Cloud Radiation Forcings and Feedbacks: General Circulation Model Tests and Observational Validation

Wan-Ho Lee Climate Research Division, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

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Sam F. Iacobellis Climate Research Division, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

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Richard C. J. Somerville Climate Research Division, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

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Abstract

Using an atmospheric general circulation model (the National Center for Atmospheric Research Community Climate Model: CCM2), the effects on climate sensitivity of several different cloud radiation parameterizations have been investigated. In addition to the original cloud radiation scheme of CCM2, four parameterizations incorporating prognostic cloud water were tested: one version with prescribed cloud radiative properties and three other versions with interactive cloud radiative properties. The authors’ numerical experiments employ perpetual July integrations driven by globally constant sea surface temperature forcings of two degrees, both positive and negative.

A diagnostic radiation calculation has been applied to investigate the partial contributions of high, middle, and low cloud to the total cloud radiative forcing, as well as the contributions of water vapor, temperature, and cloud to the net climate feedback. The high cloud net radiative forcing is positive, and the middle and low cloud net radiative forcings are negative. The total net cloud forcing is negative in all of the model versions. The effect of interactive cloud radiative properties on global climate sensitivity is significant. The net cloud radiative feedbacks consist of quite different shortwave and longwave components between the schemes with interactive cloud radiative properties and the schemes with specified properties. The increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn to negative shortwave feedbacks for the interactive radiative schemes, while the decrease in cloud amount simply produces a positive shortwave feedback for the schemes with a specified cloud water path. For the longwave feedbacks, the decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while for the other cases, the longwave feedback is positive.

These cloud radiation parameterizations are empirically validated by using a single-column diagnostic model, together with measurements from the Atmospheric Radiation Measurement program and from the Tropical Ocean Global Atmosphere Combined Ocean–Atmosphere Response Experiment. The inclusion of prognostic cloud water produces a notable improvement in the realism of the parameterizations, as judged by these observations. Furthermore, the observational evidence suggests that deriving cloud radiative properties from cloud water content and microphysical characteristics is a promising route to further improvement.

* Current affiliation: Systems Engineering Research Institute, Yoosung-Gu, Taejun, Choongnam, Korea.

Corresponding author address: Prof. Richard C. J. Somerville, Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, Dept. 0224, La Jolla, CA 92093-0224.

Abstract

Using an atmospheric general circulation model (the National Center for Atmospheric Research Community Climate Model: CCM2), the effects on climate sensitivity of several different cloud radiation parameterizations have been investigated. In addition to the original cloud radiation scheme of CCM2, four parameterizations incorporating prognostic cloud water were tested: one version with prescribed cloud radiative properties and three other versions with interactive cloud radiative properties. The authors’ numerical experiments employ perpetual July integrations driven by globally constant sea surface temperature forcings of two degrees, both positive and negative.

A diagnostic radiation calculation has been applied to investigate the partial contributions of high, middle, and low cloud to the total cloud radiative forcing, as well as the contributions of water vapor, temperature, and cloud to the net climate feedback. The high cloud net radiative forcing is positive, and the middle and low cloud net radiative forcings are negative. The total net cloud forcing is negative in all of the model versions. The effect of interactive cloud radiative properties on global climate sensitivity is significant. The net cloud radiative feedbacks consist of quite different shortwave and longwave components between the schemes with interactive cloud radiative properties and the schemes with specified properties. The increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn to negative shortwave feedbacks for the interactive radiative schemes, while the decrease in cloud amount simply produces a positive shortwave feedback for the schemes with a specified cloud water path. For the longwave feedbacks, the decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while for the other cases, the longwave feedback is positive.

These cloud radiation parameterizations are empirically validated by using a single-column diagnostic model, together with measurements from the Atmospheric Radiation Measurement program and from the Tropical Ocean Global Atmosphere Combined Ocean–Atmosphere Response Experiment. The inclusion of prognostic cloud water produces a notable improvement in the realism of the parameterizations, as judged by these observations. Furthermore, the observational evidence suggests that deriving cloud radiative properties from cloud water content and microphysical characteristics is a promising route to further improvement.

* Current affiliation: Systems Engineering Research Institute, Yoosung-Gu, Taejun, Choongnam, Korea.

Corresponding author address: Prof. Richard C. J. Somerville, Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, Dept. 0224, La Jolla, CA 92093-0224.

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  • Barkstrom, B. R., 1984: The Earth Radiation Budget Experiment (ERBE). Bull. Amer. Meteor. Soc.,65, 1170–1185.

  • Bower, K. N., T. W. Choularton, J. Latham, J. Nelson, M. B. Baker, and J. Jenson, 1994: A parameterization of warm c1ouds for use in atmospheric general circulation models. J. Atmos. Sci.,51, 2722–2732.

  • Brock, F. V., K. Crawford, R. Elliott, G. Cuperus, S. Stadler, H. Johnson, and M. Eilts, 1995: The Oklahoma Mesonet: A technical overview. J. Atmos. Oceanic Technol.,12, 5–19.

  • Cess, R. D., and G. L. Potter, 1988: A methodology for understanding and intercomparing atmospheric climate feedback processes in general circulation models. J. Geophys. Res.,93, 8305–8314.

  • ——, and Coauthors, 1990: Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. J. Geophys. Res.,95, 16601–16615.

  • ——, and Coauthors, 1996: Cloud feedback in atmospheric general circulation models: An update. J. Geophys. Res.,101, 12791–12794.

  • Del Genio, A. D., M.-S. Yao, W. Kovari, and K. K.-W. Lo, 1996: A prognostic cloud water parameterization for global climate models. J. Climate,9, 270–304.

  • Fouquart, Y., and B. Bonnel, 1980: Computation of solar heating of the Earth’s atmosphere: A new parameterization. Beitr. Phys. Atmos.,53, 35–62.

  • Hack, J. J., 1994: Parameterization of moist convection in the National Center for Atmospheric Research community climate model (CCM2). J. Geophys. Res.,99, 5551–5568.

  • ——, B. A. Boville, B. P. Briegleb, J. T. Kiehl, P. J. Rasch, and D. L. Williamson, 1993: Description of the NCAR Community Climate Model (CCM2). NCAR Tech. Note NCAR/TN-382+STR, 108 pp. [Available from National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307.].

  • Heymsfield, A. J., and C. M. R. Platt, 1984: A parameterization of the particle size spectrum of ice clouds in terms of the ambient temperature and the ice water content. J. Atmos. Sci.,41, 846–855.

  • Miller, E. R., and A. C. Riddle, 1994: TOGA COARE Integrated Sounding System data report—Volume IA revised edition. TOGA COARE International Project Office, 99 pp. [Available from TOGA COARE International Project Office, University Corporation for Atmospheric Research, 1850 Table Mesa Dr., Boulder, CO 80303.].

  • Minnis, P., W. L. Smith Jr., D. P. Garber, J. K. Ayers, and D. R. Doelling, 1995: Cloud properties derived from GOES-7 for spring 1994 ARM intensive observing period using Version 1.0.0 of ARM Satellite Data Analysis Program. NASA RP-1366, 59 pp. [Available from Patrick Minnis, NASA/Langley Research Center, MS 420, Hampton, VA 23665.].

  • Mitchell, J. F. B., and W. J. Ingram, 1992: Carbon dioxide and climate: Mechanisms of changes in cloud. J. Climate,5, 5–21.

  • Morcrette, J.-J., 1990: Impact of changes to the radiation transfer parameterizations plus cloud optical properties in the ECMWF model. Mon. Wea. Rev.,118, 847–873.

  • O’Brien, J. J., 1970: Alternative solutions to the classical vertical velocity problem. J. Appl. Meteor.,9, 197–203.

  • Ramanathan, V., 1987: The role of earth radiation budget studies in climate and general circulation research. J. Geophys. Res.,92, 4075–4095.

  • ——, B. R. Barkstrom, and E. F. Harrison, 1989: Climate and the Earth’s radiation budget. Phys. Today, May, 22–32.

  • Randall, D. A., K.-M. Xu, R. C. J. Somerville, and S. Iacobellis, 1996: Single-column models and cloud ensemble models as links between observations and climate models. J. Climate,9, 1683–1697.

  • Senior, C. A., and J. F. B. Mitchell, 1993: Carbon dioxide and climate: The impact of cloud parameterization. J. Climate,6, 393–418.

  • Slingo, A., 1989: A GCM parameterization for the shortwave radiative properties of water clouds. J. Atmos. Sci.,46, 1419–1427.

  • Slingo, J. M., 1987: The development and verification of a cloud prediction scheme for the ECMWF model. Quart. J. Roy. Meteor. Soc.,113, 899–927.

  • Smith, R. N. B., 1990: A scheme for predicting layer cloud and their water content in a general circulation model. Quart. J. Roy. Meteor. Soc.,116, 435–460.

  • Somerville, R. C. J., and L. A. Remer, 1984: Cloud optical thickness feedbacks in the CO2 climate problem. J. Geophys. Res.,89, 9668–9672.

  • Spencer, R. W., 1993: Global oceanic precipitation from the MSU during 1979–92 and comparisons to other climatologies. J. Climate,6, 1301–1326.

  • Sundqvist, H., 1981: Prediction of stratiform clouds: results from a 5-day forecast with a global model. Tellus,33, 242–253.

  • Suzuki, T., M. Takana, and T. Nakajima, 1993: The microphysical feedback of cirrus cloud in climate change. J. Meteor. Soc. Japan,71, 701–713.

  • Zhang, G. J., and N. A. McFarlane, 1995: Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Centre general circulation model. Atmos.Ocean,33, 407–446.

  • Zhang, M. H., J. J. Hack, J. T. Kiehl, and R. D. Cess, 1994: Diagnostic study of climate feedback processes in atmospheric general circulation models. J. Geophys. Res.,99, 5525–5537.

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