City-level cooling energy demand projections and derived datasets for China (2000–2100)

This dataset accompanies the manuscript "Climate-driven zoning transitions reshape urban resilience: How warming triples China's cooling energy burdens and deepens spatial inequality". The dataset includes city-level derived data and analysis scripts supporting the projection of cooling energy demand across Chinese cities from 2000 to 2100 under SSP2-4.5 and SSP5-8.5 scenarios. Input climate variables (near-surface air temperature and relative humidity) were obtained from ERA5 reanalysis and CMIP6 multi-model ensemble outputs. A dynamic zoning regression model based on wet-bulb cooling degree days (WCDD) was applied to project future cooling energy demand at the prefecture-city level. Contents: City-level historical WCDD time series (2000–2020) Future energy consumption projections by city (2021–2100) Gini coefficient results with provincial identifiers Analysis scripts for reproducing all main results ERA5 data are available from the Copernicus Climate Data Store (https://cds.climate.copernicus.eu). CMIP6 outputs are available through the Earth System Grid Federation (https://esgf-node.llnl.gov).