Decoding ENSO Predictability: The Impact of Seasonality on Deterministic Dynamics and Noise Forcing

The El Niño-Southern Oscillation (ENSO) is a primary source of seasonal predictability in the climate system. It is well known that ENSO events and predictions exhibit strong seasonality, with ENSO peaking toward the end of the calendar year and ENSO forecast skill degrading through the boreal spring season. The evolution of individual ENSO events includes contributions from seasonally varying deterministic processes (that evolve from the initial state) and seasonality in noise-forcing that ultimately degrades the prediction. In this study we use a non-seasonal linear inverse model (LIM) and a cyclostationary LIM (CSLIM) to determine the roles of deterministic dynamics and noise forcing in the evolution of individual ENSO events. We find that seasonal dynamics are critical for characterizing the deterministic ENSO trajectory, and that seasonality in noise structure and amplitude is important for setting the time scale of ENSO predictability. Results will be presented that describe the role of seasonality in the evolution of ENSO events in general, and for individual historical ENSO events.