ocean heat uptake CMIP model sensitivity Climate feedback
I would like to thank Geert Jan van Oldenborgh at KNMI for creating and maintaining the Climate Explorer website from which the CMIP5 members were retrieved (http://climexp.knmi.nl/) and aiding in the acquisition of this data. I also want to acknowledge Gavin Schmidt for comments on model drift, Urs Beyerle for help accessing the ETHZ CMIP5 sub-archive, Jonathan Gregory for information on CMIP5 run ancestry, and Catia Domingues for updates and comments on their latest UOHC data. Finally, I thank the two anonymous reviewers for helpful comments on this manuscript.
- Aldrin M, Holden M, Guttorp P, Skeie RB, Myhre G, Berntsen TK (2012) Bayesian estimation of climate sensitivity based on a simple climate model fitted to observations of hemispheric temperatures and global ocean heat content. Environmetrics 23(3):253–271. doi: 10.1002/env.2140 CrossRefGoogle Scholar
- Colman RA, Hanson LI (2012) On atmospheric radiative feedbacks associated with climate variability and change. Clim Dyn 40(1):475–492Google Scholar
- Forster P, Ramaswamy V, Artaxo P, Berntsen T, Betts R, Fahey DW, Haywood J, Lean J, Lowe DC, Myhre G, Nganga J, Prinn R, Raga G, Schulz M, Van Dorland R (2007) Changes in Atmospheric Constituents and in Radiative Forcing. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate Change 2007: The Physical Science Basis Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, CambridgeGoogle Scholar
- Hegerl GC, Zwiers FW, Braconnot P, Gillett NP, Luo Y, Marengo Orsini JA, Nicholls N, Penner JE, Stott PA (2007) Understanding and attributing climate change. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar