This replaces simple persistence as a skill threshold. 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.
Predictors are the predictands themselves at earlier times.
Final skill estimates reflect levels comparable to those of more sophisticated statistical and dynamical models. 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. 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 second author was funded through the 1995-96 NOAA Postdoctoral Program in Climate and Global Change.