• Cess, R. D., and Coauthors, 1996: Cloud feedback in atmospheric general circulation models: An update. J. Geophys. Res., 101D , 1279112794.

    • Search Google Scholar
    • Export Citation
  • Colman, R., 2003: A comparison of climate feedbacks in general circulation models. Climate Dyn., 20 , 865873.

  • Colman, R. A., , S. B. Power, , and B. J. McAvaney, 1997: Non-linear climate feedback analysis in an atmospheric general circulation model. Climate Dyn., 13 , 717731.

    • Search Google Scholar
    • Export Citation
  • Feigelson, E. D., , and G. J. Babu, 1992: Linear-regression in astronomy. 2. Astrophys. J., 397 , 5567.

  • Forest, C. E., , P. H. Stone, , A. P. Sokolov, , M. R. Allen, , and M. D. Webster, 2002: Quantifying uncertainties in climate system properties with the use of recent climate observations. Science, 295 , 113117.

    • Search Google Scholar
    • Export Citation
  • Forster, P. M. D., , and M. Collins, 2004: Quantifying the water vapour feedback associated with post-Pinatubo global cooling. Climate Dyn., 23 , 207214.

    • Search Google Scholar
    • Export Citation
  • Gregory, J. M., , R. J. Stouffer, , S. C. B. Raper, , P. A. Stott, , and N. A. Rayner, 2002: An observationally based estimate of the climate sensitivity. J. Climate, 15 , 31173121.

    • Search Google Scholar
    • Export Citation
  • Gregory, J. M., and Coauthors, 2004: A new method for diagnosing radiative forcing and climate sensitivity. Geophys. Res. Lett., 31 .L03205, doi:10.1029/2003GL018747.

    • Search Google Scholar
    • Export Citation
  • Hall, A., , and S. Manabe, 1999: The role of water vapor feedback in unperturbed climate variability and global warming. J. Climate, 12 , 23272346.

    • Search Google Scholar
    • Export Citation
  • Hansen, J., , M. Sato, , and R. Ruedy, 1997: Radiative forcing and climate response. J. Geophys. Res., 102 , D6,. 68316864.

  • Hansen, J., , R. Ruedy, , J. Glascoe, , and M. Sato, 1999: GISS analysis of surface temperature change. J. Geophys. Res., 104 , D24,. 3099731022.

    • Search Google Scholar
    • Export Citation
  • Hansen, J., and Coauthors, 2002: Climate forcings in Goddard Institute for Space Studies SI2000 simulations. J. Geophys. Res., 107 .4347, doi:10.1029/2001JD001143.

    • Search Google Scholar
    • Export Citation
  • Harvey, L. D. D., , and R. K. Kaufmann, 2002: Simultaneously constraining climate sensitivity and aerosol radiative forcing. J. Climate, 15 , 28372861.

    • Search Google Scholar
    • Export Citation
  • Houghton, J. T., , G. J. Jenkins, , and J. J. Ephraums, 1990: Scientific Assessment of Climate Change. Cambridge University Press, 365 pp.

  • Houghton, J. T., , Y. Ding, , D. J. Griggs, , M. Noguer, , P. J. van der Linden, , X. Dai, , K. Maskell, , and C. A. Johnson, 2001: Climate Change 2001: The Scientific Basis. Cambridge University Press, 881 pp.

    • Search Google Scholar
    • Export Citation
  • Isobe, T., , E. D. Feigelson, , M. G. Akritas, , and G. J. Babu, 1990: Linear-regression in astronomy. 1. Astrophys. J., 364 , 104113.

  • Jacobowitz, H., , H. V. Soule, , H. L. Kyle, , and F. B. House, 1984: The Earth Radiation Budget (Erb) Experiment—An overview. J. Geophys. Res., 89D , 50215038.

    • Search Google Scholar
    • Export Citation
  • Jones, P. D., , M. New, , D. E. Parker, , S. Martin, , and I. G. Rigor, 1999: Surface air temperature and its changes over the past 150 years. Rev. Geophys., 37 , 173199.

    • Search Google Scholar
    • Export Citation
  • Joshi, M., , K. Shine, , M. Ponater, , N. Stuber, , R. Sausen, , and L. Li, 2003: A comparison of climate response to different radiative forcings in three general circulation models: Towards an improved metric of climate change. Climate Dyn., 20 , 843854.

    • Search Google Scholar
    • Export Citation
  • Knutti, R., , T. F. Stocker, , F. Joos, , and G. K. Plattner, 2003: Probabilistic climate change projections using neural networks. Climate Dyn., 21 , 257272.

    • Search Google Scholar
    • Export Citation
  • Leggett, J. A., , W. J. Pepper, , and R. J. Swart, 1992: Emmissions scenarios for the IPCC: An update. Climate Change 1992: The Supplemenatary Report to the IPCC Scientific Assessment, J. T. Houghton, B. A. Callander, and S. K. Varney, Eds., Cambridge University Press, 69–95.

    • Search Google Scholar
    • Export Citation
  • Levitus, S., , J. I. Antonov, , T. P. Boyer, , and C. Stephens, 2000: Warming of the world ocean. Science, 287 , 22252229.

  • Myhre, G., , A. Myhre, , and F. Stordal, 2001: Historical evolution of radiative forcing of climate. Atmos. Environ., 35 , 23612373.

  • Sato, M., , J. E. Hansen, , M. P. McCormick, , and J. B. Pollack, 1993: Stratospheric aerosol optical depths, 1850–1990. J. Geophys. Res., 98 , D12,. 2298722994.

    • Search Google Scholar
    • Export Citation
  • Senior, C. A., , and J. F. B. Mitchell, 2000: The time-dependence of climate sensitivity. Geophys. Res. Lett., 27 , 26852688.

  • Soden, B. J., 1997: Variations in the tropical greenhouse effect during El Niño. J. Climate, 10 , 10501055.

  • Soden, B. J., , R. T. Wetherald, , G. L. Stenchikov, , and A. Robock, 2002: Global cooling after the eruption of Mount Pinatubo: A test of climate feedback by water vapor. Science, 296 , 727730.

    • Search Google Scholar
    • Export Citation
  • Soden, B. J., , A. J. Broccoli, , and R. S. Hemler, 2004: On the use of cloud forcing to estimate cloud feedback. J. Climate, 17 , 36613665.

    • Search Google Scholar
    • Export Citation
  • Stott, P. A., , S. F. B. Tett, , G. S. Jones, , M. R. Allen, , J. F. B. Mitchell, , and G. J. Jenkins, 2000: External control of 20th century temperature by natural and anthropogenic forcings. Science, 290 , 21332137.

    • Search Google Scholar
    • Export Citation
  • Wielicki, B. A., and Coauthors, 2002: Evidence for large decadal variability in the tropical mean radiative energy budget. Science, 295 , 841844.

    • Search Google Scholar
    • Export Citation
  • Zhang, Y. C., , W. B. Rossow, , A. A. Lacis, , V. Oinas, , and M. I. Mishchenko, 2004: Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: Refinements of the radiative transfer model and the input data. J. Geophys. Res., 109 .D19105, doi:10.1029/2003JD004457.

    • Search Google Scholar
    • Export Citation
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The Climate Sensitivity and Its Components Diagnosed from Earth Radiation Budget Data

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  • 1 Department of Meteorology, University of Reading, Reading, United Kingdom
  • | 2 Centre for Global Atmospheric Modelling, Department of Meteorology, University of Reading, Reading, and Hadley Centre, Met Office, Exeter, United Kingdom
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Abstract

One of the major uncertainties in the ability to predict future climate change, and hence its impacts, is the lack of knowledge of the earth’s climate sensitivity. Here, data are combined from the 1985–96 Earth Radiation Budget Experiment (ERBE) with surface temperature change information and estimates of radiative forcing to diagnose the climate sensitivity. Importantly, the estimate is completely independent of climate model results. A climate feedback parameter of 2.3 ± 1.4 W m−2 K−1 is found. This corresponds to a 1.0–4.1-K range for the equilibrium warming due to a doubling of carbon dioxide (assuming Gaussian errors in observable parameters, which is approximately equivalent to a uniform “prior” in feedback parameter). The uncertainty range is due to a combination of the short time period for the analysis as well as uncertainties in the surface temperature time series and radiative forcing time series, mostly the former. Radiative forcings may not all be fully accounted for; however, an argument is presented that the estimate of climate sensitivity is still likely to be representative of longer-term climate change. The methodology can be used to 1) retrieve shortwave and longwave components of climate feedback and 2) suggest clear-sky and cloud feedback terms. There is preliminary evidence of a neutral or even negative longwave feedback in the observations, suggesting that current climate models may not be representing some processes correctly if they give a net positive longwave feedback.

Corresponding author address: Piers Forster, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, United Kingdom. Email: piers@env.leeds.ac.uk

Abstract

One of the major uncertainties in the ability to predict future climate change, and hence its impacts, is the lack of knowledge of the earth’s climate sensitivity. Here, data are combined from the 1985–96 Earth Radiation Budget Experiment (ERBE) with surface temperature change information and estimates of radiative forcing to diagnose the climate sensitivity. Importantly, the estimate is completely independent of climate model results. A climate feedback parameter of 2.3 ± 1.4 W m−2 K−1 is found. This corresponds to a 1.0–4.1-K range for the equilibrium warming due to a doubling of carbon dioxide (assuming Gaussian errors in observable parameters, which is approximately equivalent to a uniform “prior” in feedback parameter). The uncertainty range is due to a combination of the short time period for the analysis as well as uncertainties in the surface temperature time series and radiative forcing time series, mostly the former. Radiative forcings may not all be fully accounted for; however, an argument is presented that the estimate of climate sensitivity is still likely to be representative of longer-term climate change. The methodology can be used to 1) retrieve shortwave and longwave components of climate feedback and 2) suggest clear-sky and cloud feedback terms. There is preliminary evidence of a neutral or even negative longwave feedback in the observations, suggesting that current climate models may not be representing some processes correctly if they give a net positive longwave feedback.

Corresponding author address: Piers Forster, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, United Kingdom. Email: piers@env.leeds.ac.uk

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