A SIMULATION OF VARIABILITY OF ENSO FORECAST SKILL

In many prediction schemes, the skill of long-range forecasts of ENSO events depends on the time of year. Such variability could be directly due to seasonal changes in the basic ocean-atmosphere system or due: to the state of ENSO itself. A highly idealized delayed oscillator mod el with seasonally varying internal parameters is used here to simulat e such behavior. The skill of the artificial forecasts shows dependenc e on both seasonal and ENSO phase. Experiments with ENSO phase-locked to the seasonal cycle, but with no seasonal variation of model paramet ers, show that the ENSO cycle alone can induce variability in skill. I nclusion of seasonal parameters enhances seasonal skill dependence. It is suggested that the seasonal skill variations found in practice are due to a combination of seasonal changes in the basic state and the p hase-locking of the ENSO and annual cycles.