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Application of the El Niño-Southern Oscillation CLImatology

andPERsistence (CLIPER) Forecasting Scheme

contributed by John Knaff¹ and Christopher Landsea²

¹Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado

²NOAA/AOML/Hurricane Research Division, Miami, Florida

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 December 1997 initialization date yields forecasts for Dec-Jan-Feb 1997 (lead 0) out through Sep-Oct-Nov 1999 (lead 7). Forecasts for the Niño 3.4 region SST and the SOI are shown in Fig. 1. These forecasts indicate that SST anomalies have already peaked during the previous season (2.60C) and are expected to very rapidly become below normal by Jun-Jul-Aug 1998 (-0.53C). The cold event is expected to peak during the Dec-Jan-Feb 1998-99 season (-1.42C). For the short leads these forecasts are almost solely based on the persistence of initial conditions. At longer leads trends in both Niño 3.4 and Niño 4 along with the initial SOI, and Niño 3.4 conditions, play a significant role in determining the cooling to come in the summer and fall of 1998. For forecasts of the other Niño regions visit the web site given in the preceding paragraph.

ENSO CLIPER forecasts of Niño 3.4 made for the last several seasons have verified reasonably (Table 1). While they underestimated the intensity of the 1997 warming, they did predict warming. The strength of the warm forecast has increased in parallel with the increas-es in the observed initial state. In addition, ENSO CLI-PER has been, since June 1997, consistently predicting the rapid cooling expected to occur in spring 1998.

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 com-ments concerning this work. The lead author was sup-ported by NOAA under contract NA37RJ0202 (Wil-liam 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, 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.

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	Forecast Made Sep 1997	Observed Anomaly
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	2.12	2.60
DJF 97-98	0.58	0.81	2.51	2.80	we will see
MAM 98	0.41	0.36	0.96	0.89	we will see
JJA 98	0.19	0.38	0.09	0.09	we will see

Fig. 1a, b. Forecast of (a) Niño 3.4 SST and (b) SOI using data available through the 1 December 1997. Forecasts are valid for Dec-Jan-Feb (DJF) 1997-98, MAM 1998, JJA 1998, SON 1998, DJF 1998-99, MAM 1999, JJA 1999 and SON 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.

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