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Consolidated Forecasts of Tropical Pacific
SST in Niño 3.4
Using Two Dynamical Models and Two Statistical
Models
contributed by David Unger, Anthony Barnston, Huug van
den Dool and Vern Kousky
Climate Prediction Center, NOAA, Camp Springs, Maryland
In this Bulletin we find a fairly large number of forecasts for the
east-central tropical Pacific SST for the coming year. Our objective here
is to synthesize information from some of the predictive sources into a
single objective estimate of the likely evolution of the SST's in the tropical
Pacific.
One approach to the problem is to combine, or consolidate, the forecasts
of several models into a single forecast. This could be done on the basis
of the past behavior of each contributing model, as well as the overlap
of information among the models. There are several methods by which this
can be done. A common method, and the one used here, is linear multiple
regression. In effect, a statistical scheme is used to combine outputs
of entire models whose natures themselves may be statistical, dynamical,
or a mixture of the two. In this case we use four input models. Two are
dynamical: the Lamont-Doherty Earth Observatory's simple coupled model
(the improved LDEO2; Chen et al. 1995; Cane and Zebiak 1986), and the recently
implemented CMP12 NCEP coupled model (Ji et al. 1994). The other two models
are statistical: the NCEP constructed analogue (CA) model (Van den Dool
1994; Van den Dool and Barnston 1995), and the NCEP canonical correlation
analysis (CCA) model (Barnston 1994). The individual forecasts of each
model are shown elsewhere in this Bulletin issue.
To derive the multiple regression equations for each target season for
each lead time, histories of the forecasts of each model were obtained.
The CCA and CA models have histories covering 1956-1995. The Lamont coupled
model has a 1972-95 history, and the NCEP coupled model 1981-95. To circumvent
the problem of the differing units and climatologies used, all forecasts
were converted to actual C forecasts. The observations were expressed likewise.
The regressions are based on forecasts for the Niño 3.4 region (5N-5S,
120-170W), except for the Lamont model, from which we receive forecasts
for the Niño 3 region. The Niño 3 forecast histories from
the Lamont model were used as a predictor for Niño 3.4 in the equation
development. The regression coefficients compensate for the slight differences
between Niño 3 and Niño 3.4 to obtain the least squares fit
for Niño 3.4. We expect to begin receiving gridded forecast fields
from Lamont shortly, and will then be able to use Lamont's Niño
3.4 forecasts directly.
The desired lead times of the consolidated forecasts range from 0.5 months
to 12.5 months by 1 month increments, where lead time is defined as the
time skipped between the time of the forecast and the beginning
of the forecasted (target) period. For example, the forecasts shown here,
which are issued in the middle of September 1996, have target periods including
Oct-Nov-Dec 1996, Nov-Dec-Jan 1996/1997,..., Oct-Nov-Dec 1997. Three of
the four individual models have forecast histories whose leads range to
12.5 months or greater, while one (the NCEP coupled model) has a maximum
lead of only 8.5 months. Consolidated forecasts for lead times higher than
8.5 months, therefore, are based only on the other three models; a slight
discontinuity in the forecast time series may thus be expected between
the Jun-Jul-Aug and the Jul-Aug-Sep 1997 forecasts.
Because the NCEP coupled model forecast only has a 1981-95 history, the
training period for the regression is limited to that period and thus results
in greater uncertainty in the coefficients than would be the case if a
longer history could be used. When that model is not included in the consolidation
process for the longer lead times, the 1972-95 period is used to derive
the regression equations, making for a more favorable training sample.
Data from three lead times were pooled together to help equation stability
and help smooth forecasts from projection to projection. Predictor and
predictand data from the season preceding and following the target season
were combined to form the regression equation. The first (last) target
season shares the equation with the adjacent season.
The consolidated forecast for Niño 3.4 resulting from the multiple
regression run in mid-September 1996, expressed as a standardized anomaly,
is shown in Fig. 1. The box and whisker intervals for the forecasts at
each time indicate the one and two error standard deviation, based on estimated
skill following shrinkage of the dependent sample skill results in accordance
with the sample size and number of predictors. The component forecasts
are displayed on the same chart for comparison. Note that the Lamont model
(CZ) anomalies are for Niño 3. The observed SST anomaly for the
most recent 3-mo period is also shown.
The consolidation forecast remains within about a half of a standard deviation
of normal throughout the 12.5 month forecast period, with a suggestion
of some very slight positive anomalies in late 1996 and then a return to
slightly cool anomalies early next year. With no clear indication of a
sustained warming or cooling, the prediction is essentially for a continuation
of the near normal temperatures that have been observed in the Niño
3.4 region for the past month.
It is interesting to note that the temperatures in the Niño 3 region
have been somewhat cooler than in Niño 3.4. This may explain some
of the difference between the plotted CZ model forecast, which are for
Nino3, and the consolidation forecast in the early leads. The regression
coefficients may have responded to the offset in position by giving a low
weight to the CZ model in the initial projections, when the spatial resolution
of the models is more important than at longer leads. At the longer projections,
the consolidation reflects a more even weighting between the models, since
the location difference between the two Niño regions becomes less
important in relation to the overall uncertainty in the evolution of the
SSTs with time.
The error bars abruptly increase in width in the spring of 1997, reflecting
the so-called spring barrier noted in SST predictions in regions related
to ENSO. Forecasts at leads greater than 6.5 months may be considered quite
close to climatology, with slight variations in anomalies just as likely
to be due to sampling variability as reflecting any real trend.
Acknowledgments: We are grateful to Stephen Zebiak and Mark Cane of
Lamont Doherty Earth Observatory, and Ming Ji and Ants Leetmaa from the
National Centers for Environmental Prediction, for providing the forecast
histories from their respective dynamical models, as well as their current
real-time forecasts.
References
Barnston, A.G., 1994: Linear statistical short-term climate predictive
skill in the Northern Hemisphere. J. Climate, 5, 1514-1564.
Cane, M., S.E. Zebiak and S.C. Dolan, 1986: Experimental forecasts of El
Niño. Nature, 321, 827-832.
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.
Ji, M., A. Kumar and A. Leetmaa, 1994: An experimental coupled forecast
system at the National Meteorological Center: Some early results. Tellus,
46A, 398-418.
van den Dool, H.M., 1994: Searching for analogues, how long must we wait?
Tellus, 46A, 314-324.
van den Dool, H.M. and A.G. Barnston, 1995: Forecasts of global sea surface
temperature out to a year using the constructed analogue method. Proceedings
of the 19th Annual Climate Diagnostics Workshop, November 14-18, 1994,
College Park, Maryland, 416-419.
Figures
Figure
1. Consolidated forecast (thick line) for the standardized anomaly
of the SST in the Nino 3.4 region (5N-5S, 120-170W) for the next
12-running 3-month periods. Month labels on the abscissa denote the
middle months of the 3-month predictand period. Box and whiskers for
each point indicate the one and two error standard deviation intervals.
The latest observation (Jun-Jul-Aug 19960 is also shown by the filled
ellipse. The prediction from each component model is shown for
comparison.
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