Extreme hydrological events such as floods, droughts, and heatwaves have been changing considerably under a changing climate. Concurrent and compound events, where extremes occur simultaneously or in succession, have been exacerbating risks to infrastructure, society, economy, and ecosystems. Understanding the evolution of extremes and their concurrent/compound occurrences across spatial and temporal scales, climate drivers influencing these events, and the uncertainty in their characterization remains a critical challenge. Consequently, there is an urgent need for advancements in modeling, monitoring, prediction, and risk assessment to reinforce resilience against extremes and their concurrent/compound occurrences at global, regional, and urban scales. In this session, we welcome research contributions encompassing, but not limited to, the following areas: (1) analysis of changes in the severity, duration, intensity, frequency, and spatial extent of extremes including concurrent/compound events under changing climate conditions; (2) exploration of latest methodologies for characterizing and predicting extreme events, including the application of machine learning techniques; (3) understanding the climate drivers impacting extreme events and their spatial/temporal evolution; (4) characterizing risk, vulnerability, exposure, and adaptive capacity; and (5) quantifying uncertainties in extreme events.