Prediction of NINO3 SST anomaly in a hybrid coupledwith a piggy-back data assimilation initialization

contributed by Hui Su and J. David Neelin

Department 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 el. (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 SV 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 May 2001 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 6- and 9-month leads have been quite consistent with the observations through the winter La Nina event, and the following weakening of the cold conditions towards near-normal conditions. Both 6-month and 9-month lead forecasts, which had been predicting a slight warming when issued earlier this year, are now predicting no warming. Lead month 3 has been tending to overpredict a slight warming from the current near-normal condition in recent months, which should be taken into account when considering the current forecast.

Figure 2 shows the latest two forecast results (starting from April and May, 2001, 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. The very small warming seen in the July 2001 forecast can be discounted due to the effect noted above for short leads. The 6-month and 9-month forecasts predict no significant departure from normal through the winter.

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

Latif, M., T. Stockdale, J. Wolff, G. Burgers, E. Maier-Reimer, M. M. Junge, K. Arpe, L. Bengtsson, 1994: Climatology and variability in the ECHO coupled GCM. Tellus, 46A, 351-366.

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 f"ur Meteorologie Report No. 15, Bundesstrasse 55, D-2000, Hamburg 13, FRG. D modes of the covariance matrix calculated from the time series of pairs of observed monthly mean Reynolds SST and Florida State University (FSU) 2pseudo-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

Reynolds, R. W., 1988: A real-time global sea surface temperature analysis. J. Climate, 1, 75-86.

Reynolds, R. W., T. M. Smith, 1994: Improved global sea surface temperature analyses using optimum interpolation. J. Climate, 7, 929-948.

Seager, R., S. E. Zebiak, M. A. Cane, 1988: A model of the tropical Pacific sea surface temperature climatology. J. Geophys. Res., 93, 1265-1280.

Syu H.-H., J. D. Neelin, D. Gutzler, 1995: Seasonal and interannual variability in a hybrid coupled GCM. J. Clim., 8, 2121-2143.

Waliser, D. E., B. Blanke, J. D. Neelin, C. Gautier, 1994: Shortwave feedbacks and El Nino-Southern Oscillation: Forced ocean and coupled ocean-atmosphere experiments.

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Fig.1 The forecasts of NINO3 SST anomalies from 1993 to present. The solid line indicates observations. The latest forecast starts from May 2001. 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 April and May 2001. 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.