Remote sensing-driven analysis of hourly urban heat storage and its effects on urban heat islands in Chinaemote 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. 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 using hourly LST of Himawari-8. Secondly, the hourly Qs in three urban agglomerations in China was simulated by the heat diffusion equation and Fourier’s law for heat conduction, using the simulated urban thermal inertia and Himawari-8 LST. Thirdly, the relationship between Qs and air temperature (Ta) was studied. 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, Qs were validated by the observed Qs (from flux tower observation) in Beijing, Shanghai and Guangzhou, R² could be up to 0.92. Results showed that, Qs was more consistent with Ta at nighttime than daytime, with R² of 0.96 and 0.1, respectively. 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 (scatterplot of hourly Qs and Ta) shape were different at LCZs. 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 night 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.