Population and economic exposure and their driving factors under different precipitation severities and scenarios

Using precipitation data from 12 global climate models in the NEX-GDDP-CMIP6 and population and GDP data developed by IIASA, we calculated global population and GDP exposure to mild, moderate, and severe extreme precipitation in the near term (2031–2060) and far term (2071–2100) under three scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. Furthermore, we analyzed the contribution rates of changes in climate and risk receptors (i.e., population or GDP) to the variation in exposure. The dataset includes the annual frequency of extreme precipitation, annual average population and GDP, and population and GDP exposure to extreme precipitation across different regions of the world in the near term and far term, as well as their change rates between the two periods. It also provides the contribution rates of climate and risk receptor changes to the variation in exposure. The spatial resolution of the dataset is 0.25° × 0.25°. This dataset was processed and generated using MATLAB. Units: Extreme precipitation frequency: times/year GDP: billion USD (in 2005 PPP USD) Population: million GDP exposure: billion USD-times Population exposure: million person-times Change rate: % Contribution rate: %