This study uses insurance loss data to examine how different types of extreme weather—such as floods, heavy rain, windstorms, and hail—occur together. It finds that multiple hazards often cluster seasonally, leading to higher losses than when events happen alone. The results highlight the need to assess multiple weather extremes jointly to better understand and manage risk.
This study uses insurance loss data to examine how different types of extreme weather—such as...
Using loss data, we assess when and how single and multiple types of meteorological extremes (river floods and heavy rainfall events, windstorms and convective gusts, and hail) are related. We find that the combination of several types of hazards clusters robustly on a seasonal scale, whereas only some single hazard types occur in clusters. This can be associated with higher losses compared to isolated events. We argue for the relevance of jointly considering multiple types of hazards.
Using loss data, we assess when and how single and multiple types of meteorological extremes...