• An, S.-I., , and F.-F. Jin, 2004: Nonlinearity and asymmetry of ENSO. J. Climate, 17, 23992412.

  • Battisti, D. S., 1988: Dynamics and thermodynamics of a warming event in a coupled atmosphere-ocean model. J. Atmos. Sci., 45, 28892919.

    • Search Google Scholar
    • Export Citation
  • Battisti, D. S., , and A. C. Hirst, 1989: Interannual variability in a tropical atmosphere-ocean model: Influence of the basic state, ocean geometry, and nonlinearity. J. Atmos. Sci., 46, 16871712.

    • Search Google Scholar
    • Export Citation
  • Bugnion, V., , and C. Hill, 2006: Equilibration mechanisms in an adjoint ocean general circulation model. Ocean Dyn., 56, 5161.

  • Bugnion, V., , C. Hill, , and P. H. Stone, 2006: An adjoint analysis of the meridional overturning circulation in a hybrid coupled model. J. Climate, 19, 37513767.

    • Search Google Scholar
    • Export Citation
  • Duan, W., , and M. Mu, 2006: Investigating decadal variability of El Niño–Southern Oscillation asymmetry by conditional nonlinear optimal perturbation. J. Geophys. Res., 111, C07015, doi:10.1029/2005JC003458.

    • Search Google Scholar
    • Export Citation
  • Duan, W., , and M. Mu, 2009a: Conditional nonlinear optimal perturbation: applications to stability, sensitivity, and predictability. Sci. China, 52D, 883906.

    • Search Google Scholar
    • Export Citation
  • Duan, W., , and M. Mu, 2009b: Investigating a nonlinear characteristic of El Niño events by conditional nonlinear optimal perturbation. Atmos. Res., 94, 1018.

    • Search Google Scholar
    • Export Citation
  • Emery, W. J., , and R. E. Thomson, 2001: Data Analysis Methods in Physical Oceanography. Elsevier Science, 638 pp.

  • Errico, R. M., 1997: What is an adjoint model? Bull. Amer. Meteor. Soc., 78, 25772591.

  • Forget, G., 2010: Mapping ocean observations in a dynamical framework: A 2004–06 ocean atlas. J. Phys. Oceanogr., 40, 12011221.

  • Fukumori, I., , T. Lee, , B. Cheng, , and D. Menemenlis, 2004: The origin, pathway, and destination of Niño-3 water estimated by a simulated passive tracer and its adjoint. J. Phys. Oceanogr., 34, 582604.

    • Search Google Scholar
    • Export Citation
  • Giering, R., , and T. Kaminski, 1998: Recipes for adjoint code construction. ACM Trans. Math. Software, 24, 437474.

  • Harrison, D. E., 1989: Local and remote forcing of ENSO ocean waveguide response. J. Phys. Oceanogr., 19, 691695.

  • Harrison, D. E., , and N. K. Larkin, 1998: El Niño–Southern Oscillation sea surface temperature and wind anomalies, 1946–1993. Rev. Geophys., 36, 353399.

    • Search Google Scholar
    • Export Citation
  • Heimbach, P., , C. Hill, , and R. Giering, 2005: An efficient exact adjoint of the parallel MIT General Circulation Model, generated via automatic differentiation. Future Gener. Comput. Syst., 21, 13561371.

    • Search Google Scholar
    • Export Citation
  • Hill, C., , V. Bugnion, , M. Follows, , and J. Marshall, 2004: Evaluating carbon sequestration efficiency in an ocean circulation model by adjoint sensitivity analysis. J. Geophys. Res., 109, C110005, doi:10.1029/2002JC001598.

    • Search Google Scholar
    • Export Citation
  • Hoteit, I., , B. Cornuelle, , A. Kohl, , and D. Stammer, 2005: Treating strong adjoint sensitivities in tropical eddy-permitting variational data assimilation. Quart. J. Roy. Meteor. Soc., 131, 36593682.

    • Search Google Scholar
    • Export Citation
  • Hoteit, I., , B. Cornuelle, , V. Thierry, , and D. Stammer, 2008: Impact of resolution and optimized ECCO forcing on simulation of the tropical Pacific. J. Atmos. Oceanic Technol., 25, 131147.

    • Search Google Scholar
    • Export Citation
  • Hoteit, I., , B. Cornuelle, , P. Heimbach, 2010: An eddy-permitting, dynamically consistent hindcast of the tropical Pacific in 2000 using and adjoint-based assimilation system. J. Geophys. Res., 115, C03001, doi:10.1029/2009JC005437.

    • Search Google Scholar
    • Export Citation
  • Jin, F.-F., , and S.-I. An, 1999: Thermocline and zonal advective feedbacks within the equatorial ocean charge oscillator model for ENSO. Geophys. Res. Lett., 26, 29892992.

    • Search Google Scholar
    • Export Citation
  • Jin, F.-F., , S.-I. An, , A. Timmermann, , and J. Zhao, 2003: Strong El Niño events and nonlinear dynamical heating. Geophys. Res. Lett., 30, 1120, doi:10.1029/2002GL016356.

    • Search Google Scholar
    • Export Citation
  • Jin, F.-F., , S. T. Kim, , and L. Bejarano, 2006: A coupled-stability index for ENSO. Geophys. Res. Lett., 33, L23708, doi:10.1029/2006GL027221.

    • Search Google Scholar
    • Export Citation
  • Johnson, G. C., , B. M. Sloyan, , W. S. Kessler, , and K. E. McTaggart, 2002: Direct measurements of upper ocean currents and water properties across the tropical Pacific Ocean during the 1990s. Prog. Oceanogr., 52, 3161.

    • Search Google Scholar
    • Export Citation
  • Kessler, W. S., , and M. J. McPhaden, 1995: The 1991-1993 El Niño in the central Pacific. Deep-Sea Res. II, 42, 295333.

  • Kim, S.-B., , T. Lee, , and I. Fukumori, 2007: Mechanisms controlling the interannual variations of mixed layer temperature averaged over the Niño-3 region. J. Climate, 20, 38223843.

    • Search Google Scholar
    • Export Citation
  • Köhl, A., , D. Stammer, , and B. Cornuelle, 2007: Interannual to decadal changes in the ECCO global synthesis. J. Phys. Oceanogr., 37, 313337.

    • Search Google Scholar
    • Export Citation
  • Le Dimet, F.-X., , and O. Talagrand, 1986: Variational algorithms for analysis and assimilation of meteorological observations: Theoretical aspects. Tellus, 38A, 97110.

    • Search Google Scholar
    • Export Citation
  • Lee, T., , B. Cheng, , and R. Giering, 2001: Adjoint sensitivity of Indonesian throughflow transport to wind stress: Application to interannual variability. Jet Propulsion Laboratory Publ. 01-11, 34 pp.

    • Search Google Scholar
    • Export Citation
  • Lee, T., , I. Fukumori, , and B. Tang, 2004: Temperature advection: Internal versus external processes. J. Phys. Oceanogr., 34, 19361944.

    • Search Google Scholar
    • Export Citation
  • Lloyd, J., , E. Guilyardi, , H. Weller, , and J. Slingo, 2009: The role of atmosphere feedbacks during ENSO in the CMIP3 models. Atmos. Sci. Lett., 10, 170176.

    • Search Google Scholar
    • Export Citation
  • Losch, M., , and P. Heimbach, 2007: Adjoint sensitivity of an ocean general circulation model to bottom topography. J. Phys. Oceanogr., 37, 377393.

    • Search Google Scholar
    • Export Citation
  • MacMynowski, D. G., , and E. Tziperman, 2010: Testing and improving ENSO models by process using transfer functions. Geophys. Res. Lett., 37, L19701, doi:10.1029/2010GL044050.

    • Search Google Scholar
    • Export Citation
  • Marotzke, J., , R. Giering, , K. Q. Zhang, , D. Stammer, , C. Hill, , and T. Lee, 1999: Construction of the adjoint MIT ocean general circulation model and application to Atlantic heat transport variability. J. Geophys. Res., 104, 29 52929 547.

    • Search Google Scholar
    • Export Citation
  • Marshall, J., , A. Adcroft, , C. Hill, , L. Perelman, , and C. Heisey, 1997: A finite-volume, incompressible Navier–Stokes model for studies of the ocean on parallel computers. J. Geophys. Res., 102, 57535766.

    • Search Google Scholar
    • Export Citation
  • McPhaden, M. J., 2004: Evolution of the 2002–03 El Niño. Bull. Amer. Meteor. Soc., 85, 677695.

  • McPhaden, M. J., , and X. Yu, 1999: Equatorial waves and the 1997-98 El Niño. Geophys. Res. Lett., 26, 29612964.

  • McPhaden, M. J., and Coauthors, 1998: The Tropical Ocean-Global Atmosphere observing system: A decade of progress. J. Geophys. Res., 103, 14 16914 240.

    • Search Google Scholar
    • Export Citation
  • McPhaden, M. J., , and S. E. Zebiak, , and M. H. Glantz, 2006: ENSO as an integrating concept in earth science. Science, 314, 17401745.

  • Moore, A. M., , H. G. Arango, , E. D. Lorenzo, , A. J. Miller, , and B. D. Cornuelle, 2009: An adjoint sensitivity analysis of the Southern California Current circulation and ecosystem. J. Phys. Oceanogr., 39, 702720.

    • Search Google Scholar
    • Export Citation
  • Mu, M., , W. S. Duan, , and B. Wang, 2003: Conditional nonlinear optimal perturbation and its applications. Nonlinear Processes Geophys., 10, 493501.

    • Search Google Scholar
    • Export Citation
  • Philander, S. G., 1990: El Niño, La Niña, and the Southern Oscillation. Academic Press, 289 pp.

  • 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, 354384.

    • Search Google Scholar
    • Export Citation
  • Roemmich, D., , and J. Gilson, 2009: The 2004–2008 mean and annual cycle of temperature, salinity, and steric height in the global ocean from the Argo program. Prog. Oceanogr., 82, 81100.

    • Search Google Scholar
    • Export Citation
  • Roemmich, D., and Coauthors, 1998: On the design and implementation of ARGO: An initial plan for a global array of profiling floats. International CLIVAR Project Office Rep. 21, GODAE Rep. 5, GODAE International Project Office, Melbourne, Australia, 32 pp.

    • Search Google Scholar
    • Export Citation
  • Stockdale, T. N., , A. J. Busalacchi, , D. E. Harrison, , and R. Seager, 1998: Ocean modeling for ENSO. J. Geophys. Res., 103, 14 32514 355.

    • Search Google Scholar
    • Export Citation
  • Thacker, W. C., , and R. B. Long, 1988: Fitting dynamics to data. J. Geophys. Res., 93, 12271240.

  • Veneziani, V., , C. A. Edwards, , and A. M. Moore, 2009: A central California coastal ocean modeling study: 2. Adjoint sensitivities to local and remote forcing mechanisms. J. Geophys. Res., 114, C04020, doi:10.1029/2008JC004775.

    • Search Google Scholar
    • Export Citation
  • Vintzileos, A., , M. M. Rienecker, , M. J. Suarez, , S. D. Schubert, , and S. K. Miller, 2005: Local versus remote wind forcing of the equatorial Pacific surface temperature in July 2003. Geophys. Res. Lett., 32, L05702, doi:10.1029/2004GL021972.

    • Search Google Scholar
    • Export Citation
  • Wang, C., , and J. Picaut, 2004: Understanding ENSO physics—A review. Earth’s Climate: The Ocean–Atmosphere Interaction, Geophys. Monogr., Vol. 147, Amer. Geophys. Union, 21–48.

    • Search Google Scholar
    • Export Citation
  • Zebiak, S. E., , and M. A. Cane, 1987: A model El Niño–Southern Oscillation. Mon. Wea. Rev., 115, 22622278.

  • Zhang, X., , and M. J. McPhaden, 2006: Wind stress variations and interannual sea surface temperature anomalies in the eastern equatorial Pacific. J. Climate, 19, 226241.

    • Search Google Scholar
    • Export Citation
  • Zhang, X., , and M. J. McPhaden, 2008: Eastern equatorial Pacific forcing of ENSO sea surface temperature anomalies. J. Climate, 21, 60706079.

    • Search Google Scholar
    • Export Citation
  • Zhang, X., , and M. J. McPhaden, 2010: Surface layer heat balance in the eastern equatorial Pacific Ocean on interannual time scales: Influence of local versus remote wind forcing. J. Climate, 23, 43754394.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 37 37 2
PDF Downloads 24 24 3

Adjoint Sensitivity of the Niño-3 Surface Temperature to Wind Forcing

View More View Less
  • 1 Scripps Institution of Oceanography, La Jolla, California, and CSIRO Marine and Atmospheric Research, Hobart, Tasmania, Australia
  • | 2 Scripps Institution of Oceanography, La Jolla, California
© Get Permissions
Restricted access

Abstract

The evolution of sea surface temperature (SST) over the eastern equatorial Pacific plays a significant role in the intense tropical air–sea interaction there and is of central importance to the El Niño–Southern Oscillation (ENSO) phenomenon. Effects of atmospheric fields (especially wind stress) and ocean state on the eastern equatorial Pacific SST variations are investigated using the Massachusetts Institute of Technology general circulation model (MITgcm) and its adjoint model, which can calculate the sensitivities of a cost function (in this case the averaged 0–30-m temperature in the Niño-3 region during an ENSO event peak) to previous atmospheric forcing fields and ocean state going backward in time. The sensitivity of the Niño-3 surface temperature to monthly zonal wind stress in preceding months can be understood by invoking mixed layer heat balance, ocean dynamics, and especially linear equatorial wave dynamics. The maximum positive sensitivity of the Niño-3 surface temperature to local wind forcing usually happens ~1–2 months before the peak of the ENSO event and is hypothesized to be associated with the Ekman pumping mechanism. In model experiments, its magnitude is closely related to the subsurface vertical temperature gradient, exhibiting strong event-to-event differences with strong (weak) positive sensitivity during La Niña (strong El Niño) events. The adjoint sensitivity to remote wind forcing in the central and western equatorial Pacific is consistent with the standard hypothesis that the remote wind forcing affects the Niño-3 surface temperature indirectly by exciting equatorial Kelvin and Rossby waves and modulating thermocline depth in the Niño-3 region. The current adjoint sensitivity study is consistent with a previous regression-based sensitivity study derived from perturbation experiments. Finally, implication for ENSO monitoring and prediction is also discussed.

Corresponding author address: Xuebin Zhang, Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Dr., MS 0230, La Jolla, CA 92093-0230. E-mail: Xuebin.Zhang@csiro.au

Abstract

The evolution of sea surface temperature (SST) over the eastern equatorial Pacific plays a significant role in the intense tropical air–sea interaction there and is of central importance to the El Niño–Southern Oscillation (ENSO) phenomenon. Effects of atmospheric fields (especially wind stress) and ocean state on the eastern equatorial Pacific SST variations are investigated using the Massachusetts Institute of Technology general circulation model (MITgcm) and its adjoint model, which can calculate the sensitivities of a cost function (in this case the averaged 0–30-m temperature in the Niño-3 region during an ENSO event peak) to previous atmospheric forcing fields and ocean state going backward in time. The sensitivity of the Niño-3 surface temperature to monthly zonal wind stress in preceding months can be understood by invoking mixed layer heat balance, ocean dynamics, and especially linear equatorial wave dynamics. The maximum positive sensitivity of the Niño-3 surface temperature to local wind forcing usually happens ~1–2 months before the peak of the ENSO event and is hypothesized to be associated with the Ekman pumping mechanism. In model experiments, its magnitude is closely related to the subsurface vertical temperature gradient, exhibiting strong event-to-event differences with strong (weak) positive sensitivity during La Niña (strong El Niño) events. The adjoint sensitivity to remote wind forcing in the central and western equatorial Pacific is consistent with the standard hypothesis that the remote wind forcing affects the Niño-3 surface temperature indirectly by exciting equatorial Kelvin and Rossby waves and modulating thermocline depth in the Niño-3 region. The current adjoint sensitivity study is consistent with a previous regression-based sensitivity study derived from perturbation experiments. Finally, implication for ENSO monitoring and prediction is also discussed.

Corresponding author address: Xuebin Zhang, Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Dr., MS 0230, La Jolla, CA 92093-0230. E-mail: Xuebin.Zhang@csiro.au
Save