• Barnston, A. G., H. M. Van den Dool, S. E. Zebiak, T. P. Barnett, M. Ji, D. R. Rodenhuis, M. A. Cane, A. Leetmaa, N. E. Graham, C. F. Ropelewski, V. E. Kousky, E. A. O’Lenic, and R. E. Livezey, 1994: Long-lead seasonal forecasts—Where do we stand? Bull. Amer. Meteor. Soc.,75, 2079–2114.

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

  • Behringer, D. W., M. Ji, and A. Leetmaa, 1998: An improved coupled model for ENSO prediction and implications for ocean initialization. Part I: The ocean data assimilation system. Mon. Wea. Rev.,126, 1013–1021.

  • Bjerknes, J., 1969: Atmospheric teleconnections from the equatorial Pacific. Mon. Wea. Rev.,97, 163–172.

  • Blumenthal, M. B., 1991: Predictability of a coupled ocean–atmosphere model. J. Climate,4, 766–784.

  • Bryan, K., 1969: A numerical method for the study of the World Ocean. J. Comput. Phys.,4, 347–376.

  • Cane, M. A., S. E. Zebiak, and S. C. Dolan, 1986: Experimental forecasts of El Nino. Nature,321, 827–832.

  • Chen, D., S. E. Zebiak, A. J. Busalacchi, and M. A. Cane, 1995: An improved procedure for El Niño forecasting. Science,269, 1699–1702.

  • Cox, M. D., 1984: A primitive, 3-dimensional model of the ocean. GFDL Ocean Group Tech. Rep. 1, Geophysical Fluid Dynamics Laboratory/NOAA, Princeton University, 143 pp.

  • Derber, J. D., and A. Rosati, 1989: A global oceanic data assimilation system. J. Phys. Oceanogr.,19, 1333–1347.

  • Goldenberg, S. B., and J. J. O’Brien, 1981: Time and space variability of tropical Pacific wind stress. Mon. Wea. Rev.,109, 1190–1207.

  • Ji, M., and A. Leetmaa, 1997: Impact of data assimilation on ocean initialization and El Niño prediction. Mon. Wea. Rev.,125, 742–753.

  • ——, A. Kumar, and A. Leetmaa, 1994: An experimental coupled forecast system at the national meteorological center: Some early results. Tellus,46A, 398–418.

  • ——, A. Leetmaa, and J. Derber, 1995: An ocean analysis system for seasonal to interannual climate studies. Mon. Wea. Rev.,123, 460–481.

  • ——, ——, and V. E. Kousky, 1996: Coupled model prediction of ENSO during the 1980s and the 1990s at the National Centers for Environmental Prediction. J. Climate,9, 3105–3120.

  • Kanamitsu, M., and Coauthors, 1991: Description of NMC global data assimilation and forecast system. Wea. Forecasting,6, 425–435.

  • Kirtman, B. P., J. Shukla, B. Huang, Z. Zhu, and E. K. Schneider, 1997: Multiseasonal predictions with a coupled tropical ocean–global atmosphere system. Mon. Wea. Rev.,125, 789–808.

  • Kleeman, R., 1993: On the dependence of hindcast skill in a coupled ocean-atmosphere model on ocean thermodynamics. J. Climate,6, 2012–2033.

  • ——, A. M. Moore, and N. R. Smith, 1995: Assimilation of subsurface thermal data into a simple ocean model for the initialization of an intermediate tropical coupled ocean–atmosphere forecast model. Mon. Wea. Rev.,123, 3103–3113.

  • ——, R. A. Colman, N. R. Smith, and S. B. Power, 1996: A recent change in the mean state of the Pacific basin climate: Observational evidence and atmospheric and oceanic responses. J. Geophys. Res. (Oceans),101, 20483–20499.

  • Kumar, A., M. P. Hoerling, M. Ji, A. Leetmaa, and P. Sardeshmukh, 1996: Assessing a GCM’s suitability for making seasonal predictions. J. Climate,9, 115–129.

  • Latif, M., A. Sterl, E. Maier-Reimer, and M. M. Junge, 1993: Structure and predictability of the El Niño/Southern Oscillation phenomenon in a coupled ocean–atmosphere general circulation model. J. Climate,6, 700–708.

  • ——, R. Kleeman, and C. Eckert, 1997: Greenhouse warming, decadal variability or El Niño? An attempt to understand the anomalous 1990s. J. Climate,10, 2221–2239.

  • Levitus, S., R. Burgett, and T. P. Boyer, 1994: World Ocean Atlas 1994. Vol. 3. Salinity. NOAA Atlas NESDIS 3, 99 pp.

  • Oberhuber, J. M., 1988: An atlas based on the “COADS” data set: The budgets of heat, buoyancy and turbulent kinetic energy at the surface of the global ocean. Rep. 15, Max-Planck-Institut für Meteorologie, 20 pp. [Available from Max-Planck-Institut für Meteorologie, Bundesstrasse 55, Hamburg, Germany.].

  • Pacanowski, R., and S. G. H. Philander, 1981: Parameterization of vertical mixing in numerical models of tropical oceans. J. Phys. Oceanogr.,11, 1443–1451.

  • Philander, S. G. H., W. J. Hurlin, and A. D. Seigel, 1987: A model of the seasonal cycle in the tropical Pacific ocean. J. Phys. Oceanogr.,17, 1986–2002.

  • Reynolds, R. W., and T. M. Smith, 1994: Improved global sea surface temperature analysis using optimum interpolation. J. Climate,7, 929–948.

  • ——, and ——, 1995: A high resolution global sea surface temperature climatology. J. Climate,8, 1571–1583.

  • Ropelewski, C. F., and M. S. Halpert, 1987: Global and regional scale precipitation patterns associated with El Nino/Southern Oscillation. Mon. Wea. Rev.,115, 1606–1626.

  • Rosati, A., K. Miyakoda, and R. Gudgel, 1997: The impact of ocean initial conditions on ENSO forecasting with a coupled model. Mon. Wea. Rev.,125, 754–772.

  • Wyrtki, K., 1975: El Nino—The dynamical response of the equatorial Pacific to atmospheric forcing. J. Phys. Oceanogr.,5, 572–584.

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

  • Xue, Y., M. A. Cane, and S. E. Zebiak, 1997: Predictability of a coupled model of ENSO using singular vector analysis. Part I: Optimal growth in seasonal background and ENSO cycles. Mon. Wea. Rev,125, 2043–2056.

  • Zebiak, S. E., and M. A. Cane, 1987: A model El Nino–Southern Oscillation. Mon. Wea. Rev.,115, 2262–2278.

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An Improved Coupled Model for ENSO Prediction and Implications for Ocean Initialization. Part II: The Coupled Model

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  • 1 National Centers for Environmental Prediction, NWS/NOAA, Washington, D.C.
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Abstract

An improved forecast system has been developed and implemented for ENSO prediction at the National Centers for Environmental Prediction (NCEP). This system consists of a new ocean data assimilation system and an improved coupled ocean–atmosphere forecast model (CMP12) for ENSO prediction. The new ocean data assimilation system is described in Part I of this two-part paper.

The new coupled forecast model (CMP12) is a variation of the standard NCEP coupled model (CMP10). Major changes in the new coupled model are improved vertical mixing for the ocean model; relaxation of the model’s surface salinity to the climatological annual cycle; and incorporation of an anomalous freshwater flux forcing. Also, the domain in which the oceanic SST couples to the atmosphere is limited to the tropical Pacific.

Evaluation of ENSO prediction results show that the new coupled model, using the more accurate ocean initial conditions, achieves higher prediction skill. However, two sets of hindcasting experiments (one using the more accurate ocean initial conditions but the old coupled model, the other using the new coupled model but the less accurate ocean initial conditions), result in no improvement in prediction skill. These results indicate that future improvement in ENSO prediction skill requires systematically improving both the coupled model and the ocean analysis system. The authors’ results also suggest that for the purpose of initializing the coupled model for ENSO prediction, care should be taken to give sufficient weight to the model dynamics during the ocean data assimilation. This can reduce the danger of aliasing large-scale model biases into the low-frequency variability in the ocean initial conditions, and also reduce the introduction of small-scale noise into the initial conditions caused by overfitting the model to sparse observations.

Corresponding author address: Dr. Ming Ji, Climate Modeling Branch, National Centers for Environmental Prediction, 5200 Auth Road, Rm. 807, Camp Springs, MD 20746.

Email: ming.ji@noaa.gov

Abstract

An improved forecast system has been developed and implemented for ENSO prediction at the National Centers for Environmental Prediction (NCEP). This system consists of a new ocean data assimilation system and an improved coupled ocean–atmosphere forecast model (CMP12) for ENSO prediction. The new ocean data assimilation system is described in Part I of this two-part paper.

The new coupled forecast model (CMP12) is a variation of the standard NCEP coupled model (CMP10). Major changes in the new coupled model are improved vertical mixing for the ocean model; relaxation of the model’s surface salinity to the climatological annual cycle; and incorporation of an anomalous freshwater flux forcing. Also, the domain in which the oceanic SST couples to the atmosphere is limited to the tropical Pacific.

Evaluation of ENSO prediction results show that the new coupled model, using the more accurate ocean initial conditions, achieves higher prediction skill. However, two sets of hindcasting experiments (one using the more accurate ocean initial conditions but the old coupled model, the other using the new coupled model but the less accurate ocean initial conditions), result in no improvement in prediction skill. These results indicate that future improvement in ENSO prediction skill requires systematically improving both the coupled model and the ocean analysis system. The authors’ results also suggest that for the purpose of initializing the coupled model for ENSO prediction, care should be taken to give sufficient weight to the model dynamics during the ocean data assimilation. This can reduce the danger of aliasing large-scale model biases into the low-frequency variability in the ocean initial conditions, and also reduce the introduction of small-scale noise into the initial conditions caused by overfitting the model to sparse observations.

Corresponding author address: Dr. Ming Ji, Climate Modeling Branch, National Centers for Environmental Prediction, 5200 Auth Road, Rm. 807, Camp Springs, MD 20746.

Email: ming.ji@noaa.gov

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