Global quantification of subnational vulnerability drivers of human impacts from extreme weather events

Granular socioeconomic vulnerability drivers of impacts during extreme weather events remain poorly understood. Global climate vulnerability indices are usually only available at the national level, and the reporting of observed impacts is still unsystematic. By combining human impact data reported at subnational levels from the international disaster database EM-DAT and the Global Gridded Relative Deprivation Index, we ask ourselves whether the granularity of this data can be used to improve our understanding of disaster outcomes and in turn help to identify adaptation priorities. Here, we quantitatively show that higher multidimensional deprivation leads to larger human impacts per people exposed during floods, storms and droughts between 2010-2020. Due to gaps in EM-DAT reporting, these conclusions cannot be drawn for heatwaves, wildfires and landslides. Our global spatial analysis reveals that subnational areas more deprived than respective national means experience larger human impacts (for floods), while very local variability in deprivation (∼1 km spatial resolution) leads to lower impacts. The multidimensionality of the deprivation index allows to identify concrete socioeconomic factors that can be more effectively addressed, such as the levels of health or the specific age distribution of a population. While improvements are still needed to fully quantify the complex nature of climate vulnerability and rigorously track impacts from extreme weather events, understanding the main socioeconomic factors driving vulnerability at local levels allows to support policies, strategically plan adaptation and address losses and damages through tailored approaches.