Data and code for comparing the cooling of urban water bodies and green spaces across the aridity gradient of 229 Chinese cities

This record contains the data and the code of the main calculations of a study that compares the daytime and nighttime land surface temperature (LST) of urban water bodies, green spaces and built-up land in 229 Chinese cities on a 1 km grid (June–August, 2018–2023). Contents: data/cells_1km.csv.gz: 746,554 cells of 1 km with LST by day and night, water occurrence, vegetation and built-up shares, elevation, background air and dewpoint temperature, NDVI, evapotranspiration and residents; data/cities.csv: the 229 cities with their aridity index and zone and summer climate; data/results/: city-level and station-level results underlying the figures and tables of the paper; code/: Python code of the main calculations (cooling intensity, the adjusted advantage of Eq. 1, the cover effects of Eq. 2 and the water demand), with a README that lists the variables, sources and steps. Source datasets: Global Urban Boundaries, MODIS Aqua LST (MYD11A2, MYD11A1), ESA WorldCover v200, JRC Global Surface Water, SRTM, ERA5-Land, TerraClimate, MODIS NDVI (MOD13A2), ET (MOD16A2GF) and albedo (MCD43A3), PML-V2.2a, Landsat 8 and 9 Collection 2, WorldPop 2020, gridded GDP per capita (Kummu et al., 2025) and the Integrated Surface Database. Only derived values are included; the source data are available from their providers. Contains modified Copernicus Climate Change Service information 2026.