To provide a baseline of skill in seasonal ENSO forecasting, 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 out-forecast the ENSO-CLIPER--a more difficult task.

This statistical prediction method is based on an optimal combination of persistence, month-to-month trend of initial conditions, and climatology. 14 candidate predictors are made available for the selection, based on the 1950-1994 period. Zero to four predictors were chosen for regression models for each of the calendar months. The predictands to be forecast include the Southern Oscillation (pressure) Index (SOI), and the Niño 1+2, 3, 3.4 and 4 SST indices at lead times ranging zero to over 20 months. While hindcast skill is very 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 on a 1 September 1997 initialization date yields forecasts for Sep-Oct-Nov 1997 (lead 0) out through Jun-Jul-Aug 1999 (lead 7). Forecasts for the Niño 3.4 region SST and the SOI are shown in Fig. 1. These forecasts indicate SST anomalies peaking (2.80C in Niño 3.4) in Dec-Jan-Feb 1997-98 and then somewhat rapidly returning to near normal by Jun-Jul-Aug 1998 (0.09C for Niño 3.4) with a strong indication of cool conditions returning to the whole of the equatorial Pacific by the Sep-Oct-Nov 1998 period (-0.45C for Niño 3.4). For the short leads, these forecasts are based almost solely upon the persistence of initial conditions. At longer leads the upward trend of Niño 3.4 along with the initial SOI conditions play a significant role in determining the cooling in spring/early summer 1998.

ENSO-CLIPER forecasts Niño 3.4 made 1, 2 and 3 seasons ago have verified reasonably (Table 1). While they underestimated the intensity of the warming that has occurred, they did predict warming. The strength of the warm forecast has increased in parallel with the increases in the observed initial state.

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 was supported by NOAA under contract NA37RJ0202 (William Gray, PI) with supplemental support given by NSF under contracts ATM-9417563 (William Gray, PI). The second author was funded through the 1995-96 NOAA Postdoctoral Program in Climate and Global Change.

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

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, in press.

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.

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

Target  Period	Forecast Made  Dec 1996	Forecast Made  Mar 1997	Forecast Made Jun 1997	Observed
DJF 96-97	-0.20	--	--	-0.46
MAM 97	0.13	-0.03	--	0.46
JJA 97	0.19	0.52	1.52	1.70
SON 97	0.59	0.72	2.04	we will see
DJF 97-98	0.58	0.81	2.51	we will see

 
 
 
 
 

Fig. 1. Forecast of Niño 3.4 SST and SOI using data available through the 1 September 1997. Forecasts are valid for Sep-Nov (SON) 1997, Dec-Feb (DJF) 1997-98, MAM 1998, JJA 1998, SON 1998, DJF 1998-99, MAM and JJA 1999. Actual numerical forecast values for these times are shown on each plot along with estimated RMSE bars. These anomalies are based on a 1950-1979 mean.