How ENSO Modifies Propagation of the Boreal Summer Intraseasonal Oscillation (BSISO) in the Asian Monsoon Region

Oral Presentation 

While significant progress has been made in the skilful prediction of the Madden-Julian Oscillation (MJO), the forecast skill of the Boreal Summer Intraseasonal Oscillation (BSISO) in operational models declines rapidly beyond 10–15 days lead time. In this study, we have used the ECMWF ERA5 reanalysis data to identify factors that may enhance the predictability of the BSISO by extending the lead time, thereby ultimately improving the predictability of the Asian summer monsoon at subseasonal timescales.To understand the dynamics and propagation of the BSISO, we analyse its complex spatiotemporal evolution using phase composites and lag-correlation diagrams, capturing its distinct northward propagation over the northern Indian Ocean and western North Pacific, alongside eastward propagation along the equator. We have investigated how slowly varying, seasonally persisting components, such as the El Niño-Southern Oscillation (ENSO), modulate the background mean state through which the BSISO propagates by analyzing composite spatial plots of BSISO phases under El Niño and La Niña conditions.Observational analyses show that ENSO has a strong influence on the background mean state, which sets the environment through which transient features propagate. In particular, ENSO phases have a significant impact on the background easterly vertical shear, which plays a crucial role in generating Rossby waves and trapping moist equatorial waves within the monsoon region. In this study, we investigate how the prediction skill of the BSISO varies across different ENSO phases, specifically exploring whether El Niño or La Niña create conditions that may enhance or limit BSISO forecast skill. Understanding this intricate interaction between the background mean state and the BSISO underscores the importance of accurately representing these processes in order for good prediction skill to be realised in models for subseasonal-to-seasonal time scales.