Assessment of different metrics for physical climate feedbacks
详细信息 查看全文
- 作者：Daniel Klocke (1) (2)
Johannes Quaas (1)
Bjorn Stevens (1) - 关键词：Climate feedbacks ; Radiative forcing ; Climate sensitivity
- 刊名：Climate Dynamics
- 出版年：2013
- 出版时间：September 2013
- 年：2013
- 卷：41
- 期：5-6
- 页码：1173-1185
- 全文大小：2750KB
- 参考文献：1. Andrews T, Forster PM (2008) CO2 forcing induces semi-direct effects with consequences for climate feedback interpretation, Geophys Res Lett 35:L04802. doi:10.1029/2007GL032273 CrossRef
2. Boer GJ, Yu B (2003) Climate sensitivity and climate state. Clim Dyn 21:167鈥?76 CrossRef
3. Bony S, Dufresne J (2005) Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models. Geophys Res Lett 32:L20806. doi:10.1029/2005GL023851 CrossRef
4. Bony S et聽al (2006) How well do we understand and evaluate climate change feedback processes? J Clim 19:3445鈥?482 CrossRef
5. Cagnazzo C, Manzini E, Giorgetta MA, De F, Fortster PM, Morcrette JJ (2007) Impact of an improved shortwave radiation scheme in the MAECHAM5 general circulation model. Atmos Chem Phys 7:2503-2515
6. Cess R (1975) Global climate change: an investigation of atmospheric feedback mechanisms. Tellus 27:193鈥?98 CrossRef
7. Cess RD, Potter GL (1987) Exploratory studies of cloud radiative forcing with a general circulation model. Tellus A 39A(5):460鈥?73. doi:10.1111/j.1600-0870.1987.tb00321.x CrossRef
8. Cess RD et聽al (1990) Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. J Geophys Res 95:16601鈥?6615 CrossRef
9. Colman RA, McAvaney BJ (1997) A study of general circulation model climate feedbacks determined from perturbed sea surface temperature experiments. J Geophys Res 102(D16):19383鈥?9402. doi:10.1029/97JD00206 CrossRef
10. Colman R (2003) A comparison of climate feedbacks in GCMs. Clim Dyn 20:865鈥?73
11. Friedlingstein P et聽al (2006) Climate-carbon cycle feedback analysis: results from the C4MIP model intercomparison. J Clim 19:3337鈥?353. doi:10.1175/JCLI3800.1 CrossRef
12. Gregory JM, Ingram WJ, Palmer MA, Jones GS, Stott PA, Thorpe RB, Lowe JA, Johns TC, Williams KD (2004) A new method for diagnosing radiative forcing and climate sensitivity. Geophys Res Lett 31:L03205 CrossRef
13. Gregory J, Webb M (2008) Tropospheric adjustment induces a cloud component in CO2 forcing. J Clim 21(1):58鈥?1. doi:10.1175/2007JCLI1834.1 CrossRef
14. Hansen J, Lacis A, Rind D, Russell G, Stone P, Fung I (1984) Climate sensitivity: analysis of feedback mechanisms, climate processes and climate sensitivity, geophysical monograph 29, American Geophysical Union, pp 130鈥?63
15. Hartmann DL, Larson K (2002) An important constraint on tropical cloud-climate feedback. Geophys Res Lett 29(20). doi:10.1029/2002GL015835
16. Held I, Soden B (2000) Water vapor feedback and global warming. Annu Rev Energy Environ 25:441鈥?75. doi:10.1146/annurev.energy.25.1.441 CrossRef
17. Held IM, Winton M, Takahashi K, Delworth T, Zeng F, Vallis G (2010) Probing the fast and slow components of global warming by returning abruply to preindustrial forcing. J Clim 23:2418鈥?427 CrossRef
18. Held IM, Shell KM (2012) Using relative humidity as a state variable in climate feedback analysis. J Clim 25:2578鈥?582 CrossRef
19. Huybers P (2010) Compensation between model feedbacks and curtailment of climate sensitivity. J Clim 23:3009鈥?018. doi:10.1175/2010JCLI3380.1 CrossRef
20. Jonko A, Shell K, Sanderson B, Danabasoglu G (2012) Climate feedbacks in CCSM3 under changing CO2 forcing. part i: adapting the linear radiative kernel technique to feedback calculations for a broad range of forcings. J Clim doi:10.1175/JCLI-D-11-00524.1
21. Loeb NG, Wielicki BA, Doelling DR, Smith GL, Keyes DF, Kato S, Manalo-Smith N, Wong T (2009) Toward optimal closure of the earth鈥檚 top-of-atmosphere radiation budget. J Clim 22:748鈥?66. doi:10.1175/2008JCLI2637.1 CrossRef
22. Roeckner E et聽al (2003) The atmospheric general circulation model ECHAM5. Part I: model description, Tech. Rep. 349, Max-Planck-Institut f眉r Meteorologie, Hamburg, Germany
23. Schneider EK, Kirtman BP, Lindzen RS (1999) Tropospheric water vapor and climate sensitivity. J Atmos Sci 56:1649鈥?658 CrossRef
24. Soden BJ, Broccoli AJ, Hemler RS (2004) On the use of cloud forcing to estimate cloud feedback. J Clim 17:3661鈥?665 CrossRef
25. Soden BJ, Held IM (2006) An assessment of climate feedbacks in coupled ocean-atmoshere models. J Clim 19:3354鈥?360 CrossRef
26. Soden BJ, Held IM, Colman R, Shell KM, Kiehl JT, Shields CA (2008) Quantifying climate feedbacks using radiative kernels. J Clim 21(14):3504鈥?520 CrossRef
27. Sohn B-J, Schmetz J, Stuhlmann R, Lee J-Y (2006) Dry bias in satellite-derived clear-sky water vapor and its contribution to longwave cloud radiative forcing. J Clim 19:5570鈥?580 CrossRef
28. Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt K, Tignor M, Miller H (2007) Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
29. Stevens B, Schwartz SE (2012) Observing and modeling earth鈥檚 energy flows. Surv Geophy 33(3鈥?):779鈥?16
30. Stone Peter H, Carlson John H (1979) Atmospheric lapse rate regimes and their parameterization. J Atmos Sci 36:415鈥?23 CrossRef
31. Stuber N, Sausen R, Ponater M (2001) Stratosphere adjusted radiative forcing calculations in a comprehensive climate model. Theor Appl Climatol 68(3):125鈥?35 CrossRef
32. Wetherald RT, Manabe S (1988) Cloud feedback processes in a general circulation model. J Atmos Sci 45:1397鈥?416 CrossRef
33. Wielicki Bruce A, Barkstrom Bruce R, Harrison Edwin F, Lee Robert B, Smith G Louis, Cooper John E (1996) Clouds and the Earth鈥檚 radiant energy system (CERES): an earth observing system experiment. Bull Am Meteorl Soc 77:853鈥?68 CrossRef
34. Zelinka MD, Hartmann DL (2010) Why is longwave cloud feedback positive? J Geophys Res 115:D16117. doi:10.1029/2010JD013817 CrossRef
35. Zhang MH, Hack JJ, Kiehl JT, Cess RD (1994) Diagnostic study of climate feedback processes in atmospheric general circulation models. J Geophys Res 99(D3):5525鈥?537. doi:10.1029/93JD03523 CrossRef - 作者单位：Daniel Klocke (1) (2)
Johannes Quaas (1)
Bjorn Stevens (1)
1. Max-Planck-Institut f眉r Meteorologie, Bundesstr. 52, 20146, Hamburg, Germany
2. European Centre for Medium-Range Weather Forecasts, Reading, Berkshire, UK - ISSN：1432-0894
文摘
We quantify the feedbacks from the physical climate system on the radiative forcing for idealized climate simulations using four different methods. The results differ between the methods and differences are largest for the cloud feedback. The spatial and temporal variability of each feedback is used to estimate the averaging scale necessary to satisfy the feedback concept of one constant global mean value. We find that the year-to-year variability, combined with the methodological differences, in estimates of the feedback strength from a single model is comparable to the model-to-model spread in feedback strength of the CMIP3 ensemble. The strongest spatial and temporal variability is in the short-wave component of the cloud feedback. In our simulations, where many sources of natural variability are neglected, long-term averages are necessary to get reliable feedback estimates. Considering the large natural variability and relatively small forcing present in the real world, as compared to the forcing imposed by doubling CO2 concentrations in the simulations, implies that using observations to constrain feedbacks is a challenging task and requires reliable long-term measurements.