Skip to main content

Observational estimate of climate sensitivity from changes in the rate of ocean heat uptake and comparison to CMIP5 models

Abstract

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.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  1. 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

    Article  Google Scholar 

  2. Andrews T, Gregory JM, Webb MJ, Taylor KE (2012) Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models. Geophys Res Lett 39(9):L09712

    Article  Google Scholar 

  3. Annan JD, Hargreaves JC (2006) Using multiple observationally-based constraints to estimate climate sensitivity. Geophys Res Lett 33(6):L06704

    Article  Google Scholar 

  4. Armour KC, Bitz CM, Roe GH (2012) Time-varying climate sensitivity from regional feedbacks. J Clim. doi:10.1175/JCLI-D-12-00544.1

    Google Scholar 

  5. Church JA, White NJ, Konikow LF, Domingues CM, Cogley JG, Rignot E, Gregory JM, van den Broeke MR, Monaghan AJ, Velicogna I (2011) Revisiting the Earth’s sea-level and energy budgets from 1961 to 2008. Geophys Res Lett 38:L18601. doi:10.1029/2011GL048794

    Article  Google Scholar 

  6. Colman RA, Hanson LI (2012) On atmospheric radiative feedbacks associated with climate variability and change. Clim Dyn 40(1):475–492

    Google Scholar 

  7. Domingues CM, Church JA, White NJ, Gleckler PJ, Wijffels SE, Barker PM, Dunn JR (2008) Improved estimates of upper-ocean warming and multi-decadal sea-level rise. Nature 453(7198):1090–1093

    Article  Google Scholar 

  8. Edwards TL, Crucifix M, Harrison SP (2007) Using the past to constrain the future: how the palaeorecord can improve estimates of global warming. Prog Phys Geogr 31(5):481–500

    Article  Google Scholar 

  9. 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, Cambridge

    Google Scholar 

  10. Forster PMF, Gregory JM (2006) The climate sensitivity and its components diagnosed from Earth radiation budget data. J Clim 19(1):39–52

    Article  Google Scholar 

  11. Gregory JM, Stouffer RJ, Raper SCB, Stott PA, Rayner NA (2002) An observationally based estimate of the climate sensitivity. J Clim 15(22):3117–3121

    Article  Google Scholar 

  12. Hansen J, Sato M, Ruedy R, Kharecha P, Lacis A, Miller et al (2007) Climate simulations for 1880–2003 with GISS modelE. Clim Dyn 29(7):661–696

    Article  Google Scholar 

  13. Hansen J, Ruedy R, Sato M, Lo K (2010) Global surface temperature change. Rev Geophys 48:RG4004. doi:10.1029/2010RG000345

    Article  Google Scholar 

  14. 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, Cambridge

    Google Scholar 

  15. Held IM, Winton M, Takahashi K, Delworth T, Zeng F, Vallis GK (2010) Probing the fast and slow components of global warming by returning abruptly to preindustrial forcing. J Clim 23(9):2418–2427

    Article  Google Scholar 

  16. Ishii M, Kimoto M (2009) Reevaluation of historical ocean heat content variations with time-varying XBT and MBT depth bias corrections. J Oceanogr 65(3):287–299

    Article  Google Scholar 

  17. Jones PD, Lister DH, Osborn TJ, Harpham C, Salmon M, Morice CP (2012) Hemispheric and large-scale land-surface air temperature variations: an extensive revision and an update to 2010. J Geophys Res 117:D05127. doi:10.1029/2011JD017139

    Google Scholar 

  18. Knutti R, Hegerl GC (2008) The equilibrium sensitivity of the Earth’s temperature to radiation changes. Nat Geosci 1(11):735–743

    Article  Google Scholar 

  19. Levitus S et al (2012) World ocean heat content and thermosteric sea level change (0–2,000 m), 1955–2010. Geophys Res Lett 39:L10603. doi:10.1029/2012GL051106

    Article  Google Scholar 

  20. Lin B, Chambers L, Stackhouse P Jr, Wielicki B, Hu Y, Minnis P et al (2010) Estimations of climate sensitivity based on top-of-atmosphere radiation imbalance. Atmos Chem Phys 10:1923–1930

    Article  Google Scholar 

  21. Lin B, Min Q, Sun W, Hu Y, Fan TF (2011) Can climate sensitivity be estimated from short-term relationships of top-of-atmosphere net radiation and surface temperature? J Quant Spectrosc Radiat Transfer 112(2):177–181

    Article  Google Scholar 

  22. Lindzen RS, Choi YS (2011) On the observational determination of climate sensitivity and its implications. Asia-Pacific J Atmos Sci 47(4):377–390

    Article  Google Scholar 

  23. Loeb NG, Lyman JM, Johnson GC, Allan RP, Doelling DR, Wong T et al (2012) Observed changes in top-of-the-atmosphere radiation and upper-ocean heating consistent within uncertainty. Nat Geosci 5(2):110–113

    Article  Google Scholar 

  24. Mascioli NR, Canty T, Salawitch RJ (2012) An empirical model of global climate-part 2: implications for future temperature. Atmos Chem Phys Discuss 12:23913–23974. doi:10.5194/acpd-12-23913-2012

    Article  Google Scholar 

  25. Murphy JM, Sexton DM, Barnett DN, Jones GS, Webb MJ, Collins M, Stainforth DA (2004) Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature 430(7001):768–772

    Article  Google Scholar 

  26. Murphy DM, Solomon S, Portmann RW, Rosenlof KH, Forster PM, Wong T (2009) An observationally based energy balance for the Earth since 1950. J Geophys Res 114(D17):D17107

    Article  Google Scholar 

  27. Schwartz SE (2012) Determination of Earth’s transient and equilibrium climate sensitivities from observations over the twentieth century: strong dependence on assumed forcing. Surveys Geophys 33:745–777. doi:10.1007/s10712-012-9180-4

    Article  Google Scholar 

  28. Shindell DT, Lamarque JF, Schulz M, Flanner M, Jiao C, Chin M, Yoon JH (2012) Radiative forcing in the ACCMIP historical and future climate simulations. Atmos Chem and Phys Discuss 12:21105–21210

    Article  Google Scholar 

  29. Smith TM, Reynolds RW, Peterson TC, Lawrimore J (2008) Improvements to NOAA’s historical merged land-ocean surface temperature analysis (1880–2006). J Clim 21:2283–2293. doi:10.1175/2007JCLI2100.1

    Article  Google Scholar 

  30. Soden BJ, Held IM (2006) An assessment of climate feedbacks in coupled ocean-atmosphere models. J Clim 19(14):3354–3360

    Article  Google Scholar 

  31. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 90:485–498. doi:10.1175/BAMS-D-11-00094.1

    Article  Google Scholar 

  32. Van Oldenborgh GJ, Drijfhout S, Van Ulden A, Haarsma RJ, Sterl A, Severijns C, Dijkstra HA (2009) Western Europe is warming much faster than expected. Climate of the Past 5(1):1–12

    Article  Google Scholar 

  33. Winton M, Takahashi K, Held IM (2010) Importance of ocean heat uptake efficacy to transient climate change. J Clim 23(9):2333–2344

    Article  Google Scholar 

Download references

Acknowledgments

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.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Troy Masters.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Masters, T. Observational estimate of climate sensitivity from changes in the rate of ocean heat uptake and comparison to CMIP5 models. Clim Dyn 42, 2173–2181 (2014). https://doi.org/10.1007/s00382-013-1770-4

Download citation

Keywords

  • Climate sensitivity
  • Ocean heat uptake
  • CMIP model sensitivity
  • Climate feedback