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Kim, Young-Joon; Hogan, Timothy F. (2004)
Publisher: Co-Action Publishing
Journal: Tellus A
Languages: English
Types: Article

Classified by OpenAIRE into

arxiv: Astrophysics::Earth and Planetary Astrophysics, Physics::Atmospheric and Oceanic Physics, Physics::Fluid Dynamics
Various drag mechanisms are currently parametrized in numerical models of the atmosphere. For global models that include the middle atmosphere in particular, these mechanisms profoundly affect weather forecast as well as climate simulation.We have developed an extended-top version of the Navy Operational Global Atmospheric Prediction System (NOGAPS) to include the middle atmosphere by modifying some physical parametrizations and the vertical coordinate. We performed a series of ensemble simulations corresponding to January 2000 for investigating the response of the model to various drag mechanisms, such as mountain drag, orographic gravity wave drag, surface friction drag, and artificial model top drag. Based on the monthly mean fields obtained from the simulations, we first investigate the effect of gravity wave drag due to its direct impact through planetary wave activity as well as indirect impact through induced meridional circulation.We discuss the difficulties in partitioning between the mountain drag due to resolved orography and the gravity wave drag due to unresolved orography, first using conventional diagnostic measures. From analyses of the atmospheric angular momentum budget, we show that various model drag mechanisms when modified interact with one another by redistributing their drag while conserving the total amount. In particular, an overestimation of mountain drag is accompanied by an underestimation of gravity wave drag in the Northern Hemisphere mid-latitudes to conserve the total amount of drag in the model while likely breaking an optimal balance among the mechanisms. Under such a condition, the inclusion of a gravity wave drag parametrization – even if the drag amount itself is reasonable – does not necessarily improve the performance of the model. Diagnosis of this type of imbalance is not clear by conventional monthly mean fields of variables. In this paper, we argue that the budget of atmospheric angular momentum is a useful measure to diagnose impact of such changes in model physics with regard to the partition and balance among drag mechanisms. We also discuss the experimental results that led to the replacement of silhouette orography by mean orography in our model.
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    • Andrews, D. G., Holton, J. R. and Leovy, C. B. 1987. Middle Atmospheric Dynamics. Academic, New York, 489 pp.
    • Andrews, D. G. and McIntyre, M. E. 1976. Planetary waves in horizontal and vertical shear: The generalized Eliassen-Palm relation and the mean zonal acceleration. J. Atmos. Sci. 33, 2031-2048.
    • Barker, E. 1992. Design of the Navy's multivariate optimum interpolation analysis system. Wea. Forecasting 7, 220-231.
    • Bell, M. J., Hide, R. and Sakellarides, G. 1991. Atmospheric angular momentum forecasts as novel tests of global numerical weather prediction models. Phil. Trans. R. Soc. London A 334, 55-92.
    • Boer, G. J. 1990. Earth-atmosphere exchange of angular momentum simulated in a general circulation model and implications for the length of day. J. Geophys. Res. 95, 5511-5531.
    • Boer, G. J. and Lazare, M. 1988. Some results concerning the effect of horizontal resolution and gravity-wave drag on simulated climate. J. Climate 1, 789-806.
    • Boville, B. A. 1984. The influence of the polar night jet on the tropospheric circulation in a GCM. J. Atmos. Sci. 41, 1132-1142.
    • Boyd, J. 1976. The non-interaction of waves with the zonally averaged flow on a spherical earth and the interrelationships of eddy fluxes of energy, heat and momentum. J. Atmos. Sci. 33, 2285-2291.
    • Broad, A. S. 1996. High-resolution numerical-model integrations to validate gravity-wave-drag parametrization schemes: a case study. Q. J. R. Meteorol. Soc. 122, 1625-1653.
    • Chou, M.-D. and Peng, L. 1983. A parametrization of the absorption in the 15 mm CO2 spectral region with application to climate sensitivity studies. J. Atmos. Sci. 40, 2183-2192.
    • Chun, H.-Y. and Baik, J.-J. 1998. Momentum flux by thermally induced internal gravity waves and its approximation for large-scale models. J. Atmos. Sci. 55, 3299-3310.
    • Chun, H.-Y., Song, M.-D., Kim, J.-W. and Baik, J.-J. 2001. Effects of gravity wave drag induced by cumulus convection on the atmospheric general circulation. J. Atmos. Sci. 58, 302-319.
    • Edmon, H. J. Jr., Hoskins, B. J. and McIntyre, M. E. 1980. Eliassen-Palm cross-sections for the troposphere. J. Atmos. Sci. 37, 2600-2616.
    • Egger, J. 2003. Gravity wave drag and global angular momentum: geostrophic adjustment processes. Tellus 55A, 419-425.
    • Emanuel, K. A. and Zivkovic-Rothman, M. 1999. Development and evaluation of a convection scheme for use in climate models. J. Atmos. Sci. 56, 1766-1782.
    • Goerss, J. S. and Phoebus, P. 1992. The Navy's operational atmospheric analysis. Wea. Forecasting 7, 232-249.
    • Gregory, D., Shutts, G. J. and Mitchell, J. R. 1998. A new gravity-wavedrag scheme incorporating anisotropic orography and low-level wave breaking: impact upon the climate of the UK Meteorological Office Unified Model. Q. J. R. Meteorol. Soc. 124, 463-493.
    • Harshvardhan, Davies, R., Randall, D. and Corsetti, T. 1987. A fast radiation parametrization for atmospheric circulation models. J. Geophys. Res. 92, 1009-1016.
    • Haynes, P. H., Marks, C. J., McIntyre, M. E., Shepherd, T. G. and Shine, K. P. 1991. On the 'downward control' of extratropical diabatic circulations by eddy-induced mean zonal forces. J. Atmos. Sci. 48, 651-678.
    • Hogan, T. and Rosmond, T. 1991. The description of the Navy Operational Global Atmospheric Prediction System's spectral forecast model. Mon. Wea. Rev. 119, 1186-1815.
    • Hogan, T., Rosmond, T. and Gelaro, R. 1991. The NOGAPS forecast model: a technical description. NOARL Report 13, 220 pages.
    • Hogan, T. and Brody, L. 1993. Sensitivity Studies of the Navy's global forecast model parametrizations and evaluation of improvements to NOGAPS. Mon. Wea. Rev. 121, 2373-2395.
    • Huang, H. P., Sardeshmukh, P. D. and Weickmann, K. M. 1999. The balance of global angular momentum in a long-term atmospheric data set. J. Geophys. Res. 104, 2031-2040.
    • Kim, Y.-J. 1996. Representation of subgrid-scale orographic effects in a general circulation model: Part I. Impact on the dynamics of simulated January climate. J. Climate 9, 2698-2717.
    • Kim, Y.-J. and Arakawa, A. 1995. Improvement of orographic gravitywave parametrization using a mesoscale gravity-wave model. J. Atmos. Sci. 52, 1875-1902.
    • Kim, Y.-J., Eckermann, S.D. and Chun, H.-Y. 2003. An overview of the past, present and future of gravity-wave drag parametrization for numerical climate and weather prediction models. Atmosphere-Ocean 41, 65-98 (available on-line at http://www.cmos.ca/Ao/Papersfull/v410105.pdf).
    • Kim, Y.-J., Farrara, J. D. and Mechoso, C. R. 1998. Sensitivity of AGCM simulations to modifications in the ozone distribution and refinements in selected physical parametrizations. J. Meteorol. Soc. Japan 76, 695- 709.
    • Klinker, E. and Sardeshmukh, P. D. 1992. The diagnosis of mechanical dissipation in the atmosphere from large-scale balance requirements. J. Atmos. Sci. 49, 608-627.
    • Kodera, K., Yamazaki, K., Chiba, M. and Shibata, K. 1990. Downward propagation of upper stratospheric mean zonal wind perturbation to the troposphere. Geophy. Res. Lett. 17, 1263-1266.
    • Kuroda, Y. 2002. Relationship between the polar night jet oscillation and the annular mode. Geophy. Res. Lett. 29, 81.
    • Lejena¨s, H., Madden, R. A. and Hack, J. J. 1997. Global atmospheric angular momentum and Earth-atmosphere exchange of angular momentum simulated in a general circulation model. J. Geophys. Res. 102, 1931-1941.
    • Lott, F. and Miller, M. J. 1997. A new subgrid-scale orographic parametrization: its formulation and testing. Q. J. R. Meteorol. Soc. 123, 101-127.
    • Louis, J. F. 1979. A parametric model of vertical eddy fluxes in the atmosphere. Boundary Layer Meteorol. 17, 187-202.
    • McFarlane, N. A. 1987. The effect of orographically excited gravitywave drag on the general circulation of the lower stratosphere and troposphere. J. Atmos. Sci. 44, 1775-1800.
    • Milton, S. F. and Wilson, C. A. 1996. The impact of parametrized subgrid-scale orographic forcing on systematic errors in global NWP model. Mon. Wea. Rev. 124, 2023-2045.
    • Palmer, T. N., Shutts, G. J. and Swinbank, R. 1986. Alleviation of a systematic westerly bias in general circulation and numerical weather prediction models through an orographic gravity wave drag parametrization. Q. J. R. Meteorol. Soc. 112, 1001-1039.
    • Peixoto, J. P. and Oort, A. H. 1992. Physics of Climate. American Institute of Physics, New York, 520 pp.
    • Robinson, W. A. 1986. The application of the quasi-geostrophic Eliassen-Palm flux to the analysis of stratospheric data. J. Atmos. Sci. 43, 1017-1023.
    • Rontu, L. and Boutier, F. 2002. In: HIRLAM Workshop on Mesoscale Modelling, Dublin, 14-16 October (available at http://hirlam.knmi.nl).
    • Rontu, L., Sattler, K. and Sigg, R. 2002. Parametrization of subgridscale orography effects in HIRLAM. HIRLAM Technical Report 56 (available at http://hirlam.knmi.nl).
    • Rosmond, T. E. 1992. The design and testing of the Navy operational global atmospheric prediction system. Wea. Forecasting 7, 262-272.
    • Salstein, D. A., Kann, D. M., Miller, A. J. and Rosen, R. D. 1993. The sub-bureau for atmospheric angular momentum of the International Earth Rotation Service: a meteorological data center with geodetic applications. Bull. Am. Meteorol. Soc. 74, 67-80.
    • Scinocca, J. F. and McFarlane, N. A. 2000. The parametrization of drag induced by stratified flow over anisotropic topography. Q. J. R. Meteorol. Soc. 126, 2353-2393.
    • Shepherd, T. G., Semeniuk, K. and Koshyk, J. N. 1996. Sponge layer feedbacks in middle-atmosphere models. J. Geophys. Res. 101, 23,447-23,464.
    • Slingo, J. M. 1987. The development and verification of a cloud prediction scheme in the ECMWF model. Q. J. R. Meteorol. Soc. 113, 899-927.
    • Swinbank, R. 1985. The global atmospheric angular-momentum balance inferred from analyses made during the FGGE. Q. J. R. Meteorol. Soc. 111, 977-992.
    • Teixeira, J. and Hogan, T. F. 2002. Boundary layer clouds in a global atmospheric model: simple cloud cover parametrizations. J. Climate 15, 1261-1276.
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