Application of the El Niño-Southern Oscillation CLImatology

and PERsistence (CLIPER) Forecasting Scheme

Christopher W. Landsea¹ and John A. Knaff²

¹NOAA/AOML/Hurricane Research Division, Miami, Florida

²Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins,Colorado

To provide a baseline of skill in seasonal ENSO forecasting, a multiple regression has been used to take best advantage of CLImatology, PERsistence and trend of initial conditions - the ENSO-CLIPER (Knaff and Landsea 1997). This replaces simple persistence as a skill threshold. "Skill" is then redefined as the ability to outforecast the ENSO-CLIPER - a more difficult task.

This statistical prediction method is based entirely on the optimal combination of persistence, month-to-month trend of initial conditions and climatology. Multiple least squares regression is employed to test a total of fourteen possible predictors for the selection of the best predictors, based upon 1950-1994 developmental data. A range of zero to four predictors were chosen in developing twelve separate regression models, developed separately for each initial calendar month. The predictands to be forecast include the Southern Oscillation (pressure) Index (SOI) and the Niño 1+2, Niño 3, Niño 4 and Niño 3.4 SST indices for the equatorial eastern and central Pacific at lead times ranging from zero seasons (0 - 2 months) through seven seasons (21 - 23 months). Though hindcast ability is strongly seasonally dependent, substantial improvement is achieved over simple persistence wherein largest gains occur for two to seven season (6 to 23 months) lead times. The ENSO-CLIPER model thus not only offers a baseline "no-skill" forecast of ENSO variability, but a practical forecast based upon the CLIPER premise.

The regression design called leaps and bounds (IMSL 1987) is used to develop optimal models (the best subsets of a prescribed number of predictors). Predictors include 1, 3 or 5 month averages of initial predictor anomalies as well as their recent trends. Predictors are the predictands themselves at earlier times. Some limits on predictor selection were imposed to reduce overfitting (Aczel 1989). Skills are degraded from dependent sample results to reflect estimated independent forecast skill following Davis (1979) and Shapiro (1984). Final skill estimates reflect levels comparable to those of more sophisticated statistical and dynamical models. More details about the ENSO-CLIPER model, including its skill and its predictor selection rules, are given in the June 1997 issue of this Bulletin (p. 55). A copy of Knaff and Landsea (1997) as well as future monthly ENSO-CLIPER forecasts are available at the Web site: http://tropical.atmos.colostate.edu/~knaff. The program to run ENSO-CLIPER is also available upon request.

Employing the chosen predictors in the ENSO-CLIPER model on a 1 June 1999 initialization date yields forecasts for Jun-Jul-Aug 1999 (zero season lead) out through Mar-Apr-May 2001 (seven season lead). Results for just the Niño 3.4 region SST and the SOI are shown in Fig. 1. These forecasts indicate that there may be a continuation of weak to moderate La Niña conditions through Dec-Jan-Feb of 1999-2000, with a change to a moderate El Niño regime by Sep-Oct-Nov 2000. The short leads are based primarily upon persistence of initial conditions, while the change to El Niño-like conditions in one year's time depend upon the climatological preference to change phase on the biennial timescale.

ENSO-CLIPER predictions made over the last several seasons have verified reasonable well (Table 1, and past ELLFB issues). The onset of La Niña conditions in Jun-Jul-Aug 1998 was suggested by ENSO-CLIPER to occur consistently back to early June 1997 forecasts, though its magnitude was also not correctly predicted. Lead 0 and Lead 1 forecasts continue to perform extremely well. Over the last couple of years the performance of this model has been very competitive with both statistical and numerical ENSO forecast models. This fact suggest that there is no skill (above the performance shown by ENSO-CLIPER) associated with present ENSO forecast schemes (Barnston et al. 1999).

Acknowledgments: The authors wish to thank William Gray, Tony Barnston, John Sheaffer, Dave Enfield, Dennis Mayer, Barb Brumit, Amie Hedstrom, Bill Thorson and Rick Taft for all their help and comments concerning this work.

The lead author is being supported by NOAA under contract NA67RJ0152 and is employed with the Regional Mesoscale Meteorology Team at CIRA. The second author was funded through the 1995-96 NOAA Postdoctoral Program in Climate and Global Change.

References:

Aczel, A. D., 1989: Complete Business Statistics. Richard D. Irwin, Inc., 1056 pp.

Barnston, A. G., M. H. Glantz, and Y. He, 1999: Predictive skill of statistical and dynamical climate models in SST forecasts during the 1997-98 El Niño episode and the 1998 La Niña onset. Bull. Amer. Meteor. Soc., 80, 217-243.

Davis, R. E., 1979: A search for short range climate productivity. Dyn. Atmos. Oceans, 3, 485-497.

IMSL, 1987: FORTRAN subroutines for statistical analysis. International Mathematical & Statistical FORTRAN Library, 1232 pp.

Knaff, J. A. and C. W. Landsea, 1997: An El Niño-Southern Oscillation CLImatology and PERsistence (CLIPER) Forecasting Scheme. Wea. Forecasting , 12, 633-652.

Shapiro, L. J., 1984: Sampling errors in statistical models of tropical cyclone motion: A comparison of predictor screening and EOF techniques. Mon. Wea. Rev. , 112, 1378-1388.

Figure 1: Forecast of Niño 3.4 and SOI using data available through 1 June 1999. Forecasts are valid for Jun.-Aug. (JJA) 1999, Sep.-Nov. (SON) 1999, Dec.-Feb. (DJF) 1999-2000, MAM 2000, JJA 2000, SON 2000, DJF 2000-2001 and MAM 2001. Actual numerical forecast values for these times are shown on each plot along with estimated RMSE bars. These anomalies are based upon a 1950-1979 mean.

Table 1: Recent history of ENSO-CLIPER forecasts and corresponding observations for the Niño 3.4 SST region (in degree C).

Target Period	Forecast Made 1 Dec 1977	Forecast Made 1 Mar1998	Forecast Made 1 Jun 1998	Forecast Made 1 Sep 1998	Forecast Made 1 Dec 1998	Forecast Made 1 Mar1999	Observed Anomaly
DFJ 97-98	2.25	-	-	-	-	-	2.6
MAM 98	0.80	1.21	-	-	-	-	1.2
JJA 98	-0.53	-0.03	-0.16	-	-	-	-1.06
SON 98	-0.74	-0.06	-1.09	-1.06	-	-	-1.16
DJF 98-99	-1.42	-0.05	-0.84	-1.81	-1.02	-	-1.55
MAM 99	-0.81	-0.65	-0.32	-1.59	-0.28	-0.82	-0.71
JJA 99	-0.72	-0.94	0.13	0.13	0.02	-0.53	-