Influence of stochastic forcing on ENSO prediction

Journal of Geophysical Research: Oceans

Volumn 109, Issue 11, 2004, Pages

  Zavala Garay, Javier ^a   Moore, Andy M ^b   Kleeman, R ^c  

^a UNIVERSITY OF MIAMI   (United States)

^b UNIVERSITY OF COLORADO   (United States)

^c NEW YORK UNIVERSITY   (United States)

Author keywords

Data assimilation; ENSO prediction; Stochastic model

Indexed keywords

AIR-SEA INTERACTION; CLIMATE FORCING; DATA ASSIMILATION; EL NINO-SOUTHERN OSCILLATION; FORECASTING METHOD; STOCHASTICITY;

EID: 12444272696     PISSN: None     EISSN: 21699291     Source Type: Journal    
DOI: 10.1029/2004JC002406     Document Type: Article

References (31)

1. Cane, M. A., S. E. Zebiak, and S. C. Dolan (1986), Experimental forecast of El Niño, Nature, 321, 827-834.
2. Chen, D., S. E. Zebiak, A. J. Busalacchi, and M. A. Cane (1995), An improved procedure for El Niño forecasting: Implications for predictability, Science, 269, 1699-1702.
3. Demit, F. L., and O. Talagrand (1986), Variational algorithms for analysis and assimilation of meteorological observations: Theoretical aspects, Tellus, Ser. A, 38, 97-100.
4. Flügel, M., and P. Chang (1998), Does the predictability of ENSO depend on the seasonal cycle?, J. Atmos. Sci., 55, 3230-3243.
5. Ghil, M., and N. Jiang (1998), Recent forecast skill for the El Niño/Southern Oscillation, Geophys. Res. Lett., 25, 171-174.
6. Gill, A. (1982), The tropics, in Atmosphere-Ocean Dynamics, chap. 11, pp. 429-491, Academic, San Diego, Calif.
7. Ji, M., and A. Leetmaa (1996), Impact of data assimilation on ocean initialization and El Niño prediction, Mon. Weather Rev., 125, 742-753.
8. Ji, M., A. Kumar, and A. Leetmaa (1994), An experimental coupled forecast system at the National Meteorological Center: Some early results, Tellus, Ser. A, 46, 398-418.
9. Kalnay, E., et al. (1996), NCEP/NCAR 40-years reanalysis project, Bull. Am. Meteorol. Soc., 77, 437-441.
10. Kirtman, B. P., and P. S. Schopf (1998), Decadal variability in ENSO predictability and prediction, J. Clim., 11, 2804-2822.
11. Kirtman, B. P., J. Shukla, M. Balmaseda, N. Graham, C. Penland, Y. Xue, and S. Zebiak (2002), Current status of ENSO Forecast Skill: A report to the Climate Variability and Predictability (CLWAR) Numerical Experimentation Group (NEG), WCRP Informal Rep. 23/01, World Clim. Res. Programme, Geneva.
12. Kleeman, R. (1991), A simple model of the atmospheric response to ENSO sea surface temperature anomalies, J. Atmos. Sci., 48, 3-18.
13. Kleeman, R. (1993), On the dependence of hindcast skill on ocean thermodynamics in a coupled ocean-atmosphere model, J. Clim., 6, 2012-2033.
14. Kleeman, R., and A. M. Moore (1999), A new method for determining the reliability of dynamical ENSO predictions, Mon. Weather Rev., 127, 694-705.
15. Kleeman, R., A. 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. Weather Rev., 123, 3103-3113.
16. Lau, K. M. (1985), Elements of a stochastic dynamical theory of the long-term variability of the El Niño-Southern Oscillation, J. Atmos. Sci. 42, 1552-1558.
17. Lau, K., and P. H. Chan (1986), The 40-50 day oscillation and the El Niño/Southern Oscillation: A new perspective, Bull. Am. Meteorol. Soc., 67, 533-534.
18. McPhaden, M. J. (2003), Tropical Pacific Ocean heat content and ENSO persistence barriers, Geophys. Res. Lett., 30(9), 1480, doi:10.1029/2003GL016872.
19. Moore, A. M. (1989), Aspects of geostrophic adjustment during tropical ocean data assimilation, J. Phys. Oceanogr., 19, 435-461.
20. Moore, A. M., and R. Kleeman (1999), Stochastic forcing of ENSO by the intraseasonal oscillation, J. Clim., 12, 1199-1220.
21. Penland, C. (1996), A stochastic model of Indo Pacific sea surface temperature anomalies, Physica D, 98, 534-558.
22. Penland, C., and L. P. D. Sardeshmukh (1995), The optimal growth of tropical sea surface temperature anomalies, J. Clim., 8, 1999-2024.
23. Reynolds, R. W., and T. M. Smith (1994), Improved global sea surface temperature analyses using optimal interpolation, J. Clim., 7, 929-948.
24. Rosati, A., K. Miyakoda, and R. Gudgel (1997), The impact of ocean initial conditions on ENSO forecasting with a coupled model, Mon. Weather Rev., 125, 754-772.
25. Sasaki, Y. (1970), Some basic formalisms in numerical variational analysis, Mon. Weather Rev., 98, 875-883.
26. Shinoda, T., H. H. Hendon, and J. Glick (1999), Intraseasonal surface fluxes in the tropical western Pacific and Indian Oceans from NCEP reanalyses, Mon. Weather Rev., 127, 1685-1702.
27. Talagrand, O., and P. Courtier (1987), Variational assimilation of meteorological observations with the adjoint vorticity equation: I. Theory, Q. J. R. Meteorol. Soc., 113, 1329-1347.
28. Trenberth, K. E., G. W. Branstator, D. Karoly, A. Kumar, C. Lau, and C. Ropelewski (1998), Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures, J. Geophys. Res., 103, 14,291-14,324.
29. Webster, P. J. (1972), Response of the tropical atmosphere to local, steady forcing, Mon. Weather Rev., 100, 518-541.
30. Zavala-Garay, J., A. M. Moore, C. L. Perez, and R. Kleeman (2003), The response of a coupled model of ENSO to observed estimates of stochastic forcing, J. Clim., 16, 2827-2842.
31. Zebiak, S. E. and M. A. Cane (1987), A model of El Niño-Southern Oscillation, Mon. Weather Rev., 115, 2262-2278.