| 摘 要： |
Apparent temperature (AT) is used to evaluate human comfort and is of great importance for studies on the effects of environmental factors on human health. This study used the daytime heat index (HI) calculated by national surface meteorological stations in China as the AT dependent variable, with August 2020 employed as an example. The daytime fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate (ERA5) data and multi-source data extracted from the stations were used as the independent variables. Due to the presence of multicollinearity among the independent variables, we implemented a multiple stepwise regression model and developed a daily near-surface 1 km HI estimation model. The correlation analysis using the model showed that the coefficient of determination (R-2) was 0.89; the mean absolute error (MAE) was 1.49 degrees C, and the root mean square error (RMSE) was 2.08 degrees C. We also used 10-fold cross-validation to calculate the error between the parameter and predicted values. The R-2 of the model was 0.96; the MAE was 1.80 degrees C, and the RMSE was 2.40 degrees C. In this month, the mean daily daytime HI was 20.51 degrees C. According to the Universal Thermal Climate Index (UTCI), the areas with more than 20 days of heat stress for one month were largely distributed in the desert areas of northwest China and the coastal areas in southeast China, accounting for 29.98% of the total land area of China. This study improves the spatial resolution and accuracy of HI prediction, thus providing a scientific reference for studying residential environments and the urban heat island effect. |
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