• Bjerknes, J., 1964: Atlantic air–sea interaction. Advances in Geophysics, Vol. 10, Academic Press, 1–82.

  • Deser, C., and M. L. Blackmon, 1993: Surface climate variations over the North Atlantic Ocean during winter: 1900–1989. J. Climate,6, 1743–1753.

  • Frankignoul, C., and P. Müller, 1979: Quasi-geostrophic response of an infinite β-plane ocean to stochastic forcing by the atmosphere. J. Phys. Oceanogr.,9, 104–127.

  • ——, ——, and E. Zorita, 1997: A simple model of the decadal response of the ocean to stochastic wind forcing. J. Phys. Oceanogr.,27, 1533–1546.

  • Greatbatch, R. J., and S. Zhang, 1995: An interdecadal oscillation in an idealized ocean basin forced by constant heat flux. J. Climate,8, 81–91.

  • Grötzner, A., M. Latif, and T. P. Barnett, 1998: A decadal climate cycle in the North Atlantic Ocean as simulated by the ECHO coupled GCM. J. Climate,11, 831–847.

  • Haidvogel, D. B., J. C. McWilliams, and P. R. Gent, 1992: Boundary current separation in a quasigeostrophic, eddy-resolving ocean circulation model. J. Phys. Oceanogr.,22, 882–902.

  • Hasselmann, K., 1976: Stochastic climate models. Part I. Theory. Tellus,28, 473–484.

  • Holland, W. R., 1978: The role of mesoscale eddies in the general circulation of the ocean—Numerical experiments using a wind-driven quasi-geostrophic model. J. Phys. Oceanogr.,8, 363–392.

  • Hurrell, J. W., 1995: Decadal trends in the North Atlantic Oscillation:Regional temperatures and precipitation. Science,269, 676–679.

  • Jiang, S., F.-F. Jin, and M. Ghil, 1995: Multiple equilibria, periodic, and aperiodic solutions in a wind-driven, double-gyre, shallow-water model. J. Phys. Oceanogr.,25, 764–786.

  • Jin, F.-F., 1997: A theory of interdecadal climate variability of the North Pacific ocean–atmosphere system. J. Climate,10, 1821–1835.

  • Kushnir, Y., 1994: Interdecadal variations in North Atlantic sea surface temperature and associated atmospheric conditions. J. Climate,7, 141–157.

  • Latif, M., and T. B. Barnett, 1994: Causes of decadal climate variability over the North Pacific and North America. Science,266, 634–637.

  • ——, and ——, 1996: Decadal climate variability over the North Pacific and North America: Dynamics and predictability. J. Climate,9, 2407–2423.

  • Levitus, S., J. I. Antonov, and T. P. Boyer, 1994: Interannual variability of temperature at a depth of 125 m in the North Atlantic Ocean. Science,266, 96–99.

  • McCalpin, J., and D. B. Haidvogel, 1996: Phenomenology of the low-frequency variability in a reduced-gravity quasigeostrophic double-gyre model. J. Phys. Oceanogr.,26, 739–752.

  • Münnich, M., M. Latif, S. Venske, and E. Maier-Reimer, 1998: Decadal oscillations in a simple coupled model. J. Climate,11, 3309–3319.

  • Saravanan, R., and J. C. McWilliams, 1997: Stochasticity and spatial resonance in interdecadal climate fluctuations. J. Climate,10, 2299–2320.

  • Weaver, A. J., and E. S. Sarachik, 1991: Evidence for decadal variability in an ocean general circulation model: An advective mechanism. Atmos–Ocean,29, 197–231.

  • Weng, W., and J. D. Neelin, 1998: On the role of ocean–atmosphere interaction in midlatitude interdecadal variability. Geophys. Res. Lett.,25, 167–170.

  • White, W. B., 1977: Annual forcing of baroclinic long waves in the tropical North Pacific Ocean. J. Phys. Oceanogr.,7, 50–61.

  • Winton, M., and E. S. Sarachik, 1993: Thermohaline oscillations induced by strong steady salinity forcing of ocean general circulation models. J. Phys. Oceanogr.,23, 1713–1724.

  • Wright, P. B., 1988: An atlas based on the COADS data set: Fields of mean wind, cloudiness and humidity at the surface of the global ocean. Max-Planck-Institut für Meteorologie Rep. No. 14, 68 pp. [Available from Max-Planck-Institut für Meteorologie, Bundesstrasse 55, D-20146 Hamburg, Germany.].

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Decadal Variability in a Simplified Wind-Driven Ocean Model

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  • 1 Meteorologisches Institut, Universität Hamburg, Hamburg, Germany
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Abstract

The impact of an unsteady wind forcing on oceanic low-frequency variability is conceptually studied using a reduced-gravity shallow-water model. A time-averaged wind forcing and a simple ocean–atmosphere coupling is completed by a stochastic component (spatially coherent white noise) representing the effect of atmospheric transient eddies. To account for the observed concentration of eddy activity along the North Atlantic and North Pacific storm tracks the variance of the stochastic forcing is chosen to be spatially inhomogeneous. Low-frequency variability of the basin-averaged energetics shows a dominant spectral peak with an amplitude depending on the inhomogeneity of the stochastic forcing and the time-averaged wind stress. The period of the variability is unexpected considering baroclinic Rossby waves forced by the ocean–atmosphere coupling only. This variability can be explained by “spatial resonance” of the forced baroclinic Rossby wave and the Reynolds momentum flux induced by the spatially inhomogeneous white noise.

Corresponding author address: Dr. Frank Lunkeit, Meteorologisches Institut der Universität Hamburg, Bundesstraße 55, D-20146 Hamburg, Germany.

Email: lunkeit@dkrz.de

Abstract

The impact of an unsteady wind forcing on oceanic low-frequency variability is conceptually studied using a reduced-gravity shallow-water model. A time-averaged wind forcing and a simple ocean–atmosphere coupling is completed by a stochastic component (spatially coherent white noise) representing the effect of atmospheric transient eddies. To account for the observed concentration of eddy activity along the North Atlantic and North Pacific storm tracks the variance of the stochastic forcing is chosen to be spatially inhomogeneous. Low-frequency variability of the basin-averaged energetics shows a dominant spectral peak with an amplitude depending on the inhomogeneity of the stochastic forcing and the time-averaged wind stress. The period of the variability is unexpected considering baroclinic Rossby waves forced by the ocean–atmosphere coupling only. This variability can be explained by “spatial resonance” of the forced baroclinic Rossby wave and the Reynolds momentum flux induced by the spatially inhomogeneous white noise.

Corresponding author address: Dr. Frank Lunkeit, Meteorologisches Institut der Universität Hamburg, Bundesstraße 55, D-20146 Hamburg, Germany.

Email: lunkeit@dkrz.de

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