A Uniform- and Variable-Resolution Stretched-Grid GCM Dynamical Core with Realistic Orography

Michael S. Fox-Rabinovitz Department of Meteorology/ESSIC, University of Maryland at College Park, College Park, Maryland, and Data Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Georgiy L. Stenchikov Department of Environmental Sciences, Rutgers–The State University of New Jersey, New Brunswick, New Jersey

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Max J. Suarez Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Lawrence L. Takacs Data Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Ravi C. Govindaraju Data Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Abstract

The impact of introducing a realistic orographic forcing into a uniform- and variable-resolution stretched-grid GCM dynamical core is investigated by performing long-term and medium-range integrations. Comparisons are made between various stretched-grid simulations and a control that consists of a uniform grid integration at high resolution. These comparisons include those where the orography has and has not been filtered to eliminate small-scale noise. Results from the region of interest with highest resolution show that 1) the stretched-grid GCM provides an efficient downscaling over the area of interest, that is, it properly simulates not only large-scale but also mesoscale features; and 2) the introduction of orography has a greater impact than the effect of stretching. Results presented here suggest that dynamical core integrations with both uniform and stretched grids should consider orographic forcing as an integral part of the model dynamics.

* Additional affiliation: General Sciences Corporation, Beltsville, Maryland.

Corresponding author address: Dr. Michael S. Fox-Rabinovitz, Department of Meteorology, University of Maryland at College Park, College Park, MD 20742.

Abstract

The impact of introducing a realistic orographic forcing into a uniform- and variable-resolution stretched-grid GCM dynamical core is investigated by performing long-term and medium-range integrations. Comparisons are made between various stretched-grid simulations and a control that consists of a uniform grid integration at high resolution. These comparisons include those where the orography has and has not been filtered to eliminate small-scale noise. Results from the region of interest with highest resolution show that 1) the stretched-grid GCM provides an efficient downscaling over the area of interest, that is, it properly simulates not only large-scale but also mesoscale features; and 2) the introduction of orography has a greater impact than the effect of stretching. Results presented here suggest that dynamical core integrations with both uniform and stretched grids should consider orographic forcing as an integral part of the model dynamics.

* Additional affiliation: General Sciences Corporation, Beltsville, Maryland.

Corresponding author address: Dr. Michael S. Fox-Rabinovitz, Department of Meteorology, University of Maryland at College Park, College Park, MD 20742.

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  • Cote, J., 1997: Variable resolution techniques for weather prediction. Meteor. Atmos. Phys.,63, 31–38.

  • ——, M. Roch, A. Staniforth, and L. Fillion, 1993: A variable-resolution semi-Lagrangian finite-element global model of the shallow-water equations. Mon. Wea. Rev.,121, 231–243.

  • ——, S. Gravel, A. Metot, A. Patoine, M. Roch, and A. Staniforth, 1998: The operational CMC/MRB Global Environmental Multiscale (GEM) model. Part I: Design considerations and formulation. Mon. Wea. Rev.,126, 1373–1395.

  • Courtier, P., and J.-F. Geleyn, 1988: A global numerical weather prediction model with variable resolution: Application to the shallow-water equations. Quart. J. Roy. Meteor. Soc.,114, 1321–1346.

  • Deque, M., and J. P. Piodelievre, 1995: High resolution climate stimulation over Europe. Climate Dyn.,11, 321–339.

  • Dickinson, R. E., R. M. Errico, F. Giorgi, and G. T. Bates, 1989: A regional climate model for the western United States. Climatic Change,15, 383–422.

  • Fletcher, C. A. J., 1988: Computational Techniques for Fluid Dynamics. Vol. 2. Springer-Verlag, 541 pp.

  • Fox-Rabinovitz, M. S., 1988: Dispersion properties of some regular and irregular grids used in atmospheric models. Preprints, Eighth Conf. on Numerical Weather Prediction, Baltimore, MD, Amer. Meteor. Soc., 784–789.

  • ——, L. V. Stenchikov, M. J. Suarez, and L. L. Takacs, 1997: A finite-difference GCM dynamical core with a variable resolution stretched grid. Mon. Wea. Rev.,125, 2943–2968.

  • Giorgi, F., 1990: Simulation of regional climate using a limited area model nested in a GCM. J. Climate,3, 941–963.

  • ——, 1995: Perspectives for regional earth system modeling. Global Planet. Change,10, 23–42.

  • Hardiker, V., 1997: A global numerical weather prediction model with variable resolution. Mon. Wea. Rev.,125, 349–360.

  • Held, I. M., and M. J. Suarez, 1994: A benchmark calculation for the dry dynamical cores of atmospheric general circulation models. Bull. Amer. Meteor. Soc.,75, 1825–1830.

  • Lanczos, C., 1966: Discourse on Fourier Series. Hafner Publishing, 255 pp.

  • Lindzen, R. S., and M. S. Fox-Rabinovitz, 1989: Consistent vertical and horizontal resolution. Mon. Wea. Rev.,117, 2575–2583.

  • Oliger, J., and A. Sundstrom, 1978: Theoretical and practical aspects of some initial boundary value problems in fluid dynamics. SIAM J. Appl. Math.,35, 419–446.

  • Paegle, J., 1989: A variable resolution global model based upon Fourier and finite-element representation. Mon. Wea. Rev.,117, 583–606.

  • Pielke, R. A., and Coauthors, 1992: A comprehensive meteorological modeling system—RAMS. Meteor. Atmos. Phys.,49, 69–91.

  • Roache, P. J., 1976: Computational Fluid Dynamics. Hermosa Publishers, 446 pp.

  • Shapiro, R., 1970: Smoothing, filtering and boundary effects. Rev. Geophys. Space Phys.,8, 359–387.

  • Staniforth, A., 1995: Regional modeling: Theoretical discussion. WMO PWPR Rep. Series, No. 7, WMO/TD-No. 699, 61 pp.

  • ——, 1997: Regional modeling: A theoretical discussion. Meteor. Atmos. Phys.,63, 15–29.

  • ——, and H. Mitchell, 1978: A variable resolution finite element technique for regional forecasting with primitive equations. Mon. Wea. Rev.,106, 439–447.

  • ——, and R. Daley, 1979: A baroclinic finite element model for regional forecasting with the primitive equations. Mon. Wea. Rev.,107, 107–121.

  • Suarez, M. J., and L. L. Takacs, 1995: Documentation of the Aries/GEOS dynamical core, version 2. NASA Tech. Memo. 104606, NASA Goddard Space Flight Center, Greenbelt, MD, 103 pp. [Available from Data Assimilation Office, Laboratory of Atmospheres, NASA Goddard Space Flight Center, Greenbelt, MD 20771].

  • Takacs, L. L., and M. J. Suarez, 1996: Dynamical aspects of climate simulations using the GEOS GCM, version 10. NASA Tech. Memo. 104606, 56 pp. [Available from Data Assimilation Office, Laboratory of Atmospheres, NASA Goddard Space Flight Center, Greenbelt, MD 20771].

  • ——, A. Molod, and T. Wang, 1994: Goddard Earth Observing System (GEOS) General Circulation Model (GCM), version 1. NASA Tech. Memo. 104606, NASA Goddard Space Flight Center, Greenbelt, MD, 97 pp. [Available from Data Assimilation Office, Laboratory of Atmospheres, NASA Goddard Space Flight Center, Greenbelt, MD 20771].

  • Vichnevetsky, R., 1987: Wave propagation and reflection in irregular grids for hyperbolic equations. Appl. Numer. Math.,2, 133–166.

  • Yessad, K., and P. Benard, 1996: Introduction of local mapping factor in the spectral part of the Meteo-France global variable mesh numerical forecast model. Quart. J. Roy. Meteor. Soc.,122, 1701–1719.

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