Asymmetry in ENSO Prediction Skill Linked to Consecutive La Niña Events Within the IRI Real‐Time Forecast System

Accurately predicting the El Niño–Southern Oscillation (ENSO) remains a key challenge in climate science. An evaluation of the International Research Institute for Climate and Society (IRI) real‐time ENSO forecast system reveals an asymmetry in prediction skill linked to consecutive La Niña events. ENSO forecasts show consistently high skill for El Niño events, whereas La Niña forecasts exhibit greater uncertainty. Specifically, first‐year La Niña events demonstrate prediction skill comparable to that of El Niño events; however, most consecutive La Niña events display much lower predictability. This asymmetry is related to differences in ENSO dynamics. El Niño and first‐year La Niña events typically follow the linear recharge–discharge oscillator framework, supporting their high predictability. In contrast, consecutive La Niña events tend to deviate from this framework, likely due to enhanced nonlinear processes that constrain their forecast skill. Improved representation of these nonlinear processes may help enhance prediction skill for consecutive La Niña events.