Compounding hazards can lead to interconnected or aggravated impacts. In recent years, the analysis of compound events has become essential to understand and to improve our response to such high-impact multi-hazard disasters.

In the context of weather, climate or hydrology, compound events refer to combinations of multiple drivers or hazards which can lead to large impacts and disasters. The compounding events can be independent of each other (i.e., the outcome of one event has no effect on the probability of the other), or they can be dependent (i.e., the outcome of one event affects the probability of another). While compound weather, climate or hydrological events can be related to extreme conditions themselves (e.g. storms, heatwaves, floods and droughts), they can also result from combinations of events that are themselves not extreme but lead to an extreme event or significant impact when combined.

In this Short Course, we will introduce compound events, their types (preconditioned, multivariate, temporally compounding, and spatially compounding events), and the methods used to detect and characterize them. We will highlight the advantages and limitations of different methods to study compound events in large datasets, which can help to identify non-trivial spatio-temporal patterns of extreme events.

This Short Course will focus on sharing experience from a wide range of applications across different scales, state-of-the-art methodological approaches, open access code and datasets, and will allow participants to discuss their own challenges in detecting, characterizing and assessing the risk of compound events in diverse contexts (climate, atmospheric, hydrologic, ocean and natural hazards sciences).