SST predictions with an intermediate coupled model of the tropical Pacific.

contributed by Boris Dewitte¹, Dasha Gushchina ², Yves duPenhoat ¹ and Rodrigo Abarca del Rio³

¹LEGOS/CNES/IRD 14 Av. E. Belin, 31401 Toulouse Cedex 4, France
²Meteorological Department, Geographical Faculty, Moscow State University, Vorobyevy gory, Moscow, 119899, Russia
³ DEFAO, University of Concepcion, Casilla 160-C, Concepcion, Chile

Forecasts of the tropical Pacific SST are presented here using two intermediate coupled models. The oceanic component consists in a three baroclinic mode ocean and the mixed layer model differs from the Cane and Zebiak (1987) model in the parameterization of the vertical advection terms and the basic state (cf. Dewitte, 2000). The atmospheric component is either a statistical atmospheric model based on the singular value decomposition (SVD) of observed sea surface temperature (SST) and wind stress anomalies (see Périgaud et al., 2000) or a Gill(1980)'s dynamical tropical atmosphere. Initial conditions for the prediction runs are produced in a coupled mode by nudging the observed winds (FSU winds for the period 1961-1992, ERS1-2 winds from may 1992 until september 2000, QuikSCAT winds from october 2000) to the simulated winds as in Chen et al. (1995). The skill of the models for the NINO3 SST index over various periods and for the 1997-1998 El Niño is presented in Dewitte et al. (2002).

Figure 1 shows model predicted SST and wind stress anomalies in the tropical Pacific for the next four seasons in the case of the statistical atmosphere. These are ensemble averages of 12 forecasts started from Mar-Apr-May 2004 conditions. For producing the initial conditions of the individual forecasts, random noise was added to the system with an approach similar to Kirtman and Schopf (1998).

The model using the statistical atmosphere is predicting slightly cold conditions for 2004, whereas the model using the dynamical atmosphere (figure 2) predicts slightly warm conditions developing from the Sep-Oct-Nov 2004 season.

Caveat: The forecasts shown above are experimental in nature. The reader is forewarned that the methods/forecasts are new and subject to future change and improvement.

References:

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

Dewitte B., 2000: Sensitivity of an intermediate coupled ocean-atmosphere model of the tropical Pacific to its oceanic vertical structure. J. Climate, 13, 2363-2388.

Dewitte B., D. Gushchina, Y. duPenhoat and S. Lakeev, 2002: On the importance of subsurface variability for ENSO simulation and prediction with intermediate coupled models of the Tropical Pacific: A case study for the 1997-1998 El Niño. Geoph. Res. Lett., 29 (14). (15 jul. 2002)

Gill, A., Some simple solutions heat-induced tropical circulation. Q. J. R. Meteorol. Soc., 106, 447-462, 1980.

Kirtman, B. P. and P. S. Schopf, 1998: Decadal variability in ENSO predictability an prediction, J. Climate, 11, 2804-2822

Périgaud C. C. Cassou, B. Dewitte, L.-L. Fu and D. Neelin, 2000: Using data and intermediate coupled models for seasonal-to-interannual forecasts. Mon. Wea. Rev., 128, 3025-3049.

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

Figure Captions:

Fig. 1:  model  forecast of tropical Pacific SST (°C) and wind stress (Dyn/cm²) anomalies for JJA 2004, SON 2004, DJF 2004/2005 and MAM 2005. Each forecast is an ensemble average of 12 sets of prediction runs initialized from wind forced model outputs perturbated by random noise. Observed data through 28^th of May 2004 was used to produce the forecast. Contour interval 0.5°C. Regions with SSTA amplitude larger than 0.5°C (lower than -0.5°C) are in yellow-orange (blue). The longuest wind stress arrow on each map corresponds to the value indicated on the right hand side. Only wind stress anomalies for which wind modulus is larger than 0.1 Dyn/cm² are plotted.

Fig.2: same as Fig. 1 but for the coupled model using the dynamical atmosphere.