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Generalization of Baroclinic Instability and Rossby Wave Saturation Theory

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Part of the Mathematics of Planet Earth book series (MPE, volume 8)

Abstract

This chapter describes a problem of barotropic and baroclinic instability in realistic zonal and non-zonal basic state on a sphere, using three-dimensional (3D) spectral primitive equations derived by the 3D NMFs. The most unstable mode in a realistic zonal basic state, called Charney mode, appears in mid-latitudes associated with the baroclinicity of the subtropical jet. In a zonally-varying basic state, we find that the unstable modes are modified by the regionality of the local baroclinicity of the basic state. Given the zonally varying barotropic basic state, we find that the barotropically most unstable standing mode appears to be the Arctic Oscillation (AO) mode. The eigensolution of the linear baroclinic model (LBM) in this section is regarded as a generalized extension of the 3D normal mode at the motionless atmosphere to those of an arbitrary climate basic state. Some applications of the nonlinear primitive equation models are presented for the nonlinear life-cycle experiment of baroclinic waves. The saturation of the growing Rossby waves produces the characteristic energy spectrum obeying the squared phase speed of Rossby waves. We call it as the Rossby wave saturation theory which explains the observed energy spectrum of the geostrophic turbulence in the phase speed domain.

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References

  1. Akahori, K. and Yoden, S. (1996). Zonal flow vacillation and bimodality of baroclinic eddy life cycles in a simple global circulation model. J. Atmos. Sci., 54:2349–2361.CrossRefGoogle Scholar
  2. Ambaum, M. H. P., B. J. H. and Stephenson, D. B. (2001). Arctic oscillation or north atlantic oscillation? J. Clim., 14:3495–3507.Google Scholar
  3. Basdevant, C., B. L. and Sadourny, R. (1981). A study of barotropic model flows: Intermittency, waves and predictability. J. Atmos. Sci., 38:2305–2326.Google Scholar
  4. Bengtsson, L. K. (1985). Medium-range forecasting at the ecmwf. issues in atmospheric and oceanic modeling. Advances in Geophysics, 28:3–54.CrossRefGoogle Scholar
  5. Boer, G. J., S. F. and Yu, B. (2001). The signature of the annular modes in the moisture budget. J. Clim., 14:3655–3665.Google Scholar
  6. Branstator, G. (1985). Analysis of general circulation model sea surface temperature anomaly simulations using a linear model. J. Atmos. Sci., 42:2242–2254.CrossRefGoogle Scholar
  7. Chen, W. Y. (1989). Estimate of dynamical predictability from nmc derf experiments. Mon. Wea. Rev., 117:1227–1236.CrossRefGoogle Scholar
  8. Dalcher, A. and Kalnay, E. (1987). Error growth and predictability in operational ECMWF forecasts. Tellus A, 39A:474–491.CrossRefGoogle Scholar
  9. Deser, C. (2000). On the teleconnectivity of the arctic oscillation. Geophys. Res. Lett., 27:779–782.CrossRefGoogle Scholar
  10. Edmon, H.J., H. B. and McIntyre, M. (1980). Eliassen-palm cross-sections for the troposphere. J. Atmos. Sci., 37:2600–2616.Google Scholar
  11. Frederiksen, J. S. and Lee, S. (1998). Is the atmospheric zonal index driven by an eddy feedback? J. Atmos. Sci., 55:3077–3086.CrossRefGoogle Scholar
  12. Fyfe, J. C., G. J. B. and Flato, G. M. (1989). The arctic and antarctic oscillations and their projected changes under global warming. Geophys. Res. Lett., 26:1601–1604.Google Scholar
  13. Golub, G. and van Loan, C. (1983). Matrix Computations. Johns Hopkins.Google Scholar
  14. Hartman, D. L. (1995). A pv view of zonal flow vacillation. J. Atmos. Sci., 52:2561–2670.CrossRefGoogle Scholar
  15. Holloway, G. (1983). E_ects of planetary wave propagation and finite depth on the predictability of atmosphere. J. Atmos. Sci., 40:314–327.CrossRefGoogle Scholar
  16. Itoh, H. (2002). True versus apparent arctic oscillation. Geophys. Res. Lett., 29:1268.CrossRefGoogle Scholar
  17. James, I. N. and James, P. M. (1992). Spatial structure of ultra-low frequency variability of the flow in a simple atmospheric circulation model. Quart. J. Roy. Meteor. Soc., 118:1211–1233.CrossRefGoogle Scholar
  18. Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K., Ropelewski, C.,Wang, J., Leetmaa, A., Reynolds, R., Jenne, R.,, and Joseph, D. (1996). The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77:437–471.CrossRefGoogle Scholar
  19. Kalnay, E., K. M. and Baker, W. E. (1990). Global numerical weather prediction at the national meteorological center. Bull. Amer. Meteor. Soc, 71:1410–1428.Google Scholar
  20. Kalnay, E., L. S. J. and McPherson, R. D. (1998). Maturity of operational numerical weather prediction: Medium range. Bull. Amer. Meteor. Soc, 79:2753–2769.Google Scholar
  21. Karoly, D. J. (1990). The role of transient eddies in the low-frequency zonal variations in the southern hemisphere circulation. Tellus, 42A:41–50.CrossRefGoogle Scholar
  22. Kasahara, A. (1977). Numerical integration of the global barotropic primitive equations with hough harmonic expansions. J. Atmos. Sci., 34:687–701.CrossRefGoogle Scholar
  23. Kimoto, M., J. F.-F. W. M. and Yasutomi, N. (2001). Zonal-eddy coupling and a neutral mode theory for the arctic oscillation. Geophys. Res. Lett., 28:737–740.Google Scholar
  24. Leith, C. E. (1971). Atmospheric predictability and two-dimensional turbulence. J. Atmos. Sci., 28:145–161.zbMATHCrossRefGoogle Scholar
  25. Leith, C. E. and Kraichnan, R. H. (1972). Predictability of turbulent flows. J. Atmos. Sci., 29:1041–1058.CrossRefGoogle Scholar
  26. Limpasuvan, V. and Hartmann, D. L. (2000). Wave-maintained annular mode of climate variability. J. Clim., 13:4414–4429.CrossRefGoogle Scholar
  27. Lorenz, D. J. and Hartmann, D. L. (2001). Eddy-zonal flow feedback in the southern hemisphere. J. Clim., 13:4414–4429.Google Scholar
  28. Lorenz, E. L. (1963). Deterministic nonperiodic flow. J. Atmos. Sci., 20:130–141.MathSciNetzbMATHCrossRefGoogle Scholar
  29. Lorenz, E. N. (1969). The predictability of a flow which possess many scales of motion. Tellus, XXI(3):289–307.Google Scholar
  30. Lorenz, E. N. (1985). The growth of errors in prediction. Turbulence and Predictability in Geophysical Fluid Dynamics and Climate Dynamics.Google Scholar
  31. Marshall, J. and Molteni, F. (1993). Toward a dynamical understanding of planetaryscale flow regimes. J. Atmos. Sci., 50:1792–1818.CrossRefGoogle Scholar
  32. Miyakoda, K., J. S. and Ploshay, J. (1986). One-month forecast experiments-without anomaly boundary forcings. Mon. Wea. Rev., 114:2363–2401.Google Scholar
  33. Molteni, F., R. B.-T. P. and Petroliagis, T. (1996). The ecmwf ensemble prediction system: Method and validation. Quart. J. Roy. Meteor. Soc., 122:73–119.Google Scholar
  34. Navarra, A. (1993). A new set of orthonormal modes for linearized meteorological problems. J. Atmos. Sci., 50:2569–2583.CrossRefGoogle Scholar
  35. Rhines, P. (1975). Waves and turbulence on a beta-plane. J. Fluid Mech., 69:417–443.zbMATHCrossRefGoogle Scholar
  36. Rhines, P. (1979). Geostrophic turbulence. Ann. Rev. Fluid Mech., 11:401–441.zbMATHCrossRefGoogle Scholar
  37. Ringler, T. and Cook, K. H. (1999). Understanding the seasonality of orographically forced stationary waves: Interaction between mechanical and thermal forcing. J. Atmos. Sci., 56:1154–1174.CrossRefGoogle Scholar
  38. Robertson, A. W. (2001). Influence of ocean-atmosphere interaction on the arctic oscillation in two general circulation models. J. Clim., 14:3240–3254.CrossRefGoogle Scholar
  39. Robinson, W. (1996). Does eddy feedback sustain variability in the zonal index? J. Atmos. Sci., 53:3556–3569.CrossRefGoogle Scholar
  40. Satoh, M. (1994). Hadley circulations in radiative-convective equilibrium in an axially symmetric atmosphere. J. Atmos. Sci., 51:1947–1968.CrossRefGoogle Scholar
  41. Shigehisa, Y. (1983). Normal modes of the shallow water equations for zonal wavenumber zero. J. Meteor. Soc. Japan, 61:479–493.CrossRefGoogle Scholar
  42. Shindell, D. T., R. L. M. G. A. S. and Pandolfo, L. (1989). Simulation of recent northern winter climate trends by greenhouse-gas forcing. Nature, 399:452–455.Google Scholar
  43. Shiotani, M. (1990). Low-frequency variations of the zonal mean state of the southern hemisphere troposphere. J. Meteor. Soc. Japan, 68:461–471.CrossRefGoogle Scholar
  44. Shukla, J. (1985). Predictability. issues in atmospheric and oceanic modeling. Advances in Geophysics, 28:87–122.CrossRefGoogle Scholar
  45. Shutts, G. J. (1986). A case study of eddy forcing during an atlantic blocking episode. Adv. in Geophys., 29:135–162.CrossRefGoogle Scholar
  46. Simmons, A. J., Wallace, J. M., and Branstator, G. W. (1983). Barotropic wave propagation and instability, and atmospheric teleconnection patterns. J. Atmos.Sci., 40:1363–1392.CrossRefGoogle Scholar
  47. Stone, P. H. (1978). Baroclinic adjustment. J. Atmos. Sci., 35:561–571.CrossRefGoogle Scholar
  48. Suzuki, I. and Tanaka, H. L. (2007). Teleconnections and the arctic oscillationanalyzed in the barotropic component of the model and observedatmosphere. J. Meteor. Soc. Japan, 85:933–941.CrossRefGoogle Scholar
  49. Tanaka, H. (1985). Global energetics analysis by expansion into three-dimensional normal-mode functions during the FGGE winter. J. Meteor. Soc. Japan, 63:180–200.CrossRefGoogle Scholar
  50. Tanaka, H. (2003). Analysis and modeling of the arctic oscillation using a simple barotropic model with baroclinic eddy forcing. J. Atmos. Sci., 60:1359–1379.CrossRefGoogle Scholar
  51. Tanaka, H. and Kung, E. (1988). Normal-mode expansion of the general circulation during the FGGE year. J. Atmos. Sci., 45:3723–3736.CrossRefGoogle Scholar
  52. Tanaka, H. and Kung, E. (1989). A study of low-frequency unstable planetary waves in realistic zonal and zonally varing basic states. Tellus, 41A:179–199.CrossRefGoogle Scholar
  53. Tanaka, H. and Tokinaga, H. (2002). Baroclinic instability in high latitudes induced by polar vortex: A connection to the arctic oscillation. J. Atmos. Sci., 59:69–82.CrossRefGoogle Scholar
  54. Tanaka, H. L. (1991). A numerical simulation of amplification of low-frequency planetary waves and blocking formations by the upscale energy cascade. Mon. Wea. Rev., 119:2919–2935.CrossRefGoogle Scholar
  55. Tanaka, H. L. (1998). Numerical simulation of a life-cycle of atmospheric blocking and the analysis of potential vorticity using a simple barotropic model. J. Meteor. Soc. Japan, 76:983–1008.CrossRefGoogle Scholar
  56. Tanaka, H. L. and Kasahara, A. (1992). On thenormal modes of laplace’s tidal equations for zonal wavenumber zero. Tellus, 44A:18–32.CrossRefGoogle Scholar
  57. Tanaka, H. L. and Matsueda, M. (2005). Arctic oscillation analyzed as a singular eigenmode of the global atmosphere. J. Meteor. Soc. Japan, 83:611–619.CrossRefGoogle Scholar
  58. Tanaka, H. L. and Nohara, D. (2000). A study of deterministic predictability for the barotropic component of the atmosphere. Science Report, Institute of Geoscience, University of Tsukuba, 21:1–21.Google Scholar
  59. Tanaka, H. L. and Sun, S. (1990). A study of baroclinic energy source for large-scale atmospheric normal modes. J. Atmos. Sci., 47:2674–2695.CrossRefGoogle Scholar
  60. Tanaka, H. L., W. Y. and Kanda, T. (2004). Energy spectrum proportional to the squared phase speed of rossby modes in the general circulation of the atmosphere. Geophys. Res. Lett., 31(13):13109.Google Scholar
  61. Thompson, D. W. J. and Wallace, J. M. (1998). The arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophy. Res. Lett., 25:1297–1300.CrossRefGoogle Scholar
  62. Toth, Z. and Kalnay, E. (1997). Ensemble forecasting at NMC: The generation of perturbations. Mon. Wea. Rev., 125:3297–3319.CrossRefGoogle Scholar
  63. Vallis, G. K. (1983). On the predictability of quasi-geostrophic flow: The e_ect of beta and baroclinicity. J. Atmos. Sci., 40:10–27.CrossRefGoogle Scholar
  64. Wallace, J. M. and Gutzler, D. S. (1981). Teleconnections in the geopotential height field during the northern hemisphere winter. Mon. Wea. Rev., 109:784–812.CrossRefGoogle Scholar
  65. Wallace, J. M. and Thompson, D. W. J. (2002). The pacific center of action of the northern hemisphere annular mode: Real or artifact? J. Clim., 15:1987–1991.CrossRefGoogle Scholar
  66. Watanabe, M. and Jin, F.-F. (2004). Dynamical prototype of the arctic oscillation as revealed by a neutral singular vector. J. Clim., 17:2119–2138.CrossRefGoogle Scholar
  67. Yamazaki, K. and Shinya, Y. (1999). Analysis of the arctic oscillation simulated by agcm. J. Meteor. Soc. Japan, 77:1287–1298.CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Center for Computational SciencesUniversity of TsukubaTsukubaJapan

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