Extreme hydrometeorological events, such as floods and droughts, are changing significantly under a warming climate and are amplifying risks to infrastructure, ecosystems, economies, and society. These extremes, including their compound occurrences, are driven by complex climate–land–atmosphere processes, making their characterization, prediction, and risk assessment challenging. Addressing these challenges requires advances in monitoring, modeling, detection, attribution, and uncertainty quantification to strengthen resilience at global, regional, and local scales. This session focuses on investigating changes in the frequency, intensity, duration, severity, spatial extent, and clustering of extreme events,like floods and droughts, under climate variability and change. We welcome studies on understanding the role of climate drivers, land–atmosphere feedbacks, land-use/land-cover change, and evapotranspiration dynamics in shaping the evolution and propagation of floods and droughts.. Submissions employing innovative datasets, high-resolution observations, advanced indices, machine learning approaches, and integrated modeling frameworks to improve detection, attribution, prediction, and early warning of extreme and compound events are welcome. Studies linking extremes to risk, vulnerability, exposure, adaptive capacity, and decision-making across water, agricultural, ecological, and socio-economic systems are also welcome.