Description:

Tropical convective variability on the subseasonal to seasonal (S2S) timescale, especially the Madden-Julian Oscillation (MJO), Boreal Summer Intraseasonal Oscillation (BSISO), and the global monsoon system provide an important source of predictability for the extreme weather events around the globe. These tropical modes of variability modulate the background large-scale atmospheric circulation and thermodynamic state, which can lead to a conducive environment for the generation of extreme events through multiscale interactions and the associated feedbacks. However, most dynamical models fail to capture these complex interactions at subseasonal timescales, leading to inaccurate predictions of extreme events. This session explores the influence of MJO, BSISO, and the global monsoon system on the occurrence and severity of extreme weather events in the S2S timescale, including but not limited to heavy rainfall, floods, droughts, heat waves, and cold extremes. Additionally, the session solicits abstracts on the connections between the S2S variabilities and the extreme events utilizing various approaches, such as observations, numerical modeling, forecast verification, and machine learning techniques. In particular, we welcome studies exploring key mechanisms and processes that are involved in the complex interplay between subseasonal modes and their subsequent influence on extreme events. This session aims to foster discussion and enhance understanding of the subseasonal extremes by exploring empirical evidence, theoretical frameworks, and machine-learning approaches, ultimately facilitating more accurate prediction and mitigation strategies for these high-impact events.