Editorial Type:
Article
Article Type:
Research Article

Sensitivity of the Simulated Climate to a Diagnostic Formulation for Cloud Liquid Water

James J. Hack National Center for Atmospheric Research,* Boulder, Colorado

Search for other papers by James J. Hack in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Jul 1998
DOI:
https://doi.org/10.1175/1520-0442(1998)011<1497:SOTSCT>2.0.CO;2
Page(s):
1497–1515
Restricted access

Abstract

The accurate treatment of clouds and their radiative properties is widely regarded to be among the most important problems facing global climate modeling. A number of the more serious systematic simulation biases in the NCAR Community Climate Model (CCM2) appear to be related to deficiencies in the treatment of cloud optical properties. In this paper, a simple diagnostic parameterization for cloud liquid water is presented. The sensitivity of the simulated climate to this alternative formulation, both in terms of mean climate metrics and measures of the climate system response, is illustrated. Resulting simulations show significant reductions in CCM2 systematic biases, particularly with respect to surface temperature, precipitation, and extratropical geopotential height-field anomalies. Many aspects of the simulated response to ENSO forcing are also substantially improved.

Corresponding author address: Dr. James J. Hack, NCAR/CGD, P.O. Box 3000, Boulder, CO 80307-3000.

Abstract

The accurate treatment of clouds and their radiative properties is widely regarded to be among the most important problems facing global climate modeling. A number of the more serious systematic simulation biases in the NCAR Community Climate Model (CCM2) appear to be related to deficiencies in the treatment of cloud optical properties. In this paper, a simple diagnostic parameterization for cloud liquid water is presented. The sensitivity of the simulated climate to this alternative formulation, both in terms of mean climate metrics and measures of the climate system response, is illustrated. Resulting simulations show significant reductions in CCM2 systematic biases, particularly with respect to surface temperature, precipitation, and extratropical geopotential height-field anomalies. Many aspects of the simulated response to ENSO forcing are also substantially improved.

Corresponding author address: Dr. James J. Hack, NCAR/CGD, P.O. Box 3000, Boulder, CO 80307-3000.

Save
Cover Journal of Climate
Journal of Climate

  • Betts, A. K., and Harshvardhan, 1987: Thermodynamic constraint on the cloud liquid water feedback in climate models. J. Geophys. Res.,92, 8483–8485.

  • Branstator, G., 1985: Analysis of general circulation model sea-surface temperature anomaly simulations using a linear model. Part I: Forced solutions. J. Atmos. Sci.,42, 2225–2241.

  • Briegleb, B. P., 1992: Delta-Eddington approximation for solar radiation in the NCAR Community Climate Model. J. Geophys. Res.,97, 7603–7612.

  • 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 nineteen 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.

  • Chen, M., R. D. Cess, and M.-H. Zhang, 1995: Effects of longwave cloud radiative forcing anomalies on the atmospheric response to equatorial sea surface temperature anomalies. J. Geophys. Res.,100, 13791–13810.

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

  • Fowler, L. D., D. A. Randall, and S. A. Rutledge, 1996: Liquid and ice cloud microphysics in the CSU general circulation model. Part I: Model description and simulated microphysical processes. J. Climate,9, 489–529.

  • Gleckler, P. J., and Coauthors, 1995: Cloud radiative effects on implied oceanic energy transports as simulated by atmospheric general circulation models. Geophys. Res. Lett.,22, 791–794.

  • Greenwald, T. J., G. L. Stephens, S. A. Christopher, and T. H. Vonder Haar, 1995: Observations of the global characteristics and regional radiative effects of marine cloud liquid water. J. Climate,8, 2928–2946.

  • Hack, J. J., 1998: Analysis of the improvement in implied meridional ocean energy transport as simulated by NCAR CCM3. J. Climate,11, 1237–1244.

  • ——, 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, National Center for Atmospheric Research, Boulder, CO, 108 pp. [NTIS PB93-221802/AS.].

  • ——, ——, J. T. Kiehl, P. J. Rasch, and D. L. Williamson, 1994: Climate statistics from the NCAR Community Climate Model (CCM2). J. Geophys. Res.,99, 20785–20813.

  • ——, J. T. Kiehl, and J. W. Hurrell, 1998: The hydrologic and thermodynamic characteristics of the NCAR CCM3. J. Climate,11, 1179–1206.

  • Hoskins, B., and D. J. Karoly, 1981: The steady linear response of a spherical atmosphere to thermal and orographic forcing. J. Atmos. Sci.,38, 1179–1196.

  • Hurrell, J. W., and G. G. Campbell, 1992: Monthly mean global satellite data sets available in CCM history tape format. NCAR Tech. Note NCAR/TN-371+STR, National Center for Atmospheric Research, Boulder, CO, 94 pp.

  • ——, J. J. Hack, and D. P. Baumhefner, 1993: Comparison of NCAR Community Model Climates. NCAR Tech. Note NCAR/TN-395+STR, Boulder, CO, 335 pp.

  • Kiehl, J. T., 1994: Sensitivity of a GCM climate simulation to differences in continental versus maritime cloud drop size. J. Geophys. Res.,99, 23107–23115.

  • ——, and V. Ramanathan, 1990: Comparison of cloud forcing derived from the Earth Radiation Budget Experiment with that simulated by the NCAR Community Climate Model. J. Geophys. Res.,95, 11679–11698.

  • ——, and B. P. Briegleb, 1991: A new parameterization of the absorptance due to the 15-μm band system of carbon dioxide. J. Geophys. Res.,96, 9013–9019.

  • ——, and K. E. Trenberth, 1997: Earth’s annual global mean energy budget. Bull. Amer. Meteor. Soc.,78, 197–208.

  • ——, R. J. Wolski, B. P. Briegleb, and V. Ramanathan, 1987: Documentation of radiation and cloud routines in the NCAR Community Climate Model (CCM1). NCAR Tech. Note NCAR/TN-288+IA, Boulder, CO.

  • ——, J. J. Hack, and B. P. Briegleb, 1994: The simulated earth radiation budget of the NCAR CCM2 and comparisons with the Earth Radiation Budget Experiment (ERBE). J. Geophys. Res.,99, 20815–20827.

  • ——, J. J. Hack, G. B. Bonan, B. A. Boville, B. P. Briegleb, D. L. Williamson, and P. J. Rasch, 1996: Description of the NCAR Community Climate Model (CCM3). NCAR Tech. Note NCAR/TN420+STR, National Center for Atmospheric Research, Boulder, CO, 152 pp.

  • ——, ——, ——, ——, D. L. Williamson, and P. J. Rasch, 1998: The National Center for Atmospheric Research Community Climate Model: CCM3. J. Climate,11, 1131–1150.

  • Legates, D. R., and C. J. Willmott, 1990: Mean seasonal and spatial variability in gage-corrected, global precipitation. Int. J. Climatol.,10, 111–127.

  • Lin, B., and W. B. Rossow, 1994: Observations of cloud liquid water path over oceans: Optical and microwave remote sensing methods. J. Geophys. Res.,99, 20 907–20 927.

  • Njoku, E. G., and L. Swanson, 1983: Global measurements of sea surface temperature, wind speed, and atmospheric water content from satellite microwave radiometry. Mon. Wea. Rev.,111, 1977–1987.

  • Prabhakara, C., I. Wang, A. T. C. Chang, and P. Gloersen, 1983: A statistical examination of Nimbus 7 SMMR data and remote sensing of sea surface temperature, liquid water content in the atmosphere, and surface wind speed. J. Climate Appl. Meteor.,22, 2023–2037.

  • Ramanathan, V., and W. Collins, 1991: Thermodynamic regulation of ocean warming by cirrus clouds deduced from observations of the 1987 El Niño. Nature,351, 27–32.

  • ——, E. J. Pitcher, R. C. Malone, and M. L. Blackmon, 1983: The response of a spectral general circulation model to refinements in radiative processes. J. Atmos. Sci.,40, 605–630.

  • Rossow, W. B., and Y.-C. Zhang, 1995: Calculation of surface and top of atmosphere radiative fluxes from physical quantities based on ISCCP data sets 2. Validation and first results. J. Geophys. Res.,100, 1167–1197.

  • Sardeshmukh, P. D., and B. J. Hoskins, 1988: The generation of global rotational flow by steady idealized tropical divergence. J. Atmos. Sci.,45, 1228–1251.

  • 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.

  • Smagorinsky, J., S. Manabe, and J. L. Holloway Jr., 1965: Numerical results from a nine-level general circulation model of the atmosphere. Mon. Wea. Rev.,93, 727–768.

  • Smith, R. N. B., 1990: A scheme for predicting layer clouds and their water content in a general circulation model. Quart. J. Roy. Meteor. Soc.,116, 436–460.

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

  • Sundqvist, H., 1988: Parameterization of condensation and associated clouds in models for weather prediction and general circulation simulation. Physically Based Modelling and Simulation of Climate and Climatic Change, M. E. Schlesinger, Ed., Vol. 1, Kluwer Academic Publishers, 433–461.

  • ——, 1993: Inclusion of ice-phase of hydrometeors in cloud parameterizations for mesoscale and large-scale models. Contrib. Atmos. Phys.,66, 137–147.

  • Tiedtke, M., 1993: Representation of clouds in large-scale models. Mon. Wea. Rev.,121, 3040–3061.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 798 582 26
PDF Downloads 70 26 0