Critical infrastructures (CIs) such as power lines, roads, telecommunication and healthcare systems across the globe are more exposed than ever to the risks of extreme weather events in a changing climate. Damages to CIs often lead to failure cascades with catastrophic impacts in terms of people being cut off from basic service access. Yet, there is a gap between traditional CI failure models, operating often at local scales, with detailed proprietary, non-transferrable data, and the large scales and global occurrences of natural disasters, calling for the integration of perspectives from several fields to approach the complexities of such interconnected systems (Zio, 2016). We demonstrate a way to bridge those incompatibilities by linking a globally consistent and spatially explicit natural hazard risk modelling platform (CLIMADA (Aznar-Siguan and Bresch, 2019)) to a CI failure cascade model. The latter makes use of complex network theory, which has previously been demonstrated as a useful approach to capture many interconnected CIs across large regions (Thacker et al., 2017) and is built to work with publicly available infrastructure data and dependency heuristics between CIs to represent a system-of-systems at national scales. The integrated modelling chain (Mühlhofer et al., in review) computes natural hazard-induced infrastructure component damages, produces consequent CI failure cascades and translates those technical failures into population clusters experiencing disruptions to basic service access.

In this contribution, we showcase how a comparable and systemic risk view on cascading CI failures from natural hazards can be obtained across different regions. To this end, we run simulations of a probabilistic tropical cyclone hazard for 2-3 tropical cyclone exposed countries and evaluate their impacts on a technical and social dimension.