1932

Abstract

Recent attempts to diagnose equilibrium climate sensitivity (ECS) from changes in Earth's energy budget point toward values at the low end of the Intergovernmental Panel on Climate Change Fifth Assessment Report (AR5)'s likely range (1.5–4.5 K). These studies employ observations but still require an element of modeling to infer ECS. Their diagnosed effective ECS over the historical period of around 2 K holds up to scrutiny, but there is tentative evidence that this underestimates the true ECS from a doubling of carbon dioxide. Different choices of energy imbalance data explain most of the difference between published best estimates, and effective radiative forcing dominates the overall uncertainty. For decadal analyses the largest source of uncertainty comes from a poor understanding of the relationship between ECS and decadal feedback. Considerable progress could be made by diagnosing effective radiative forcing in models.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-earth-060614-105156
2016-06-29
2024-04-14
Loading full text...

Full text loading...

/deliver/fulltext/earth/44/1/annurev-earth-060614-105156.html?itemId=/content/journals/10.1146/annurev-earth-060614-105156&mimeType=html&fmt=ahah

Literature Cited

  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 23:253–71 [Google Scholar]
  2. Andrews T, Forster PM, Boucher O, Bellouin N, Jones A. 2010. Precipitation, radiative forcing and global temperature change. Geophys. Res. Lett. 37:L14701 [Google Scholar]
  3. Andrews T, Gregory JM, Webb MJ. 2014. The dependence of radiative forcing and feedback on evolving patterns of surface temperature change in climate models. J. Clim. 28:1630–48 [Google Scholar]
  4. 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:L09712 [Google Scholar]
  5. Andronova NG, Schlesinger ME. 2001. Objective estimation of the probability density function for climate sensitivity. J. Geophys. Res. 106:D1922605–11 [Google Scholar]
  6. Armour KC, Bitz CM, Roe GH. 2013. Time-varying climate sensitivity from regional feedbacks. J. Clim. 26:4518–34 [Google Scholar]
  7. Arrhenius S. 1896. On the influence of carbonic acid in the air upon temperature of the ground. Philos. Mag. J. Sci. 41:237–76 [Google Scholar]
  8. Balmaseda MA, Trenberth KE, Källén E. 2013. Distinctive climate signals in reanalysis of global ocean heat content. Geophys. Res. Lett. 40:1754–59 [Google Scholar]
  9. Bengtsson L, Schwartz SE. 2013. Determination of a lower bound on Earth's climate sensitivity. Tellus B 65:21533 [Google Scholar]
  10. Bindoff NL, Stott PA, AchutaRao KM, Allen MR, Gillett N. et al. 2013. Detection and attribution of change: from global to regional. See Stocker et al. 2013 867–952
  11. Bloch-Johnson J, Pierrehumbert RT, Abbot DS. 2015. Feedback temperature dependence determines the risk of high warming. Geophys. Res. Lett. 42:4973–80 [Google Scholar]
  12. Block K, Mauritsen T. 2013. Forcing and feedback in the MPI-ESM-LR coupled model under abruptly quadrupled CO2. J. Adv. Model. Earth Syst. 5:676–91 [Google Scholar]
  13. Bond TC, Doherty SJ, Fahey DW, Forster PM, Berntsen T. et al. 2013. Bounding the role of black carbon in the climate system: a scientific assessment. J. Geophys. Res. Atmos. 118:5380–552 [Google Scholar]
  14. Boucher O, Randall D, Artaxo P, Bretherton C, Feingold G. et al. 2013. Clouds and aerosols. See Stocker et al. 2013 571–658
  15. Caballero R, Huber M. 2013. State-dependent climate sensitivity in past warm climates and its implications for future climate projections. PNAS 110:14162–67 [Google Scholar]
  16. Charney JG, Arakawa A, Baker DJ, Bolin B, Dickinson RE. et al. 1979. Carbon Dioxide and Climate: A Scientific Assessment Washington, DC: Natl. Acad. Sci.
  17. Chung ES, Soden BJ, Sohn BJ. 2010. Revisiting the determination of climate sensitivity from relationships between surface temperature and radiative fluxes. Geophys. Res. Lett. 37:L10703 [Google Scholar]
  18. Church JA, Clark PU, Cazenave A, Gregory JM, Jevrejeva S. et al. 2013. Sea level change. See Stocker et al. 2013 1137–216
  19. Collins M, Knutti R, Arblaster J, Dufresne JL, Fichefet T. et al. 2013. Long-term climate change: projections, commitments and irreversibility. See Stocker et al. 2013 1029–136
  20. Colman RA, Power SB. 2010. Atmospheric radiative feedbacks associated with transient climate change and climate variability. Clim. Dyn. 34:919–33 [Google Scholar]
  21. Cowtan K, Way RG. 2014. Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends. Q. J. R. Meteorol. Soc. 140:1935–44 [Google Scholar]
  22. Crook JA, Forster PM, Stuber N. 2011. Spatial patterns of modeled climate feedback and contributions to temperature response and polar amplification. J. Clim. 24:3575–92 [Google Scholar]
  23. Dessler AE. 2011. Cloud variations and the Earth's energy budget. Geophys. Res. Lett. 38:L19701 [Google Scholar]
  24. Dessler AE. 2013. Observations of climate feedbacks over 2000–10 and comparisons to climate models. J. Clim. 26:333–42 [Google Scholar]
  25. Domingues CM, Church JA, White NJ, Gleckler PJ, Wijffels SE. et al. 2008. Improved estimates of upper-ocean warming and multi-decadal sea-level rise. Nature 453:1090–93 [Google Scholar]
  26. Donohoe A, Armour KC, Pendergrass AG, Battisti DS. 2014. Shortwave and longwave radiative contributions to global warming under increasing CO2. PNAS 111:16700–5 [Google Scholar]
  27. Flato G, Marotzke J, Abiodun B, Braconnot P, Chou SC. et al. 2013. Evaluation of climate models. See Stocker et al. 2013 741–866
  28. Forest CE, Stone PH, Sokolov AP. 2006. Estimated PDFs of climate system properties including natural and anthropogenic forcings. Geophys. Res. Lett. 33:L01705 [Google Scholar]
  29. Forster PM, Andrews T, Good P, Gregory JM, Jackson LS, Zelinka M. 2013. Evaluating adjusted forcing and model spread for historical and future scenarios in the CMIP5 generation of climate models. J. Geophys. Res. Atmos. 118:1139–50 [Google Scholar]
  30. Forster PM, Gregory JM. 2006. The climate sensitivity and its components diagnosed from Earth Radiation Budget data. J. Clim. 19:39–52 [Google Scholar]
  31. Forster PM, Ramaswamy V, Artaxo P, Berntsen T, Betts R. et al. 2007. Changes in atmospheric constituents and in radiative forcing. See Solomon et al. 2007 129–234
  32. Forster PM, Taylor KE. 2006. Climate forcings and climate sensitivities diagnosed from coupled climate model integration. J. Clim. 19:6181–94 [Google Scholar]
  33. Fourier JBJ. 1827. Mémoire sur les températures du globe terrestre et des espaces planétaires. Mem. Acad. R. Sci. Inst. Fr. 7:569–604 [Google Scholar]
  34. Frame DJ, Booth BBB, Kettleborough JA, Stainforth DA, Gregory JM. et al. 2005. Constraining climate forecasts: the role of prior assumptions. Geophys. Res. Lett. 32:L09702 [Google Scholar]
  35. Geoffroy O, Saint-Martin D, Bellon G, Voldoire A, Olivié DJL, Tytéca S. 2013. Transient climate response in a two-layer energy-balance model. Part II. Representation of the efficacy of deep-ocean heat uptake and validation for CMIP5 AOGCMs. J. Clim. 26:1859–76 [Google Scholar]
  36. Gordon ND, Jonko AK, Forster PM, Shell KM. 2013. An observationally based constraint on the water-vapor feedback. J. Geophys. Res. Atmos. 118:12435–43 [Google Scholar]
  37. Gregory J, Andrews T, Good P, Mauritsen T, Forster P. 2016. Small global-mean cooling due to volcanic radiative forcing. Clim. Dyn. doi: 10.1007/s00382-016-3055-1
  38. Gregory JM, Stouffer RJ, Raper SCB, Stott PA, Rayner NA. 2002. An observationally based estimate of the climate sensitivity. J. Clim. 15:3117–21 [Google Scholar]
  39. Hansen J, Sato M, Ruedy R, Kharecha P, Lacis A. et al. 2007. Climate simulations for 1880–2003 with GISS modelE. Clim. Dyn. 29:661–96 [Google Scholar]
  40. Hansen J, Sato M, Ruedy R, Nazarenko L, Lacis A. et al. 2005. Efficacy of climate forcings. J. Geophys. Res. 110:D18104 [Google Scholar]
  41. Hartmann DL, Klein Tank AMG, Rusticucci M, Alexander LV, Brönnimann S. et al. 2013. Observations: atmosphere and surface. See Stocker et al. 2013 159–254
  42. Hegerl GC, Zwiers FW, Braconnot P, Gillett NP, Luo Y. et al. 2007. Understanding and attributing climate change. See Solomon et al. 2007 664–745
  43. Johansson DJA, O'Neill BC, Tebaldi C, Haggstrom O. 2015. Equilibrium climate sensitivity in light of observations over the warming hiatus. Nat. Clim. Change 5:449–53 [Google Scholar]
  44. Karl TR, Arguez A, Huang B, Lawrimore JH, McMahon JR. et al. 2015. Possible artifacts of data biases in the recent global surface warming hiatus. Science 348:1469–72 [Google Scholar]
  45. Knutti R, Stocker TF, Joos F, Plattner GK. 2002. Constraints on radiative forcing and future climate change from observations and climate model ensembles. Nature 416:719–23 [Google Scholar]
  46. Koll DDB, Abbot DS. 2013. Why tropical sea surface temperature is insensitive to ocean heat transport changes. J. Clim. 26:6742–49 [Google Scholar]
  47. Kummer JR, Dessler AE. 2014. The impact of forcing efficacy on the equilibrium climate sensitivity. Geophys. Res. Lett. 41:3565–68 [Google Scholar]
  48. Levitus S, Antonov JI, Boyer TP, Baranova OK, Garcia HE. et al. 2012. World ocean heat content and thermosteric sea level change (0–2000 m), 1955–2010. Geophys. Res. Lett. 39:L10603 [Google Scholar]
  49. Lewis N. 2013. An objective Bayesian improved approach for applying optimal fingerprint techniques to estimate climate sensitivity. J. Clim. 26:7414–29 [Google Scholar]
  50. Lewis N. 2016. Implications of recent multimodel attribution studies for climate sensitivity. Clim. Dyn. 46:1387–96
  51. Lewis N, Curry J. 2014. The implications for climate sensitivity of AR5 forcing and heat uptake estimates. Clim. Dyn. 45:1009–23 [Google Scholar]
  52. Lin B, Chambers L, Stackhouse P Jr., Wielicki B, Hu Y. et al. 2010. Estimations of climate sensitivity based on top-of-atmosphere radiation imbalance. Atmos. Chem. Phys. 10:1923–30 [Google Scholar]
  53. Lindzen RS, Choi YS. 2009. On the determination of climate feedbacks from ERBE data. Geophys. Res. Lett. 36:L16705 [Google Scholar]
  54. Lindzen RS, Choi YS. 2011. On the observational determination of climate sensitivity and its implications. Asia-Pac. J. Atmos. Sci. 47:377–90 [Google Scholar]
  55. Loeb NG, Lyman JM, Johnson GC, Allan RP, Doelling DR. et al. 2012. Observed changes in top-of-the-atmosphere radiation and upper-ocean heating consistent within uncertainty. Nat. Geosci. 5:110–13 [Google Scholar]
  56. Loeb NG, Wielicki BA, Doelling DR, Smith GL, Keyes DF. et al. 2009. Toward optimal closure of the Earth's top-of-atmosphere radiation budget. J. Clim. 22:748–66 [Google Scholar]
  57. Manabe S, Wetherald RT. 1967. Thermal equilibrium of the atmosphere with a given distribution of relative humidity. J. Atmos. Sci. 24:241–59 [Google Scholar]
  58. Marvel K, Schmidt GA, Miller RL, Nazarenko LS. 2016. Implications for climate sensitivity from the response to individual forcings. Nat. Clim. Change 6386–89
  59. Masters T. 2014. Observational estimate of climate sensitivity from changes in the rate of ocean heat uptake and comparison to CMIP5 models. Clim. Dyn. 42:2173–81 [Google Scholar]
  60. Meraner K, Mauritsen T, Voigt A. 2013. Robust increase in equilibrium climate sensitivity under global warming. Geophys. Res. Lett. 40:5944–48 [Google Scholar]
  61. Merlis TM, Held IM, Stenchikov GL, Zeng F, Horowitz LW. 2014. Constraining transient climate sensitivity using coupled climate model simulations of volcanic eruptions. J. Clim. 27:7781–95 [Google Scholar]
  62. Morice CP, Kennedy JJ, Rayner NA, Jones PD. 2012. Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: the HadCRUT4 data set. J. Geophys. Res. 117:D08101 [Google Scholar]
  63. Murphy DM. 2010. Constraining climate sensitivity with linear fits to outgoing radiation. Geophys. Res. Lett. 37:L09704 [Google Scholar]
  64. Murphy DM, Forster PM. 2010. On the accuracy of deriving climate feedback parameters from correlations between surface temperature and outgoing radiation. J. Clim. 23:4983–88 [Google Scholar]
  65. 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:D17107 [Google Scholar]
  66. Myhre G, Shindell D, Bréon FM, Collins W, Fuglestvedt J. et al. 2013. Anthropogenic and natural radiative forcing. See Stocker et al. 2013 659–740
  67. Otto A, Otto FEL, Boucher O, Church J, Hegerl G. et al. 2013. Energy budget constraints on climate response. Nat. Geosci. 6:415–16 [Google Scholar]
  68. Ramanathan V, Cess RD, Harrison EF, Minnis P, Barkstrom BR. et al. 1989. Cloud-radiative forcing and climate: results from the Earth Radiation Budget Experiment. Science 243:57–63 [Google Scholar]
  69. Rhein M, Rintoul SR, Aoki S, Campos E, Chambers D. et al. 2013. Observations: ocean. See Stocker et al. 2013 255–316
  70. Roe GH, Armour KC. 2011. How sensitive is climate sensitivity?. Geophys. Res. Lett. 38:L14708 [Google Scholar]
  71. Rose BEJ, Armour KC, Battisti DS, Feldl N, Koll DDB. 2014. The dependence of transient climate sensitivity and radiative feedbacks on the spatial pattern of ocean heat uptake. Geophys. Res. Lett. 41:1071–78 [Google Scholar]
  72. Schwartz SE. 2007. Heat capacity, time constant, and sensitivity of Earth's climate system. J. Geophys. Res. 112:D24S05 [Google Scholar]
  73. Schwartz SE. 2012. Determination of Earth's transient and equilibrium climate sensitivities from observations over the twentieth century: strong dependence on assumed forcing. Surv. Geophys. 33:745–77 [Google Scholar]
  74. Sherwood SC, Bony S, Boucher O, Bretherton C, Forster PM. et al. 2015. Adjustments in the forcing feedback framework for understanding climate change. Bull. Am. Meteorol. Soc. 96:217–28 [Google Scholar]
  75. Sherwood SC, Bony S, Dufresne JL. 2014. Spread in model climate sensitivity traced to atmospheric convective mixing. Nature 505:37–42 [Google Scholar]
  76. Shindell DT. 2014. Inhomogeneous forcing and transient climate sensitivity. Nat. Clim. Change 4:274–77 [Google Scholar]
  77. Shindell DT, Faluvegi G, Rotstayn L, Milly G. 2015. Spatial patterns of radiative forcing and surface temperature response. J. Geophys. Res. Atmos. 120:5385–403 [Google Scholar]
  78. Skeie RB, Berntsen T, Aldrin M, Holden M, Myhre G. 2014. A lower and more constrained estimate of climate sensitivity using updated observations and detailed radiative forcing time series. Earth Syst. Dyn. 5:139–75 [Google Scholar]
  79. Soden BJ, Held IM. 2006. An assessment of climate feedbacks in coupled ocean-atmosphere models. J. Clim. 19:3354–60 [Google Scholar]
  80. Solomon S, Qin D, Manning M, Chen Z, Marquis M. et al. 2007. 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, UK: Cambridge Univ. Press
  81. Spencer RW, Braswell WD. 2008. Potential biases in feedback diagnosis from observational data: a simple model demonstration. J. Clim. 21:5624–28 [Google Scholar]
  82. Stefan J. 1879. Über die Beziehung zwischen der Wärmestrahlung und der Temperatur. Sitz. Math. Naturwiss. Cl. Kais. Akad. Wiss. 1:391–428 [Google Scholar]
  83. Stevens B. 2015. Rethinking the lower bound on aerosol radiative forcing. J. Clim. 28:4794–819 [Google Scholar]
  84. Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK. et al. 2013. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Cambridge, UK: Cambridge Univ. Press
  85. Trenberth KE, Fasullo JT, O'Dell C, Wong T. 2010. Relationships between tropical sea surface temperature and top-of-atmosphere radiation. Geophys. Res. Lett. 37:L03702 [Google Scholar]
  86. Trenberth KE, Zhang Y, Fasullo JT, Taguchi S. 2015. Climate variability and relationships between top-of-atmosphere radiation and temperatures on Earth. J. Geophys. Res. Atmos. 120:3642–59 [Google Scholar]
  87. Tsushima Y, Abe-Ouchi A, Manabe S. 2005. Radiative damping of annual variation in global mean surface temperature: comparison between observed and simulated feedback. Clim. Dyn. 24:591–97 [Google Scholar]
  88. Tsushima Y, Manabe S. 2013. Assessment of radiative feedback in climate models using satellite observations of annual flux variation. PNAS 110:7568–73 [Google Scholar]
  89. Tyndall J. 1861. The Bakerian Lecture: on the absorption and radiation of heat by gases and vapours, and on the physical connexion of radiation, absorption, and conduction. Philos. Trans. R. Soc. 151:1–36 [Google Scholar]
  90. Wigley TML, Jones PD, Raper SCB. 1997. The observed global warming record: What does it tell us?. PNAS 94:8314–20 [Google Scholar]
  91. Winton M, Griffies SM, Samuels BL, Sarmiento JL, Frolicher T. 2013. Connecting changing ocean circulation with changing climate. J. Clim. 26:2268–78 [Google Scholar]
  92. Wong T, Wielicki BA, Lee RB, Smith GL, Bush KA, Willis JK. 2006. Reexamination of the observed decadal variability of the Earth radiation budget using altitude-corrected ERBE/ERBS Nonscanner WFOV data. J. Clim. 19:4028–40 [Google Scholar]
/content/journals/10.1146/annurev-earth-060614-105156
Loading
/content/journals/10.1146/annurev-earth-060614-105156
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error