Local-resolution risk assessment for tropical cyclones: toward global adaptation

Between 1998 and 2017, tropical cyclones (TCs) caused 233,000 deaths, affected approximately 726 million people globally, and led to an average of 9.3 million human displacements annually between 2017 and 2020 (Kam et al., 2024). Within countries impacted by TCs, economically disadvantaged populations are disproportionately affected (Jing et al., 2024). Adaptation to TCs is impregnated with uncertainty within a global context where coastal adaptation efforts are unbalance distributed (Magnan et al., 2023).

While adaptive capacity varies widely at subnational levels (Magnan et al., 2023), adaptive information is provided at the national level or, at best, at the second administration level (e.g., states). There is a lack of local adaptation information specifically related to TCs. As part of the TRANSCLIMA project (https://transclima.ihcantabria.com/), we developed global, local risk indicators at the fourth administration level, based on changes in TC characteristics, exposed population, and TC-related adaptive capacity.

This study identifies TC regions where changes in intensity and frequency are observed. Based on these changes, regions where minor or major TCs shift and assesses whether TCs may become an unprecedented hazard, leading to emergent risks. These hazard indicators resulted from analysing TC characteristics under two climatological periods: a baseline climate (1980-2017) and a future high-emission climate scenario, Shared Socioeconomic Pathway SSP8.5 (2015-2050). We used synthetic tracks datasets of four Global Climate Models (CMCC, CNRM, EC-Earth, and HadGEM3)  (Bloemendaal, et al., 2022). Population data were obtained from the fourth version of the gridded population of the world with a 1 km resolution of the Socioeconomic Data and Application Center for the base year 2000 and for the years 2040 and 2050 under the SSP5 scenario (Center For International Earth Science Information Network-CIESIN-Columbia University, 2017), calculated for each coastal locality (Odériz et al., 2024). We assessed the adaptive capacity of each TC region using an index that combines local adaptive capacity, such as indicator local experience based on IBTrACS data (Knapp, 2018; K. R. Knapp et al., 2010). Additionally, we proposed a national-level insurance coverage indicator and a national-level adaptation readiness indicator.

Using this global, local-resolution risk assessment, we provided a detailed overview of the adaptation status of countries, considering subnational levels, that can be used to identify hotspots for financial adaptation plans.