Prediction of NINO3 SST anomaly in a hybrid coupled model with a piggy-back data

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 SVD modes of the covariance matrix calculated from the time series of pairs of observed monthly mean Reynolds SST anomalies and Florida State University (FSU) subjective pseudo-stress anomalies over a 19-year period from January, 1970 through December, 1988. Atmospheric adjustment is parameterized by a simple 60-day spin-up time scale (Syu and Neelin 2000a). 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 (see Syu and Neelin 2000a for model details).

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, with further analysis in Syu and Neelin (2000b).The ocean climatology used in all hindcast/forecast experiments is specified to be the averaged model SST, forced by the FSU subjective wind stress product 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 subjective wind stress over the same period (1978-1993). The forecast results from 1991 to present been verified against the observations from the Reynolds optimal interpoloation (OI) SST data set (Reynolds et at., 2002; Reynolds 1988; Reynolds and Smith 1994), now referred to as Reynolds OI SST version 1. Recently this version 1 product was discontinued and replaced with a version 2 SST product (Smith and Reynolds 1998). Verification observed SST anomalies are now shown against the version 2 product.

The initialization scheme makes use of wind information (FSU pseudo-stress converted to wind stress), the ocean model data assimilation product from the Climate Prediction Center (CPC) (Ji et al., 1995) and SST anomalies to initialize the atmospheric model. In addition to specifying 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 (see the Sep. 1997 issue and Syu and Neelin 2000b), and thus appears to be a viable, economical forecast method.

In March 2002, Florida State University (FSU) changed to an objectively analyzed pseudo-stress product (Bourassa et al., 2001). Description of the impacts of this objective wind stress product on our forecast scheme are given in the June

2002 issue of ELLFB for runs over the period 1993 to June 2002. The change to Reynolds OI SST version 2 was made as of our June 2003 forecast. In neither case was the forecast system itself altered, aside from the change in data set. While changes in each data set are not large, they do have noticable impacts upon forecasts. We have therefore re-run model initialization runs and hindcasts over the baseline period 1982-93, using the two new data sets, and recomputed the model drift and error bars as the mean and root-mean-square error in SST anomaly, respectively, as a function of forecast lead time over all hindcasts in that period. To minimize the alteration in the forecast scheme, both the FSU objective wind stress and the Reynolds OI version 2 SST product are used as anomalies with respect to their 1978-1993 mean. Figures 1 and 2 present the NINO3 index for forecasts and initialization from 1993 to present overlaid onto previously published forecasts through September 2003. The previously published forecasts utilized the subjective FSU wind product until March 2002 and Reynolds OI version 1 SST until July 2003. We note that the previously published initialization contains a substantial jump in SST anomaly at the time of the switch to FSU objective winds.

Figure 1 shows NINO3 SSTAs for observations (3-month running average, thick black curves) and past and current forecasts (gray curves) at 0-, 3-, 6- and 9-month lead (previously published results dashed gray curves). Averages of each lead month based on forecast verification over the 1982-1993 time span are removed before plotting the curves. Vertical bars represent plus and minus one RMS error, over the same forecast verification time span. The cooling shown in the previous forecast continues to be seen in the NINO3 SST anomaly forecasts for the 3- and 6-month leads. The 9-month lead forecast has been for near normal conditions for the beginning part of 2005.

Figure 2 shows the latest two forecast results (starting from April and May, 2004, respectively, for 12 months, dark dotted line), with the mean over the forecast verification time span (1982-1993) removed. The observations (solid line), model initialization run (dark dashed line) and the previously published results (light dashed line) since 1993 are also displayed. Forecasts initiated with April and May observations both show cooling in NINO3 continuing through the end of summer 2004. While the minimum is sufficiently cold to classify as La Nina conditions we caution that the model has over predicted some past coolings. A moderate temperature increase follows to normal conditions for late 2004 and early 2005.

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