Quantifying the sources of intermodel spread in equilibrium climate sensitivity

Journal of Climate

Volumn 29, Issue 2, 2016, Pages 513-524

  Caldwell, Peter M ^a   Zelinka, Mark D ^a   Taylor, Karl E ^a   Marvel, Kate ^a,b  

^a LAWRENCE LIVERMORE NATIONAL LABORATORY   (United States)

^b NASA GODDARD INSTITUTE FOR SPACE STUDIES   (United States)

Author keywords

Climate models; Climate sensitivity; Feedback; Forcing; Mathematical and statistical techniques; Models and modeling; Physical meteorology and climatology; Statistics

Indexed keywords

CARBON DIOXIDE; FEEDBACK; STATISTICS;

CLIMATE SENSITIVITY; CLOUD FEEDBACKS; FORCING; MODEL DIFFERENCES; NEW APPROACHES; SPECIFIC HUMIDITY; STATISTICAL TECHNIQUES; TEMPERATURE RESPONSE;

CLIMATE MODELS;

CARBON DIOXIDE; CARBON EMISSION; CLIMATE MODELING; CLIMATE PREDICTION; NUMERICAL MODEL; WEATHER FORECASTING;

EID: 84957824678     PISSN: 08948755     EISSN: None     Source Type: Journal    
DOI: 10.1175/JCLI-D-15-0352.1     Document Type: Article

References (38)

1. Andrews, T., J. M. Gregory, M. J. Webb, and K. E. Taylor, 2012: Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models. Geophys. Res. Lett., 39, L09712, doi:10.1029/2012GL051607.
2. Andrews, T., J. M. Gregory, and M. J. Webb, 2015: The dependence of radiative forcing and feedback on evolving patterns of surface temperature change in climate models. J. Climate, 28, 1630-1648, doi:10.1175/JCLI-D-14-00545.1.
3. Armour, K. C., C. M. Bitz, and G. H. Roe, 2013: Time-varying climate sensitivity from regional feedbacks. J. Climate, 26, 4518-4534, doi:10.1175/JCLI-D-12-00544.1.
4. 2. J. Adv. Model. Earth Syst., 5, 676-691, doi:10.1002/jame.20041.
5. Bony, S., and Coauthors, 2006: How well do we understand and evaluate climate change feedback processes? J. Climate, 19, 3445-3482, doi:10.1175/JCLI3819.1.
6. Cess, R., 1975: Global climate change: An investigation of atmospheric feedback mechanisms. Tellus, 27A, 193-198, doi:10.1111/j.2153-3490.1975.tb01672.x.
7. Cess, R., and Coauthors, 1990: Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. J. Geophys. Res., 95, 16 601-16 615, doi:10.1029/JD095iD10p16601.
8. Cess, R., and Coauthors, 1997: Comparison of the seasonal change in cloud-radiative forcing from atmospheric general circulation models and satellite observations. J. Geophys. Res., 102, 16 593-16 603, doi:10.1029/97JD00927.
9. Chung, E.-S., and B. J. Soden, 2015a: An assessment of direct radiative forcing, radiative adjustments, and radiative feedbacks in coupled ocean-atmosphere models. J. Climate, 28, 4152-4170, doi:10.1175/JCLI-D-14-00436.1.
10. Chung, E.-S., and B. J. Soden, 2015b: An assessment of methods for computing radiative forcing in climate models. Environ. Res. Lett., 10, 074004, doi:10.1088/1748-9326/10/7/074004.
11. Dufresne, J.-L., and S. Bony, 2008: An assessment of the primary sources of spread of global warming estimates from coupled atmosphere-ocean models. J. Climate, 21, 5135-5144, doi:10.1175/2008JCLI2239.1.
12. Flato, G., and Coauthors, 2013: Evaluation of climate models. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 741-866. [Available online at https://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter09_FINAL.pdf.].
13. Gordon, N. D., and S. A. Klein, 2014: Low-cloud optical depth feedback in climate models. J. Geophys. Res. Atmos., 119, 6052-6065, doi:10.1002/2013JD021052.
14. Gregory, J., and Coauthors, 2004: A new method for diagnosing radiative forcing and climate sensitivity. Geophys. Res. Lett., 31, L03205, doi:10.1029/2003GL018747.
15. Held, I. M., and B. Soden, 2000: Water vapor feedback and global warming. Annu. Rev. Energy Environ., 25, 441-475, doi:10.1146/annurev.energy.25.1.441.
16. Held, I. M., and K. M. Shell, 2012: Using relative humidity as a state variable in climate feedback analysis. J. Climate, 25, 2578-2582, doi:10.1175/JCLI-D-11-00721.1.
17. Huybers, P., 2010: Compensation between model feedbacks and curtailment of climate sensitivity. J. Climate, 23, 3009-3018, doi:10.1175/2010JCLI3380.1.
18. 2 forcing. Part I: Adapting the linear radiative kernel technique to feedback calculations for a broad range of forcings. J. Climate, 25, 5260-5272, doi:10.1175/JCLI-D-11-00524.1.
19. Klein, S. A., and C. Jakob, 1999: Validation and sensitivities of frontal clouds simulated by the ECMWF model. Mon. Wea. Rev., 127, 2514-2531, doi:10.1175/1520-0493(1999)127<2514: VASOFC>2.0.CO;2.
20. Mauritsen, T., R.G.Graversen, D.Klocke, P. L. Langen, B. Stevens, and L. Tomassini, 2013: Climate feedback and synergy. Climate Dyn., 41, 2539-2554, doi:10.1007/s00382-013-1808-7.
21. O'Gorman, P. A., and M. S. Singh, 2013: Vertical structure of warming consistent with an upward shift in the middle and upper troposphere. Geophys. Res. Lett., 40, 1838-1842, doi:10.1002/grl.50328.
22. Reichler, T., M. Dameris, and R. Sausen, 2003: Determining the tropopause height from gridded data. Geophys. Res. Lett., 30, 2042, doi:10.1029/2003GL018240.
23. Ringer, M. A., T. Andrews, and M. J. Webb, 2014: Global-mean radiative feedbacks and forcing in atmosphere-only and coupled atmosphere-ocean climate change experiments. Geophys. Res. Lett., 41, 4035-4042, doi:10.1002/2014GL060347.
24. Rose, B. E. J., K. C. Armour, D. S. Battisti, N. Feldl, and D. D. B. Koll, 2014: The dependence of transient climate sensitivity and radiative feedbacks on the spatial pattern of ocean heat uptake. Geophys. Res. Lett., 41, 1071-1078, doi:10.1002/2013GL058955.
25. Shell, K. M., J. T. Kiehl, and C. A. Shields, 2008: Using the radiative kernel technique to calculate climate feedbacks in NCAR's community atmospheric model. J. Climate, 21, 2269-2282, doi:10.1175/2007JCLI2044.1.
26. Soden, B. J., and I. M. Held, 2006: An assessment of climate feedbacks in coupled ocean-atmosphere models. J. Climate, 19, 3354-3360, doi:10.1175/JCLI3799.1.
27. Soden, B. J., A. J. Broccoli, and R. S. Hemler, 2004: On the use of cloud forcing to estimate cloud feedback. J. Climate, 17, 3661-3665, doi:10.1175/1520-0442(2004)017<3661:OTUOCF>2.0.CO;2.
28. Soden, B. J., I. M. Held, R. Colman, K. M. Shell, J. T. Kiehl, and C. A. Shields, 2008: Quantifying climate feedbacks using radiative kernels. J. Climate, 21, 3504-3520, doi:10.1175/2007JCLI2110.1.
29. Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485-498, doi:10.1175/BAMS-D-11-00094.1.
30. Vial, J., J.-L. Dufresne, and S. Bony, 2013: On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates. Climate Dyn., 41, 3339-3362, doi:10.1007/s00382-013-1725-9.
31. Webb, M., C. Senior, S. Bony, and J.-J. Morcrette, 2001: Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models. Climate Dyn., 17, 905-922, doi:10.1007/s003820100157.
32. Webb, M., F. H. Lambert, and J. M. Gregory, 2013: Origins of differences in climate sensitivity, forcing, and feedback in climate models. Climate Dyn., 40, 677-707, doi:10.1007/s00382-012-1336-x.
33. Williams, K. D., W. J. Ingram, and J. M. Gregory, 2008: Time variation of effective climate sensitivity in GCMs. J. Climate, 21, 5076-5090, doi:10.1175/2008JCLI2371.1.
34. Winton, M., K. Takahashi, and I. M. Held, 2010: Importance of ocean heat uptake efficacy to transient climate change. J. Climate, 23, 2333-2344, doi:10.1175/2009JCLI3139.1.
35. World Meteorological Organization, 1957: Meteorology, a threedimensional science: Second session of the Commission for Aerology. WMO Bull., 4, 134-138.
36. Zelinka, M. D., and D. L. Hartmann, 2010: Why is longwave cloud feedback positive? J. Geophys. Res., 115, D16117, doi:10.1029/2010JD013817.
37. Zelinka, M. D., S. A. Klein, and D. L. Hartmann, 2012: Computing and partitioning cloud feedbacks using cloud property histograms. Part I: Cloud radiative kernels. J. Climate, 25, 3715-3735, doi:10.1175/JCLI-D-11-00248.1.
38. Zelinka, M. D., S. A. Klein, K. Taylor, T. Andrews, M. Webb, J. Gregory, and P. Forster, 2013: Contributions of different cloud types to feedbacks and rapid adjustments in CMIP5. J. Climate, 26, 5007-5027, doi:10.1175/JCLI-D-12-00555.1.