Remote sensing-driven analysis of hourly urban heat storage and its effects on urban heat islands in China

Urban heat storage (Qs) is an essential component of urban surface energy balance. Urban with 3D structure has larger surface area than rural and urban would absorb and release more energy than rural. Qs is the main factor for urban heat island (UHI) at nighttime. The quantitative contribution of Qs to UHI is still unclear, due to the lack of a spatio-temporal continuous Qs dataset. In this study, firstly, we developed an urban surface thermal inertia model considering diurnal variation of surface temperature (LST) using hourly LST of Himawari-8. Secondly, the hourly Qs at 2-km resolution in three urban agglomerations in China was simulated by a half-order time derivative method which derived from combining the one-dimensional heat diffusion equation and Fourier’s law for heat conduction, using the urban thermal inertia model and hourly Himawari-8 LST. Thirdly, the relationship between Qs and air temperature (Ta) was studied at different time scales (day and nighttime, four seasons) and different LCZs (local climate zones). The Ta was derived from the interpolation of dense automatic weather stations with more than 10000 sites in China. Finally, some urban heat mitigation measures were provided based on the above analysis. Based on the in-situ observation, the accuracy of urban thermal inertial in this study was higher than other model, RMSE, MAE, R² were improved from 4.65 K, 3.58 K and 0.88 to 1.86 K, 1.53 K and 0.97. In addition, the simulated Qs were validated by the observed Qs (the minus of net radiation, sensible and latent heat flux from in-situ flux tower, and anthropogenic heat flux simulation) in Beijing, Shanghai and Guangzhou, R² could be up to 0.92. The results showed that, Qs was more consistent with Ta at nighttime than daytime, with R² of 0.96 and 0.1, respectively. That showed that Qs is the main factor for nighttime UHI in this study area. During nighttime, the high-rise building has higher Ta than low-rise building, due to higher Qs and release more energy than low-rise. In natural surfaces, water has larger Qs and higher Ta than dense trees. The loop (between hourly Qs and hourly Ta) shape were different at different LCZs, with different loop area and loop slope. Based on the loop area and slope, we found that high-rise building had higher UHI but varied quickly, however, low-rise UHI is lower but would last longer. The water surface in nighttime is also heat source and has a longer time UHI. Therefore, the high-rise building and water surface are not conductive to alleviating the nighttime UHI.