An experimental coupled forecast system at the National Meteorological Center

References

• Barnett, T. P., Graham, N. E., Cane, M. A., Zebiak, S. E., Dolan, S. C., O’Brien, J. J. and Legeler, P. M. 1988. On the prediction of the El Niño of 1986-87. Science 241, 192–96.
   PubMed Web of Science ®Google Scholar
• Barnett, T. P., Latif, M., Krik, E. and Roecken, E. 1991. On ENSO physics. J. Climate 4, 487–515.
   Web of Science ®Google Scholar
• Barnett, T. P., Latif, M., Graham, N., Flugel, M., Pazan, S. and White, W. 1993. ENSO and ENSO-related predictability: Part 1: Prediction of equatorial Pacific sea surface temperatures with a hybrid coupled ocean-atmosphere model. J. Climate 6, 1545–1566.
   Web of Science ®Google Scholar
• Barnston, A. G. and Ropelewski, C. F. 1992. Prediction of ENSO episodes using canonical correlation analysis. J. Climate 5, 1316–1345.
   Web of Science ®Google Scholar
• Battisti, D. S. 1988. Dynamics and thermodynamics of a warming event in a coupled tropical atmosphere-ocean model. J. Atmos. Sci. 45, 2889–2919.
   Web of Science ®Google Scholar
• Blumenthal, M. B. 1991. Predictability of a coupled ocean-atmosphere model. J. Climate 4,766–784.
   Web of Science ®Google Scholar
• Boyle, J. S. 1993. Sensitivity of dynamical quantities to horizontal resolution for a climate simulation using the ECMWF (Cycle 33) model. J. Climate 6, 796–815.
   Web of Science ®Google Scholar
• Bryan, K. 1969. A numerical method for the study of the world ocean. J. Comput. Phys. 4,347–376.
   Google Scholar
• Cane, M. A. and Zebiak, S. E. 1985. A theory for El Niño and the Southern Oscillation. Science 228, 1085–87.
   PubMed Web of Science ®Google Scholar
• Cane, M. A., Zebiak, S. E. and Dolan, S. C. 1986. Experimental forecasts of El Niño. Nature 321, 827–832.
   Web of Science ®Google Scholar
• Cox, M. D. 1984. A primitive, 3-dimensional model of the ocean. GFDL ocean group Tech. Rep. no. 1, Geophysical Fluid Dynamics Laboratory, 143 pp.
   Google Scholar
• Ebisuzaki, W. and Van den Dool, H. M. 1993a. Analysis of the variability in a GCM forced by realistically varying SST. Proceedings of the Workshop on numerical extended range weather prediction, 8-10 June 1993, Airlie, Virginia.
   Google Scholar
• Ebisuzaki, W. and Van den Dool, H. M. 1993b. NMC Office note 402. The atmospheric model intercomparison project at the National Meteorological Center. Available from the National Meteorological Center, 5200 Auth Road, Camp Springs, Md. 20746 USA.
   Google Scholar
• Hartmann, D. L., Hendon, H. H. and Houze, R. A.Jr. 1984. Some implications of the mesoscale circulations in the tropical cloud clusters for large-scale dynamics and climate. J. Atmos. Science 41, 113–121.
   Web of Science ®Google Scholar
• Harrison, D. E. 1989. On climatological mean wind stress and wind stress curl fields over the world ocean. J. Climate 2, 57–70.
   Web of Science ®Google Scholar
• Hellerman, S. and Rosenstein, M. 1983. Normal monthly wind stress over the world ocean with error estimates. J. Phys. Oceanogr. 13, 1093–1104.
   Web of Science ®Google Scholar
• Holtslag, A. A. M. and Moeng, C-H. 1991. Eddy diffusivity and countergradient transport in the convective atmospheric boundary layer. J. Atmos. Sci. 48, 1690–1698.
   Web of Science ®Google Scholar
• Ji, M., Kumar, A. and Leetmaa, A. 1994a. A multi-season climate forecast system at the National Meteorological Center. Bull. of Amer. Meteor. Soc., in press.
   Google Scholar
• Ji, M., Leetmaa, A. and Derber, J. 1994b. An ocean analysis system for climate studies. Mon. Wea. Rev., in press.
   Google Scholar
• Kanamitsu, M. 1989. Description of the NMC global data assimilating and forecast system. Weather and Forecasting 4, 335–442.
   Google Scholar
• Kanamitsu, M., Mo, K. C. and Kalnay, E. 1990. Annual cycle integration of the NMC medium range forecasting (MRF) model. Mon. Wea. Rev. 118, 2543–2567.
   Web of Science ®Google Scholar
• Kanamitsu, M., Mo, K. C., Kalnay, E., Alpert, J. C., Campana, K. A., Caplan, P. M., Deaven, D. G., Iredell, M., Katz, B., Pan, H. L., Sella, J. and White, G. H. 1991. Recent changes implemented into the global forecast system at NMC. Weather and Forecasting 6, 425–435.
   Web of Science ®Google Scholar
• Kim, J. and Mahrt, L. 1992. Simple formulation of turbulent mixing in stable free atmosphere and nocturnal boundary layer. Tel/us 44A, 381–394.
   Google Scholar
• Kloesel, K. A. and Albrecht, B. A. 1989. Low-level inversions over the tropical Pacific: Thermodynamic structure of the boundary layer and the above-inversion moisture structure. Mon. Wea. Rev. 117, 87–101.
   Web of Science ®Google Scholar
• Latif, M., Sterl, A., Maier-Reimer, E. and Junge, M. M. 1993. Structure and predictability of the El Niño/ Southern Oscillation phenomenon in a coupled ocean-atmosphere general circulation model. J. Climate 6, 700–708.
   Web of Science ®Google Scholar
• Latif, M., Barnett, T. P., Cane, M. A., Flugel, M. and Graham, N. E. 1994. A review on ENSO prediction studies. Climate Dyn. 9, 167–179.
   Web of Science ®Google Scholar
• Lau, K.-M. and Peng, L. 1987. Origin of the low-frequency (intra-seasonal) oscillations in the tropical atmosphere: Part 1: Basic theory. J. Atmos. Science 44, 950–972.
   Web of Science ®Google Scholar
• Leetmaa, A. and Ji, M. 1989. Operational hindcasting of the tropical Pacific. Dyn. Atmos. Oceans 13, 465–490.
   Web of Science ®Google Scholar
• Lindzen, R. S. and Nigam, S. 1987. On the role of sea surface temperature gradients in forcing low level winds and convergence in the tropics. J. Atmos. Science 44, 2418–2436.
   Web of Science ®Google Scholar
• McCreary, J. P. and Anderson, D. L. T. 1984. A simple model of El Niño and the Southern Oscillation. Mon. Wea. Rev. 112, 934–46.
   Web of Science ®Google Scholar
• Meehl, G. A. and Albrecht, B. A. 1991. Response of a GCM with a hybrid convection scheme to a tropical Pacific sea surface temperature anomaly. J. Climate 4, 672–688.
   Web of Science ®Google Scholar
• Neelin, J. D. 1988. A simple model for surface stress and low-level flow in the tropical atmosphere driven by prescribed heating. Quat. J. Roy. Meteo. Soc. 114, 747–770.
   Web of Science ®Google Scholar
• Neelin, J. D. and Held, I. M. 1987. Modeling tropical convergence based on the moist static energy budget. Mon. Wea. Rev. 115, 3–12.
   Web of Science ®Google Scholar
• Neelin, J. D., Latif, M. and Jin, F.-F. 1994. Dynamics of coupled ocean-atmosphere models: The tropical problem. Annu. Rev. Fluid Mech. 26, 617–659.
   Web of Science ®Google Scholar
• NMC Staff, 1988. Documentation of the research version of NMC medium range forecasting model. [ Available from NOAA/NMC, Development Division, Washington, DC 20233]
   Google Scholar
• Pacanowski, R. and Philander, S. G. H. 1981. Parameterization of vertical mixing in numerical models of tropical oceans. J. Phys. Oceanogr. 11, 1443–1451.
   Web of Science ®Google Scholar
• Philander, S. G. H., Hurlin, W. J. and Seigel, A. D. 1987. A model of the seasonal cycle in the tropical Pacific ocean. J. Phys. Oceanogr. 17, 1986–2002.
   Web of Science ®Google Scholar
• Philander, S. G. H., Lau, N. C., Pacanowski, R. C. and Nath, M. J. 1989. Two different simulations of Southern Oscillation and El Niño with coupled ocean-atmosphere general circulation models. Phil. Trans. Roy. Soc. Lond. A329, 167–78.
   Google Scholar
• Reed, R. K. 1977. On Estimating insolation over the ocean. J. Phys. Oceanogr. 6, 781–800.
   Google Scholar
• Reynolds, R. W. 1988. A real-time global sea surface temperature analysis. J. Climate 1, 75–86.
   Web of Science ®Google Scholar
• Reynolds, R. W. and Marsico, D. C. 1993. An improved real-time global sea surface temperature analysis. J. Climate 6, 114–119.
   Web of Science ®Google Scholar
• Reynolds, R. W., Arpe, K., Gordon, C., Hayes, S. P., Leetmaa, A. and McPhaden, M. J. 1989. A comparison of tropical pacific surface wind analyses. J. Climate 2, 105–111. Tellus 46A (1994), 4
   Google Scholar
• Schopf, P. S. and Suarez, M. J. 1988. Vacillations in a coupled ocean-atmosphere model. J. Atmos. Science 45, 549–566.
   Web of Science ®Google Scholar
• Slingo, A. and Slingo, J. M. 1991. Response of the National Center for Atmospheric Research community climate model to improvements in the representation of clouds. J. Geophys. Res. 96, 15341–15357.
   Web of Science ®Google Scholar
• Sud, Y. C., Chao, W. C. and Walker, G. K. 1991. Contributions to the implementation of the Arakawa-Schubert cumulus parameterization in the GLA GCM. J. Atmos. Sci. 48,1573–1586.
   Web of Science ®Google Scholar
• Tibaldi, S., Palmer, T. N., Brankovic, C. and Cubasch, U. 1990. Extended-range prediction with ECMWF models: Influence of horizontal resolution on systematic error and forecast skill. Quat. J. Roy. Meteo. Soc. 116, 835–866.
   Web of Science ®Google Scholar
• Troen, I. and Mahrt, L. 1986. A simple model of the atmospheric boundary layer: Sensitivity to the surface evaporation. Bound. Layer Meteo. 37, 129–148.
   Web of Science ®Google Scholar
• Van den Dool, H. M. and Saha, S. 1993. On the seasonal redistribution of mass in a 10-year GCM run. J. Climate 6,22–30.
   Web of Science ®Google Scholar
• Wyrtki, K. 1975. El Nifio: The dynamical response of the equatorial Pacific to atmospheric forcing. J. Phys. Ocean. 5, 572–584.
   Web of Science ®Google Scholar
• Wyrtki, K. 1985. Water displacements in the Pacific and the genesis of El Nitio cycles. J. Geophy. Res. 90, C4, 7129–32.
   Web of Science ®Google Scholar
• Zebiak, S. E. and Cane, M. A. 1987. A model El Niño-Southern Oscillation. Mon. Weather Rev. 115, 2262–2278.
   Web of Science ®Google Scholar