Modelling Daily Mean Surface Air Temperature Calculated from Different Methods and Its Impact on Urban-Related Warming Evaluations over Guangzhou and Shenzhen Using the WRF Model

The impacts of urban surface expansion, based on satellite-derived data displaying urban surface expansion in China at different spatial scales from 1980 to 2016, were investigated using nested dynamical downscaling methods with the Weather Research and Forecasting (WRF) regional climate model at a 3.3-km resolution over a city and city cluster scale. Urban-related warming, based on daily mean surface air temperature at 2 m (SAT), calculated from the averages of four time records each day (00, 06, 12, and 18 h UTC, T₄) and averages of SAT maximum (T_max) and minimum (T_min) (T_xn), was evaluated. Differences in urban-related warming contributions calculated using T₄ and T_xn were small, whereas annual mean SAT and trends calculated using T_xn were respectively and significantly larger and smaller than those calculated using T₄ over Guangzhou and Shenzhen, excluding the trends over middle-northern Shenzhen. The differences in annual mean SAT calculated using T₄ and T_xn are attributed to nonlinear or asymmetric variations with time for the diurnal cycle of SAT. Meanwhile, differences in trends between T₄ and T_xn are interpreted as a strong trend for T_min and a weak one for T_max, which mitigated the trend for T_xn. The impacts on the evaluations of urban-related warming contributions calculated from different methods were the largest over the areas classified as urban surfaces in both time periods (U2U), especially during intense urban-surface-expansion periods between 2000 and 2016. The subregional performances in the changes in annual mean SAT, trends, and urban-related warming are attributed to urban-surface-expansion, which induced varied changes in the diurnal cycle due to asymmetric warming during the daytime and nighttime over different subregions. View Full-Text