Atmospheric Chemistry and Physics www.atmos-chem-phys.net 1680-7316 1680-7324 10 4 2010 10.5194/acp-10-1923-2010 http://www.atmos-chem-phys.net/10/1923/2010/ http://www.atmos-chem-phys.net/10/1923/2010/acp-10-1923-2010.html http://www.atmos-chem-phys.net/10/1923/2010/acp-10-1923-2010.pdf 1923 1930 2010-02-19 Estimations of climate sensitivity based on top-of-atmosphere radiation imbalance B. Lin bing.lin@nasa.gov L. Chambers P. Stackhouse Jr. B. Wielicki Y. Hu P. Minnis N. Loeb W. Sun G. Potter Q. Min G. Schuster T.-F. Fan NASA Langley Research Center, Hampton, VA 23681, USA SSAI, One Enterprise Parkway, Hampton, VA 23666, USA University of California at Davis, Davis, CA 95616, USA State University of New York at Albany, Albany, NY 12222, USA Large climate feedback uncertainties limit the accuracy in predicting the response of the Earth's climate to the increase of CO₂ concentration within the atmosphere. This study explores a potential to reduce uncertainties in climate sensitivity estimations using energy balance analysis, especially top-of-atmosphere (TOA) radiation imbalance. The time-scales studied generally cover from decade to century, that is, middle-range climate sensitivity is considered, which is directly related to the climate issue caused by atmospheric CO₂ change. The significant difference between current analysis and previous energy balance models is that the current study targets at the boundary condition problem instead of solving the initial condition problem. Additionally, climate system memory and deep ocean heat transport are considered. The climate feedbacks are obtained based on the constraints of the TOA radiation imbalance and surface temperature measurements of the present climate. In this study, the TOA imbalance value of 0.85 W/m² is used. Note that this imbalance value has large uncertainties. Based on this value, a positive climate feedback with a feedback coefficient ranging from −1.3 to −1.0 W/m²/K is found. The range of feedback coefficient is determined by climate system memory. The longer the memory, the stronger the positive feedback. The estimated time constant of the climate is large (70~120 years) mainly owing to the deep ocean heat transport, implying that the system may be not in an equilibrium state under the external forcing during the industrial era. For the doubled-CO₂ climate (or 3.7 W/m² forcing), the estimated global warming would be 3.1 K if the current estimate of 0.85 W/m² TOA net radiative heating could be confirmed. With accurate long-term measurements of TOA radiation, the analysis method suggested by this study provides a great potential in the estimations of middle-range climate sensitivity. Aires, F. and Rossow, W. R.: Inferring instantaneous, multivariate and nonlinear sensitivities for analysis of feedbacks in a dynamical system: Lorentz model case study, Q. J. Roy. Meteor. Soc., 129, 239–275, 2003. Blender, R., Fraedrich, K., and Hunt, B.: Millennial climate variability: GCM-simulation and Greenland ice core, Geophys. Res. Lett., 33, L04710, doi:10.1029/2005GL024919, 2006. Dickinson, R.: Convergence rate and stability of ocean-atmosphere coupling schemes with a zero-dimensional climate model, J. Atmos. Sci., 38, 2112–2120, 1981. Hansen, J., Lacis, A., Rind, D., Russell, G., Stone, P., Fung, I., Ruedy, R., and Lerner, J.: Climate sensitivity: Analysis of feedback mechanisms. In \textitClimate Processes and Climate Sensitivity, in: American Geophysical Union, edited by: Hansen, J. E. and Takahashi, T., AGU Geophysical Monograph, 29, Maurice Ewing Vol. 5., 130–163, 1984. Hansen, J., Ruedy, R., Sato, M., and Reynolds, R.: Global surface air temperature in 1995: Return to pre-Pinatubo level, Geophys. Res. Lett., 23, 1665–1668, 1996. Hansen, J., Nazarenko, L., Ruedy, R., and coauthors: Earth's energy imbalance: Confirmation and implications, Science, 308, 1431–1435, 2005. Hansen, J., Sato, M., Kharecha, P., Russell, G., lea, D., and Siddall, M.: Climate change and trace gases, Phil. Trans. R. Soc., A, 365, 1925–1954, 2007. IPCC: Summary for Policymakers. In Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Chang, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, UK and New York, NY, USA, 2007. Kiehl, J.: Twentieth century climate model response and climate sensitivity, Geophys. Res. Lett., 34, L22710, doi:10.1029/2007GL031383, 2007. Lin, B., Stackhouse Jr., P., Minnis, P., Wielicki, B., Hu, Y., Sun, W., Fan, T.-F., and Hinkelman, L.: Assessment of global annual atmospheric energy balance from satellite observations, J. Geophys. Res., 113, D16114, doi:10.1029/2008JD009869, 2008. Lindzen, R. and Giannitsis, C.: On the climate implications of volcanic cooling, J. Geophys. Res., 103, 5929–5941, 1998. Manabe, S., Bryan, K., and Spelman, M.: Transient response of a global ocean-atmosphere model to a doubling of atmospheric carbon dioxide, J. Phys. Ocean., 20, 722–749, 1990. Roe, G. and Baker, M.: Why is climate sensitivity so unpredictable, Science, 318, 629–632, 2007. Schwartz, S.: Heat capacity, time constant, and sensitivity of Earth's climate system, J. Geophys. Res., 112, D24S05, doi:10.1029/2007/2007JD008746, 2007. Schwartz, S.: Reply to comments by G. Foster et al., R. Knutti et al., and N. Scafetta on "Heat capacity, time constant, and sensitivity of Earth's climate system", J. Geophys. Res., 113, D15105, doi:10.1029/2008JD009872, 2008. Spencer, R. and Braswell, W.: On the diagnosis of radiative feedback in the presence of unknown radiative forcing, Proc. of the Fall Meeting of Am. Geophys. Union, San Francisco, CA, USA, available online at: http://www.drroyspencer.com/research-articles/satellite-and-climate-model-evidence/ or http://science.larc.nasa.gov/ceres/STM/2009-04/pdf/14_Forcing-feedback-2-CERES-April-2009_Spencer.pdf, 14–18 December 2009. Trenberth, K., Fasullo, J., and Kiehl, J.: Earth's global energy budget, B. Am. Meteor. Soc., 90, 311–323, 2009. Von Storch, J.-S.: On statistical dissipation in GCM-climate, Clim. Dynam., 23, 1–15, doi:10.1007/s00382-004-0404-2., 2004. Wielicki, B. A., Wong, T., Allan, R., and coauthors: Evidence for large decadal variability in the tropical mean radiative energy budget, Science, 295, 841–844, 2002. Willis, J., Roemmich, D., and Cornuelle, B.: Interannual variability in upper-ocean heat content, temperature, and thermosteric expansion on global scales, J. Geophys. Res., 109, C12036, doi:10.1029/2003JC002260, 2004. Wong, T, Wielicki, B. A., and Lee III, R. B.: Reexamination of the observed decadal variability of earth radiation budget using altitude-corrected ERBE/ERBS nonscanner WFOV data, J. Clim., 19, 4028–4040, 2006. Wu, W. and Dickinson, R.: Time scales of layered soil moisture memory in the context of land-atmosphere interaction, J. Clim., 17, 2752–2764, 2004.