Austral Summer MJO Forecast Skill in S2S Models: Decadal Shifts and Their Drivers

Abstract. The Madden–Julian Oscillation (MJO) is a key driver of global subseasonal-to-seasonal (S2S) climate variability, influencing tropical convection and initiating teleconnections that affect weather patterns worldwide. Improving understanding of the factors that constrain MJO predictability is therefore critical for advancing S2S forecasting systems. Using a multi-model framework, we evaluate changes in MJO prediction skill between two periods (1981–1998 and 1999–2018) during austral summer (December–February) and examine the processes underpinning these differences. Our analysis reveals a pronounced decadal decline in MJO forecast skill, with high-skill years in 1981–1998 showing prediction lead times of around 10 days longer (based on the bivariate correlation of the RMM index) than in 1999–2018, while low-skill years show little change. This asymmetric reduction coincides with stronger MJO amplitude in the earlier period, despite relatively stable model mean-state biases in tropical SSTs and lower-tropospheric moisture. Key findings include: (1) persistent moisture biases across both periods, yet higher skill in 1981–1998, suggesting that model errors alone cannot explain the differences; (2) a stronger Quasi-Biennial Oscillation (QBO)–MJO relationship in the first period, independent of stratospheric resolution; and (3) weakened coupling between the MJO and large-scale climate modes, including the QBO, El Niño–Southern Oscillation (ENSO), and Indian Ocean Dipole (IOD), in 1999–2018, indicating reduced dynamical support for prediction. These results suggest that decadal variations in MJO skill are strongly influenced by changes in the background dynamical environment. They highlight the need for S2S systems to improve representation of tropospheric processes and stratosphere–troposphere coupling, particularly when large-scale climate forcing is weak.