As weather and climate extremes intensify in frequency and magnitude, there is a pressing need to draw on observational records, empirical methods, and cross-disciplinary research to better characterize their interconnected risks. This session aims to understand what observational and empirical analyses can tell us about the mechanisms and co-occurrence of high-impact extreme events—such as prolonged dry or wet periods, heavy winds, fire activity, and intense heat extremes—that frequently co-occur or unfold in rapid succession. We invite contributions that draw on station-based observations, satellite-derived products, reanalysis datasets, and statistical or machine-learning frameworks to examine real-world sequences of extreme events and their consequences for human communities, natural systems, and built infrastructure. The session focuses on observation-grounded, process-oriented insights into the physical triggers of extremes, their compound and cascading behavior, and the scale-dependent nature of their impacts—from local case studies to globally patterns.