The monthly high spatial resolution human thermal index collection (hiti monthly) includes near surface temperature (SAT) and 11 commonly used human perceived temperature indices: indoor apparent temperature (ATin), outdoor shaded apparent temperature (ATout), discomfort index (DI), effective temperature (ET), heat index (HI), humidity index (HMI), modified discomfort index (MDI), net effective temperature (Net), simplified wet bulb temperature (sWBGT), wet bulb temperature (WBT), and wind chill temperature (WCT). The dataset has a high spatial resolution of 1 km × 1 km, covering the Chinese Mainland from January 2003 to December 2020. The overall r-squared, root mean square error, and mean absolute error of the 12 thermal indicators in the HiTIC dataset are 0.996, 0.693, and 0.512 ° C, respectively. Stacked annually, each stack consists of 12 months of NetCDF format images. The unit of the dataset is 0.01 ℃ (° C). In order to save storage space, the data is stored in integer format (Int16) and needs to be divided by 100 to obtain data in ℃. The projection coordinate system of the dataset is Albers equal area cone projection.
Observation data of 2419 meteorological stations in Chinese Mainland.
Use the LightGBM learning algorithm to generate 12 commonly used thermal indices from multi-source data, including surface temperature, terrain, land cover, population density, and impervious surface ratio.
The data quality is good.
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CSTR:11738.11.NCDC.ZENODO.DB6675.2024
10.12072/ncdc.zenodo.db6675.2024