Editorial Type:
Article
Article Type:
Research Article

Estimating the Effect of Stochastic Wind Stress Forcing on ENSO Irregularity

Bruno Blanke Laboratoire d’Océanographie Dynamique et de Climatologie, Unité Mixte de Recherche, Centre National de la Recherche Scientifique, Paris, France

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J. David Neelin Department of Atmospheric Sciences and Institute of Geophysics and Planetary Physics, University of California, Los Angeles,Los Angeles, California

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David Gutzler Departments of Geography and Earth and Planetary Sciences, University of New Mexico, Albuquerque, New Mexico

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Print Publication:
01 Jul 1997
DOI:
https://doi.org/10.1175/1520-0442(1997)010<1473:ETEOSW>2.0.CO;2
Page(s):
1473–1486
Restricted access

Abstract

One open question in El Niño–Southern Oscillation (ENSO) simulation and predictability is the role of random forcing by atmospheric variability with short correlation times, on coupled variability with interannual timescales. The discussion of this question requires a quantitative assessment of the stochastic component of the wind stress forcing. Self-consistent estimates of this noise (the stochastic forcing) can be made quite naturally in an empirical atmospheric model that uses a statistical estimate of the relationship between sea surface temperature (SST) and wind stress anomaly patterns as the deterministic feedback between the ocean and the atmosphere. The authors use such an empirical model as the atmospheric component of a hybrid coupled model, coupled to the GFDL ocean general circulation model. The authors define as residual the fraction of the Florida State University wind stress not explained by the empirical atmosphere run from observed SST, and a noise product is constructed by random picks among monthly maps of this residual.

The impact of included or excluded noise is assessed with several ensembles of simulations. The model is run in coupled regimes where, in the absence of noise, it is perfectly periodic: in the presence of prescribed seasonal variability, the model is strongly frequency locked on a 2-yr period; in annual average conditions it has a somewhat longer inherent ENSO period (30 months). Addition of noise brings an irregular behavior that is considerably richer in spatial patterns as well as in temporal structures. The broadening of the model ENSO spectral peak is roughly comparable to observed. The tendency to frequency lock to subharmonic resonances of the seasonal cycle tends to increase the broadening and to emphasize lower frequencies. An inclination to phase lock to preferred seasons persists even in the presence of noise-induced irregularity. Natural uncoupled atmospheric variability is thus a strong candidate for explaining the observed aperiodicity in ENSO time series. Model–model hindcast experiments also suggest the importance of atmospheric noise in setting limits to ENSO predictability.

Corresponding author address: Dr. J. David Neelin, Department of Atmospheric Sciences, UCLA, Los Angeles, CA 90095.

Abstract

One open question in El Niño–Southern Oscillation (ENSO) simulation and predictability is the role of random forcing by atmospheric variability with short correlation times, on coupled variability with interannual timescales. The discussion of this question requires a quantitative assessment of the stochastic component of the wind stress forcing. Self-consistent estimates of this noise (the stochastic forcing) can be made quite naturally in an empirical atmospheric model that uses a statistical estimate of the relationship between sea surface temperature (SST) and wind stress anomaly patterns as the deterministic feedback between the ocean and the atmosphere. The authors use such an empirical model as the atmospheric component of a hybrid coupled model, coupled to the GFDL ocean general circulation model. The authors define as residual the fraction of the Florida State University wind stress not explained by the empirical atmosphere run from observed SST, and a noise product is constructed by random picks among monthly maps of this residual.

The impact of included or excluded noise is assessed with several ensembles of simulations. The model is run in coupled regimes where, in the absence of noise, it is perfectly periodic: in the presence of prescribed seasonal variability, the model is strongly frequency locked on a 2-yr period; in annual average conditions it has a somewhat longer inherent ENSO period (30 months). Addition of noise brings an irregular behavior that is considerably richer in spatial patterns as well as in temporal structures. The broadening of the model ENSO spectral peak is roughly comparable to observed. The tendency to frequency lock to subharmonic resonances of the seasonal cycle tends to increase the broadening and to emphasize lower frequencies. An inclination to phase lock to preferred seasons persists even in the presence of noise-induced irregularity. Natural uncoupled atmospheric variability is thus a strong candidate for explaining the observed aperiodicity in ENSO time series. Model–model hindcast experiments also suggest the importance of atmospheric noise in setting limits to ENSO predictability.

Corresponding author address: Dr. J. David Neelin, Department of Atmospheric Sciences, UCLA, Los Angeles, CA 90095.

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  • Balmaseda, M. A., M. K. Davey, and D. L. T. Anderson, 1995: Decadal and seasonal dependence of ENSO prediction skill. J. Climate,8, 2705–2715.

  • Barnett, T. P., 1985: Variations in near-global sea level pressure. J. Atmos. Sci.,42, 478–501.

  • ——, 1991: The interaction of multiple time scales in the tropical climate system. J. Climate,4, 269–285.

  • ——, M. Latif, N. Graham, M. Flügel, S. Pazan, and W. White, 1993: ENSO and ENSO-related predictability. Part I: Prediction of equatorial Pacific sea surface temperature with a hybrid coupled ocean–atmosphere model. J. Climate,6, 1545–1566.

  • ——, and Coauthors, 1994: Forecasting global ENSO-related climate anomalies. Tellus,46A, 381–397.

  • Battisti, D. S., 1988: Dynamics and thermodynamics of a warming event in a coupled tropical atmosphere–ocean model. J. Atmos. Sci.,45, 2889–2919.

  • ——, and A. C. Hirst, 1989: Interannual variability in the tropical atmosphere/ocean system: Influence of the basic state, ocean geometry, and nonlinearity. J. Atmos. Sci.,46, 1687–1712.

  • Bretherton, C. S., C. Smith, and J. M. Wallace, 1992: An intercomparison of methods for finding coupled patterns in climate data. J. Climate,5, 541–560.

  • Chang, P., B. Wang, T. Li, and L. Ji, 1994: Interactions between the seasonal cycle and the Southern Oscillation—Frequency entrainment and chaos in a coupled ocean–atmosphere model. Geophys. Res. Lett.,21, 2817–2820.

  • ——, L. Ji, B. Wang, and T. Li, 1995: Interactions between the seasonal cycle and El Niño–Southern Oscillation in an intermediate coupled ocean–atmosphere model. J. Atmos. Sci.,52, 2353–2372.

  • Deser, C., and J. M. Wallace, 1990: Large-scale atmospheric circulation features of warm and cold episodes in the tropical Pacific. J. Climate,3, 1254–1281.

  • Dettinger, M. D., M. Ghil, C. M. Strong, W. Weibel, and P. Yiou, 1995: Software expedites singular-spectrum analysis of noisy time series. Eos, Trans. Amer. Geophys. Union,76, 12, 14, 21.

  • Eckert, C., and M. Latif, 1997: Predictability of a stochastically forced hybrid coupled model of the tropical Pacific ocean–atmosphere system. J. Climate,10, 1488–1504.

  • Gill, A. E., 1980: Some simple solutions for heat-induced tropical circulation. Quart. J. Roy. Meteor. Soc.,106, 447–462.

  • Goswami, B. N., and J. Shukla, 1991: Predictability of a coupled ocean–atmosphere model. J. Climate,4, 3–22.

  • Hirst, A. C., 1986: Unstable and damped equatorial modes in simple coupled ocean–atmosphere models. J. Atmos. Sci.,43, 606–630.

  • ——, 1988: Slow instabilities in tropical ocean basin-global atmosphere models. J. Atmos. Sci.,45, 830–852.

  • Iooss, G., and D. D. Joseph, 1990: Elementary Stability and Bifurcation Theory. Springer-Verlag, 324 pp.

  • Jazwinski, A. H., 1970: Stochastic Processes and Filtering Theory. Academic Press, 376 pp.

  • Jiang, N., J. D. Neelin, and M. Ghil, 1995: Quasi-quadrennial and quasi-biennial variability in COADS equatorial Pacific sea surface temperature and winds. Climate Dyn.,12, 101–112.

  • Jin, F.-F., and J. D. Neelin, 1993a: Modes of interannual tropical ocean–atmosphere interaction—A unified view. Part I: Numerical results. J. Atmos. Sci.,50, 3477–3503.

  • ——, and ——, 1993b: Modes of interannual tropical ocean–atmosphere interaction—A unified view. Part III: Analytical results in fully coupled cases. J. Atmos. Sci.,50, 3523–3540.

  • ——, ——, and M. Ghil, 1994: El Niño on the Devil’s staircase: Annual subharmonic steps to chaos. Science,264, 70–72.

  • ——, ——, and ——, 1996: El Niño/Southern Oscillation and the annual cycle: Subharmonic frequency locking and aperiodicity. Physica D,9, 442–465.

  • Kleeman, R., and S. B. Power, 1994: Limits to predictability in a coupled ocean–atmosphere model due to atmospheric noise. Tellus,46A, 529–540.

  • Latif, M., and M. Flügel, 1991: An investigation of short-range climate predictability in the tropical Pacific. J. Geophys. Res.,96, 2661–2673.

  • ——, A. Sterl, E. Maier-Reimer, and M. M. Junge, 1993: Climate variability in a coupled GCM. Part I: The tropical Pacific. J. Climate,6, 5–21.

  • Legler, D. M., and J. J. O’Brien, 1984: Atlas of Tropical Pacific Wind-Stress Climatology 1971–1980. The Florida State University, 182 pp.

  • Mantua, N. J., and D. S. Battisti, 1995: Aperiodic variability in the Zebiak–Cane coupled ocean–atmosphere model: Air–sea interactions in the western equatorial Pacific. J. Climate,8, 2897–2927.

  • Münnich, M., M. A. Cane, and S. E. Zebiak, 1991: A study of self-excited oscillations of the tropical ocean–atmosphere system. Part II: Nonlinear cases. J. Atmos. Sci.,48, 1238–1248.

  • Neelin, J. D., 1990: A hybrid coupled general circulation model for El Niño studies. J. Atmos. Sci.,47, 674–693.

  • ——, 1991: The slow sea surface temperature mode and the fast-wave limit: Analytic theory for tropical interannual oscillations and experiments in a hybrid coupled model. J. Atmos. Sci.,48, 584–606.

  • ——, and F.-F. Jin, 1993: Modes of interannual tropical ocean–atmosphere interaction—A unified view. Part II: Analytical results in the weak coupling limit. J. Atmos. Sci.,50, 3504–3522.

  • ——, and Coauthors, 1992: Tropical air–sea interaction in general circulation models. Climate Dyn.,7, 73–104.

  • Oberhuber, J. M., 1988: An atlas based on the COADS data set: The budget of heat, buoyancy, and turbulent kinetic energy at the surface of the global ocean. MPI Rep. 15, 13 pp. [Available from Max-Planck-Institut für Meteorologie, Hamburg, Bundestrasse 55, D-2000, Germany.].

  • Paulson, C. A., and J. J. Simpson, 1977: Irradiance measurements in the upper ocean. J. Phys. Oceanogr.,7, 952–956.

  • Penland, C., and L. Matrosova, 1994: A balance condition for stochastic numerical models with application to the El Niño–Southern Oscillation. J. Climate,7, 1352–1372.

  • ——, and P. D. Sardeshmukh, 1995: The optimal growth of tropical sea surface temperature anomalies. J. Climate,8, 1999–2024.

  • Peters, H., M. C. Gregg, and J. M. Toole, 1988: On the parameterization of the equatorial turbulence. J. Geophys. Res.,93, 1199–1218.

  • Philander, S. G. H., T. Yamagata, and R. C. Pacanowski, 1984: Unstable air–sea interactions in the tropics. J. Atmos. Sci.,41, 604–613.

  • ——, R. C. Pacanowski, N. C. Lau, and M. J. Nath, 1992: Simulation of ENSO with a global atmospheric GCM coupled to a high resolution, tropical Pacific Ocean GCM. J. Climate,5, 308–329.

  • Rasmusson, E. M., and T. H. Carpenter, 1982: Variations in tropical sea surface temperature and surface wind fields associated with the Southern Oscillation / El Niño. Mon. Wea. Rev.,110, 354–384.

  • ——, X. Wang, and C. F. Ropelewski, 1990: The biennial component of ENSO variability. J. Mar. Syst.,1, 71–96.

  • Reynolds, R. W., 1988: A real-time global sea surface temperature analysis. J. Climate,1, 75–86.

  • Ropelewski, C. F., and M. S. Halpert, 1989: Precipitation patterns associated with the high index phase of the Southern Oscillation. J. Climate,2, 594–614.

  • Schopf, P. S., and M. J. Suarez, 1988: Vacillations in a coupled ocean–atmosphere model. J. Atmos. Sci.,45, 549–566.

  • ——, and ——, 1990: Ocean wave dynamics and the time scale of ENSO. J. Phys. Oceanogr.,20, 629–645.

  • Seager, R., S. E. Zebiak, and M. A. Cane, 1988: A model of the tropical Pacific sea surface temperature climatology. J. Geophys. Res.,93, 1265–1280.

  • Syu, H.-H., J. D. Neelin, and D. S. Gutzler, 1995: Seasonal and interannual variability in a hybrid coupled GCM. J. Climate,8, 2121–2143.

  • Tziperman, E., L. Stone, M. A. Cane, and H. Jarosh, 1994: El Niño chaos: Overlapping of resonances between the seasonal cycle and the Pacific ocean–atmosphere oscillator. Science,264, 72–74.

  • ——, M. A. Cane, and S. Zebiak, 1995: Irregularity and locking to the seasonal cycle in an ENSO prediction model as explained by the quasi-periodicity route to chaos. J. Atmos. Sci.,52, 293–306.

  • Wakata, Y., and E. S. Sarachik, 1991a: On the role of equatorial ocean modes in the ENSO cycle. J. Phys. Oceanogr.,21, 434–443.

  • ——, and ——, 1991b: Unstable coupled atmosphere–ocean basin modes in the presence of a spatially varying basic state. J. Atmos. Sci.,48, 2060–2077.

  • Waliser, D. E., B. Blanke, J. D. Neelin, and C. Gautier, 1994: Shortwave feedbacks and ENSO: Forced ocean and coupled ocean–atmosphere experiments. J. Geophys. Res.,99, 25 109–25 125.

  • Wyrtki, K., 1985: Water displacements in the Pacific and the genesis of El Niño cycles. J. Geophys. Res.,90, 7129–7132.

  • Zebiak, S. E., 1989: On the 30–60 day oscillation and the prediction of El Niño. J. Climate,2, 1381–1387.

  • ——, 1990: Diagnostic studies of Pacific surface winds. J. Climate,3, 1016–1031.

  • ——, and M. A. Cane, 1987: A model El Niño–Southern Oscillation. Mon. Wea. Rev.,115, 2262–2278.

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