Global Atmospheric Modelling

  • Robert Sadourny
Conference paper
Part of the NATO ASI Series book series (volume 22)


The history of the numerical modelling of atmospheric motion is intimately linked with the history of weather forecasting which started with World War I. The first try in numerical weather prediction was Richardson (1922)’s, who both invented finite difference modelling and… massively parallel processing, as he viewed a network of parallel personal computers (the brains and hands of individuals) passing and receiving individually processed information to their neighbours in a huge mass-production room. With regard to parallel processing, he was in advance by three quarters of a century. With regard to numerical analysis, he was too early by a quarter of a century: his calculation failed because he did not know about the CFL criterion and choose a time step too large for his horizontal resolution. One must add that he envisioned an associated optimum data coverage by dreaming of a Cartesian observing station network in exact coincidence with the computational grid: which promised a brilliant future to the small city of Romorantin, in the centre of France, as a major meteorological observing station.


General Circulation Model Potential Vorticity Numerical Weather Prediction Shallow Water Equation Atmospheric Motion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Arakawa, A. (1966): Computational design for long-term numerical integration of the equations of fluid motion. Part I: Two-dimensional incompressible flow. J. Comp. Phys., 1, 119–143.CrossRefGoogle Scholar
  2. Arakawa, A., W. H. Schubert (1974): Interaction of cumulus cloud ensemble with the large- scale environment. J. Atmos. Sci., 31, 674–701.CrossRefGoogle Scholar
  3. Basdevant, C., B. Legras, R. Sadourny, M. Béland (1981): A study of barotropic model flows: Intermittency, waves and predictability. J. Atmos. Sci., 38, 2305–2326.CrossRefGoogle Scholar
  4. Betts, A. K. (1986): New convective adjustment scheme. Part I. Observational and theoretical bases. Quart. J. Roy. Meteor. Soc., 112, 677–691.Google Scholar
  5. Betts, A. K., M. Miller (1986): New convective adjustment scheme. Part II. Single column test using GATE wave and BOMEX, APEX and Arctic Air Mass data sets. Quart. J. Roy. Met. Soc., 112, 693–709.Google Scholar
  6. Cess, R.D., G.L. Potter, J.P. Blanchet, G.J. Boer, A.D. Del Genio, M. Déqué, V. Dymnikov, V. Galin, W.L. Gates, S.J. Ghan, J.T. Kiehl, A.A. Lacis, H. Le Treut, Z.X. Li, X.Z. Liang, B.J. McAvaney, V.P. Meleshko, J.F.B. Mitchell, J.J. Morcrette, D.A. Randall, L. Rikus, E. Roeckner, J.F. Royer, U. Schlese, D.A. Sheinin, A. Slingo, A.P. Sokolov, K.E. Taylor, W.M. Washington, R.T. Wetherald, I. Yagai M.H. Zhang, 1990: Intercomparison and interpretation of climate feedback processes in nineteen atmospheric general circulation models. J. Geophys. Res.. 95. 16,601–16,615.Google Scholar
  7. Courtier, Ph., C. Freydier, J.F. Geleyn, F. Rabier,M. Rochas (1991): The ARPÈGE Project at Météo France. In: Numerical Methods in Atmospheric Models, II, 193–231, European Centre for Medium Range Weather Forecasts Seminar Proceedings.Google Scholar
  8. Held, I.M., A.Y. Hou (1980): Nonlinear axially symmetric circulations in a nearly inviscid atmosphere. J. Atmos. Sci., 37, 515–533.CrossRefGoogle Scholar
  9. Hortal, M., A.J. Simmons (1991): Use of reduced Gaussian grids in spectral models. Mon. Wea. Rev., 119, 1057–1074.CrossRefGoogle Scholar
  10. Krishnamurti, T.N. (1969): An experiment in numerical prediction in equatorial latitudes. Quart. J. Roy. Meteor. Soc., 95, 594–620.CrossRefGoogle Scholar
  11. Mesinger, F., Z.I. Janjic, S. Mickovic, D. Gavrilov, D.G. Deaven (1988): The step-mountain coordinate: model description and performance for cases of Alpine lee cyclogenesis and for a case of Appalachian redevelopment. Mon. Wea. Rev., 116, 1493–1518.CrossRefGoogle Scholar
  12. Manabe, S., R.F. Strickler (1964): Thermal equilibrium of the atmosphere with the convective adjustment. J. Atmos. Sci., 21, 361–385.CrossRefGoogle Scholar
  13. Mellor, G.L., T. Yamada (1974): A hierarchy of turbulence closure models for planetary boundary layers. J. Atmos. Sci., 31, 1791–1806.CrossRefGoogle Scholar
  14. Morcrette, J.-J., L. Smith and Y. Fouquart (1986): Pressure and temperature dependence of the absorption in longwave radiation parameterizations. Beitr. Phys. Atmosph., 59, 455–468.Google Scholar
  15. Orszag, S.A. (1970): Transform method for calculation of vector-coupled sums: application to the spectral form of the voticity equation. J. Atmos. Sci., 27, 890–895.CrossRefGoogle Scholar
  16. Phillips, N.A. (1957): A coordinate system having some special advantages for numerical forecasting. J. Meteorol., 14, 184–185.CrossRefGoogle Scholar
  17. Prather, (1988): Numerical advection by conservation of second-order moments. J. Geophys. Res., 91, 6671–6681.Google Scholar
  18. Richardson, L.F. (1922): Weather prediction by numerical process. Cambridge University Press, 236 pp.Google Scholar
  19. Robert, J. Sommeria (1991): Statistical equilibrium states for two-dimensional flows. J. Fluid Mech., 229, 291–310.CrossRefGoogle Scholar
  20. Robert, A.J. (1982): A semi-Lagrangian and semi-implicit numerical integration scheme for the primitive meteorologicall equations. J. Meteor. Soc. Japan, 60, 319–324.Google Scholar
  21. Sadourny, R., A. Arakawa, Y. Mintz (1968): Integration of the nondivergent barotropic vorticity equation with an icosahedral-hexagonal grid on the sphere. Mon. Wea. Rev., 96, 351–356.CrossRefGoogle Scholar
  22. Sadourny, R. (1975a): The dynamics of finite-difference models of the shallow water equations. J. Atmos. Sci., 32, 680–689.CrossRefGoogle Scholar
  23. Sadourny, R. (1975b): Compressible model flows on the sphere. J. Atmos. Sci., 32, 2103–2110.CrossRefGoogle Scholar
  24. Sadourny, R., C. Basdevant (1985): Parameterization of sub-grid scale barotropic and baroclinic eddies: Anticipated Potential Vorticity Method. J. Atmos. Sci., 42, 1353–1363.CrossRefGoogle Scholar
  25. Schmidt, F. (1977): Variable fine mesh in spectral global model. Beitr. Phys. Atmos., 50, 211–217.Google Scholar
  26. Sharma, O.P., H. Upadhyaya, Th. Braine-Bonnaire, R. Sadourny (1987): Experiments on regional forecasting using a stretched-coordinate general circulation model. J. Meteorol. Soc. Japan, Special Volume on Short- and Medium-Range Numerical Weather Prediction.Google Scholar
  27. Simmons, A, D. Burridge (1981): An energy and angular momentum conserving vertical finite difference scheme in hybrid vertical coordinate. Mon. Wea. Rev., 109, 758–766.CrossRefGoogle Scholar
  28. Smagorinsky, J. (1963): General circulation experiments with the primitive equations. I. The basic experiment. Mon. Wea. Rev., 91, 99–164.Google Scholar
  29. Staniforth, A.N., H.L. Mitchell (1978): A variable-resolution finite-element technique for regional forecasting with the primitive equations. Mon. Wea. Rev., 106, 439–447.CrossRefGoogle Scholar
  30. Sundqvist, H. (1978): Parametrisation for non convective condensation including prediction of cloud water content. Quart. J. Roy. Meteor. Soc., 104, 677–690.CrossRefGoogle Scholar
  31. Tiedtke, M. (1989): Comprehensive mass flux scheme for cumulus parametrisation in large- scale models. Mon. Wea. Rev., 117, 1779–1800.Google Scholar
  32. Williamson, D. (1968): Integration of the barotropic vorticity equation on a spherical geodesic grid. Tellus, 20, 642–653.CrossRefGoogle Scholar
  33. White, A.A., R.A. Bromley (1988) : A new set of dynamical equations for use in numerical weather prediction and global climate models. Meteorological Office, Met O 13 Branch memo.Google Scholar
  34. Zhu, Z., J. Thuburn, B.J. Hoskins, P.H. Haynes (1992): A vertical finite difference scheme based on a hybrid s-q-p coordinate. Mon. Wea. Rev., 120, 851–862.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Robert Sadourny
    • 1
  1. 1.Laboratoire de Météorologie Dynamique du CNRSÉcole Normale SupérieureParis Cedex 05France

Personalised recommendations