Prediction of NINO3 SST anomaly in a hybrid coupled model with a

piggy-back data assimilation initialization

Hsin-Hsin Syu¹ and J. David Neelin²

¹Jet Propulsion Laboratory California Institute of Technology, Pasadena, California

²Department of Atmospheric Science University of California, Los Angeles, California

A hybrid coupled model (HCM), similar to the one used in Syu et al. (1995), Waliser et al. (1994) and Blanke et al. (1997), is used to predict the NINO3 SST anomaly (SSTA). The atmospheric model is estimated from observations using a singular value decomposition (SVD) technique. The model contains the first seven SVD modes of the covariance matrix calculated from the time series of pairs of observed monthly mean Reynolds SST and Florida State University (FSU) pseudo-stress fields (both anomalies) over a 19-year period from January, 1970 through December, 1988. Atmospheric spin-up time, which was neglected in the previous version, is parameterized, albeit crudely, in the current version within coupling procedures. A 60-day spin-up time scale is chosen for all ENSO simulations and predictions. Heat flux is parameterized according to Oberhuber's (1988) formulation using climatological data, with the negative feedback on SST estimated following Seager et al. (1988). The OGCM is a version of the GFDL Modular Ocean Model (Pacanowski, Dixon and Rosati, 1991, personal communication) for the Pacific basin. The vertical resolution is 27 levels, with 10 levels in the upper 100 meters. A Richardson-number-dependent vertical mixing scheme is combined with a surface mixed layer parameterization, as employed in Latif et al. (1994).

The HCM has a reasonable simulation of ENSO in spatial and temporal features, with ENSO periods of 3 to 4 years. Model performance in "retroactive real-time forecasts" (hindcasts hereafter) from 1980-1992 has been shown in the September 1997 issue of the Experimental Long-Lead Forecast Bulletin. The ocean climatology used in all hindcast/forecast experiments is specified to be the averaged model SST, forced by FSU wind stress over 1978 to 1993 without modification by the data assimilation scheme. The climatological wind stress used in the hindcast/forecast experiments is also specified to be the average of the FSU wind stress over the same period (1978-1993). The forecast results after 1994 are verified against the observations from Reynolds' (1988) SST data set after applying optimum interpolation method as described in Reynolds and Smith (1994).

The initialization scheme makes use of both the wind information (FSU converted wind stress) and the ocean model data assimilation product from the Climate Prediction Center (CPC; Ji et al., 1995). In addition to the specified FSU wind stress forcing, the CPC reanalyzed anomalous ocean temperature field is "injected" into the ocean model (27 layers) every month since 1980 up to the start of the hindcast (injection scheme hereafter). Because our ocean model (GFDL MOM) is in a version reasonably close to that used by CPC, approximate consistency is assumed in injecting the CPC reanalyzed data. To make distinction between this procedure and raw-data injection, we refer to it as a "piggy-back" data assimilation scheme, because it makes use of the effort from an CPC data assimilation product. The "piggy-back" data assimilation scheme gives a substantial improvement in hindcast skill, as shown in the Sep.1997 issue, and thus appears to be a viable and economical forecast method.

Figures 1 and 2 present the NINO3 index for forecasts from 1993 to present. Observations through April 1999 are used. Figure 1 shows NINO3 SSTAs for observations (3-month running average, thick black curves) and forecasts (gray curves) at 3-, 6- and 9-month lead. Averages of each lead month based on forecast verification over the 1980-1992 time span are removed before plotting the curves. Vertical bars represent plus and minus one RMS error, over the same forecast verification time span. NINO3 SST anomaly forecasts for all lead months shown in Fig. 1 suggest that the current La Niña phase will continue through summer 1999. All lead months shown here predict continuing and intensifying cold SST anomalies. This has been generally consistent in recent forecasts, although forecasts at 3 and 6 month leads from two months ago had been predicting a weakening of the cold phase.

Figure 2 shows the latest two forecast results (starting from March and April, 1999, respectively, for 12 months), with the mean over the forecast verification time span (1980-1992) removed. The observation and model initialization run since 1993 are also displayed. Both forecasts predict an increase in magnitude of the cold anomalies through out the rest of 1999 with the maximum amplitudes occurring around winter 1999.

References

Blanke, B., J. D. Neelin, and D. Gutzler, 1997: Estimating the effect of stochastic wind stress forcing on ENSO irregularity. J. Climate, 10, 1473-1486.

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

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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. Max-Planck-Institut für Meteorologie Report No. 15, Bundesstrasse 55, D-2000, Hamburg 13, FRG.

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Waliser, D. E., B. Blanke, J. D. Neelin, and C. Gautier, 1994: Shortwave feedbacks and El Niño-Southern Oscillation: Forced ocean and coupled ocean-atmosphere experiments. J. Geophys, Res., 99, 25109-25125.

Figures:

Fig. 1. The forecasts of NINO3 SST anomalies from 1993 to present. The solid line indicates observations. The latest forecast starts from April 1999. The mean for each lead month over the forecast verification time span (1980-92) is removed before plotting. Vertical bars represent plus and minus one RMS error over the same forecast verification time span. Shown for (a) 3-month, (b) 6-month and (c) 9-month lead.

Fig. 2. The latest two forecasts (dotted lines) of NINO3 SST anomalies up to 12 lead months starting from March and April 1999. Observations (solid line) and model control run (dashed line) from 1993 to present are also shown. The mean for each lead month is removed as in Fig. 1. Vertical bars indicate the same plus and minus one RMS error used in Fig. 1.