Emerging climate risks pose pressing challenges for insurers, governments, and businesses worldwide, as they face growing uncertainty in quantifying the impacts of climate change from physical risks. This paper aims to understand the impact of specific climate factors on mortality by cause for subgroups of the United States (US) population, through sensitivity and scenario analysis based on an increase in temperature and sea level extremes. We apply compositional data analysis (CODA) techniques to examine cause-specific deaths, treating the density of deaths as a set of dependent, non-negative values that sum to one. We couple CODA with principal component analysis on the climate factors as a means of dimension reduction, and fit generalised additive models to better reflect the non-linear relationships between the dimension-reduced principal scores and mortality by cause. The results of our analysis indicate climate-related factors have varying impacts by cause and ages within each cause, with more pronounced increases in the proportions of deaths from hypertensive heart disease as temperature and sea level extremes increase. Scenario analysis also indicates that an increase in temperature high extremes, sea level, and rainfall, in conjunction with a decrease in low temperature extremes, lead to offsetting impacts on the proportion of deaths between climate-related causes, but less offsetting by age within causes. Furthermore, the impacts on the proportions of death are more pronounced for ages between 55 and 95, reinforcing the observation that climate-related risks have a greater impact on older (and potentially more vulnerable) subgroups of the population. For life insurers specifically, these results are consistent with the natural hedge that arises between annuity and protection products, in light of increasing climate risk.

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