Climate extremes are increasingly interacting rather than occurring in isolation. Floods, droughts, heatwaves, and wildfires can overlap or trigger one another, forming compound and cascading events that amplify impacts across environmental and socio-economic systems. Climate change is intensifying these interactions by altering their frequency, timing, and co-occurrence, while growing non-stationarity further challenges prediction and risk assessment.

This session invites contributions that:

(1) investigate drivers and feedbacks of interacting hazards;

(2) analyze event dynamics using process-based and data-driven approaches;

(3) apply advanced methods such as causal inference and machine learning;

(4) leverage Earth observations for detection and attribution;

(5) develop early warning systems for joint hazard-impact prediction; and

(6) assess impacts, risk and resilience across critical systems.

The session aims to advance integrated understanding and predictive tools for managing risks from colliding climate extremes.

• A - Atmospheric Sciences
• GC - Global Environmental Change
• H - Hydrology