Climate change is altering the characteristics of extreme events globally, affecting their frequency, intensity, duration, timing, spatial extent, and persistence. Extreme precipitation, heatwaves, droughts and flash droughts, floods, tropical cyclones, and compound events can generate cascading impacts on water resources, agriculture, ecosystems, human health, and infrastructure. Understanding where and how extremes are changing, the physical mechanisms driving these changes, and their links to anthropogenic climate change is essential for assessing evolving climate risks.
This session invites research on the evolution of climate extremes across past, present, and future climates using observations, palaeo-climate records, reanalyses, climate models, and statistical approaches. We particularly welcome studies examining the physical drivers of extremes, including atmospheric circulation, moisture transport, land-atmosphere interactions, ocean-atmosphere coupling, and large-scale climate variability. Studies of compound, concurrent, sequential, and rapidly transitioning extremes, including hydroclimatic whiplash, are especially encouraged.
Contributions addressing future changes in extreme-event intensity, frequency, seasonality, spatial distribution, and dependence between hazards are welcome, alongside studies of model uncertainty, internal variability, scenario uncertainty, and detection and attribution. We particularly encourage emerging AI/ML and data-driven approaches for extreme event detection, prediction, attribution, downscaling, and process understanding, including hybrid physics-ML frameworks and explainable methods. Critical assessments of their uncertainty, physical interpretability, and transferability are also encouraged.
By connecting observed changes, physical processes, and future projections, this session aims to advance understanding of evolving climate extremes and the uncertainties and emerging risks associated with them.