• Andrich, P., P. Delecluse, C. Levy, and G. Madec, 1988: A multitasked general circulation model of the ocean. Science and Engineering on Cray Supercomputers. Proc. Fourth International Symp., Minneapolis, MN, Cray Research Inc., 407–428.

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

  • Dandin, P., 1993: Variabilité basse-fréquence simulée dans l’océan Pacifique tropical. Thèse de Doctorat de l’Université de Paris–VI, 320 pp.

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

  • Gill, A. E., 1980: Some simple solutions for heat induced tropical circulations. Quart. J. Roy. Meteor. Soc.,106, 447–462.

  • Harzallah, A., and R. Sadourny, 1995: Internal versus SST-forced atmospheric variability as simulated by an atmospheric general circulation model. J. Climate,8, 474–495.

  • Hasselmann, K., 1988: PIPs and POPs: The reduction of complex dynamical systems using principal interaction and oscillation patterns. J. Geophys. Res.,93, 11015–11021.

  • Kuo, H. L., 1964: On the formation and intensification of tropical cyclones through latent heat release by cumulus convection. J. Atmos. Sci.,21, 40–63.

  • Legeckis, R., 1977: Long waves in the eastern equatorial Pacific Ocean: A view from a geostationary satellite. Science,197, 1179–1181.

  • Le Treut, H., and Z. X. Li, 1991: Sensitivity of an atmospheric general circulation model to prescribed SST changes: Feedback effects associated with the simulation of cloud optical properties. Climate Dyn.,5, 175–187.

  • Manabe, S., and R. F. Strickler, 1964: On the thermal equilibrium of the atmosphere with convective adjustment. J. Atmos. Sci.,21, 361–385.

  • Morcrette, J. J., 1991: Radiation and cloud radiative properties in the ECMWF operational weather forecast model. J. Geophys. Res.,96, 9121–9132.

  • Preisendorfer, R. W., and T. P. Barnett, 1983: Numerical model–reality intercomparison test using small-sample statistics. J. Atmos. Sci.,40, 1884–1896.

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

  • Raval, A., and V. Ramanathan, 1989: Observational detection of the greenhouse effect. Nature,342, 758–761.

  • Reynolds, R. W., and D. C. Marsico, 1993: An improved real-time global sea surface temperature analysis. J. Climate,6, 114–119.

  • Sadourny, R., 1975a: The dynamics of finite-difference models of the shallow-water equations. J. Atmos. Sci.,32, 680–689.

  • ——, 1975b: Compressible model flows on the sphere. J. Atmos. Sci.,32, 2103–2110.

  • ——, and K. Laval, 1984: January and July performance of the LMD general circulation model. New Perspectives in Climate Modelling, A. Berger, Ed., Elsevier, 173–198.

  • von Storch, H., T. Bruns, I. Fisher-Bruns, and K. Hasselmann, 1988: Principal oscillation pattern analysis of the 30- to 60-day oscillation in general circulation model equatorial troposphere. J. Geophys. Res.,93, 11 022–11 036.

  • Zheng, Q., X. Yan, C. Ho, and C. Tai, 1994: The effects of shear flow on propagation of Rossby waves in the equatorial oceans. J. Phys. Oceanogr.,24, 1680–1687.

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A General Interface between an Atmospheric General Circulation Model and Underlying Ocean and Land Surface Models: Delocalized Physics Scheme

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  • 1 Laboratoire de Météorologie Dynamique du CNRS, Paris, France
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Abstract

In order to represent in a most adequate way the various feedback mechanisms that govern the atmosphere–ocean or atmosphere–surface couplings, a “delocalized physics” method is introduced, in which the subgrid-scale physical parameterizations of the atmospheric model are computed on a grid defined independently of the grid where adiabatic dynamics are computed. This “physical grid,” which can be irregular and time dependent, is defined by juxtaposing the surface grids constructed independently for the ocean, land, and sea-ice models. The delocalization method allows taking into account the nonlinearities of vertical fluxes due to heterogeneities in the finescale surface properties that are not resolved by the adiabatic atmospheric dynamics calculations. The impact of delocalizing the physics to fit a given higher resolution surface grid is tested first on experiments where the global atmosphere is forced by observed ocean temperatures. The comparison demonstrates a significant improvement of the predominant variability mode of the outgoing longwave radiation field, corresponding mainly to the seasonal cycle. The delocalized physics method is then tested on an experiment where the General circulation model of the Laboratoire de Météorologie Dynamique is coupled to the Laboratoire d’Océanographie Dynamique et de Climatologie tropical Pacific ocean model. Delocalized physics allow surface fluxes to respond better to fine sea surface temperatures structures like the Legekis waves produced by the ocean model.

Corresponding author address: Dr. Robert Sadourny, Laboratoire de Meteorologie Dynamique, CNRS, 24, rue Lhomond, 75231 Paris, Cedex 05, France.

Email: sadourny@lmd.ens.fr

Abstract

In order to represent in a most adequate way the various feedback mechanisms that govern the atmosphere–ocean or atmosphere–surface couplings, a “delocalized physics” method is introduced, in which the subgrid-scale physical parameterizations of the atmospheric model are computed on a grid defined independently of the grid where adiabatic dynamics are computed. This “physical grid,” which can be irregular and time dependent, is defined by juxtaposing the surface grids constructed independently for the ocean, land, and sea-ice models. The delocalization method allows taking into account the nonlinearities of vertical fluxes due to heterogeneities in the finescale surface properties that are not resolved by the adiabatic atmospheric dynamics calculations. The impact of delocalizing the physics to fit a given higher resolution surface grid is tested first on experiments where the global atmosphere is forced by observed ocean temperatures. The comparison demonstrates a significant improvement of the predominant variability mode of the outgoing longwave radiation field, corresponding mainly to the seasonal cycle. The delocalized physics method is then tested on an experiment where the General circulation model of the Laboratoire de Météorologie Dynamique is coupled to the Laboratoire d’Océanographie Dynamique et de Climatologie tropical Pacific ocean model. Delocalized physics allow surface fluxes to respond better to fine sea surface temperatures structures like the Legekis waves produced by the ocean model.

Corresponding author address: Dr. Robert Sadourny, Laboratoire de Meteorologie Dynamique, CNRS, 24, rue Lhomond, 75231 Paris, Cedex 05, France.

Email: sadourny@lmd.ens.fr

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