Supporting data for “Daily air temperature estimates at 30-meter resolution in the Chongqing Metropolitan Area, China, 2016–2024”

This dataset provides high-resolution gridded daily air temperature data (Tmax and Tmin) at 30 m spatial resolution for the Metropolitan Circle of Chongqing, China, covering the period from 2016 to 2024. The dataset was developed using a Spatially Varying Coefficient Model with Sign Preservation (SVCM-SP), which incorporates multi-year averaged Landsat-derived land surface temperature (LST) and a digital elevation model (DEM) as predictors. Sign constraints were applied to ensure the physical consistency of the relationships between variables. Compared with the widely used Geographically Weighted Regression (GWR) model, the SVCM-SP method achieves higher interpolation accuracy, as reflected by improved R² and reduced RMSE/MAE values across both daily and monthly scales. The resulting dataset is well-suited for urban climate studies, heatwave risk assessment, and climate adaptation planning in topographically complex and rapidly urbanizing regions.The dataset includes a 30 m resolution DEM, monthly Landsat-derived LST, and daily maximum and minimum air temperature data from 2016 to 2024. All temperature products are provided in GeoTIFF format, referenced to the WGS 84 coordinate system, with a spatial resolution of 30 meters and a measurement unit of degrees Celsius (°C).