Sea level rise may impose substantial economic costs to coastal communities worldwide, but characterizing its global impact remains challenging because SLR costs depend heavily on natural characteristics and human investments at each location – including topography, the spatial distribution of assets, and local adaptation decisions. To date, several impact models have been developed to estimate the global costs of SLR. Yet, the limited availability of open-source and modular platforms that easily ingest up-to-date socioeconomic and physical data sources restricts the ability of existing systems to incorporate new insights transparently. In this paper, we present a modular, open-source platform designed to address this need, providing end-to-end transparency from global input data to a scalable least-cost optimization framework that estimates adaptation and net SLR costs for nearly 10 000 global coastline segments and administrative regions.

This paper estimates that the release of an additional ton of carbon dioxide today will cause mean damages to global mortality risk valued at $36.6 under a high emissions scenario and $17.1 under a moderate scenario, using a 2% discount rate that is justified by US Treasury rates over the last two decades. It is a core input to the Climate Impact Lab's Data-driven Spatial Climate Impact Model (DSCIM).