Catastrophe risk models as quantitative tools for climate change loss and damage

Addressing climate change loss and damage is a crucial ambition within international climate policy. Given the disproportionate impact of climate change on vulnerable communities, there is a need to develop quantitative tools to support just and equitable decisions surrounding financing and redress for loss and damage. However, the complexity of climate change impacts and the challenging academic and political discourse surrounding loss and damage mean a standardised quantitative framework has not been established.

Here we discuss how catastrophe risk models can be used as flexible quantitative tools to help address this critical gap in climate policy. We explore their potential to quantify both economic and non-economic losses, and their ability to adapt to integrate key features such as social vulnerability, thus responding to the complex loss and damage space. We illustrate this by exploring the change in inland flood risk under climate change for three Global South case study regions: Chikwawa in Malawi, Hanoi in Vietnam, and Cagayan in the Philippines. We estimate the risk to three exposure types with both economic and non-economic implications: residential buildings, agricultural crops, and population. Overall, our results show that catastrophe models can produce meaningful, context-specific insights into climate change loss and damage that can guide decisions surrounding adaptation and financing, while highlighting substantial scope for further development across exposure types, risk metrics, and climate change scenarios.

We also highlight some of the key questions revealed during this research and propose directions for future applications of catastrophe models in the loss and damage space, whilst acknowledging important limitations and climate model uncertainties that should be integrated in future work. Finally, we argue that collaboration across sectors – including academia, industry, and local communities – is fundamental to using catastrophe models to contribute appropriately and justly to addressing loss and damage.