INVESTIGATING THE IMPACT OF URBAN AGGLOMERATION FORMATION ON HEAT WAVES THROUGH DEEP LEARNING BASED LAND COVER CLASSIFICATION DATA

This study investigates the impact of urbanization on climate in the Yangtze River Delta urban agglomeration from 1984 to 2022. Using high-resolution Landsat-derived land cover data and the Weather Research and Forecasting (WRF) model capable of considering distributed urban parameters and anthropogenic heating, we simulated climate with various landcover conditions for 1984, 2000, 2010, and 2022. Simulations of a June 2022 heatwave month were conducted while varying the urban extent according to the actual historical landcover. In the core areas, or areas that have been urban since 1984, the monthly near-surface air temperature (wind speeds) continually increased (decreased) with increasing urban cover. During the heatwave, urban cover change of 1984 to 2022 increased the core’s spatial average temperature by 0.52°C with windspeed decreasd by 0.13m/s. However, urban expansion areas farther away from the core tend to have lower air temperatures than the expansion areas closer to the core. The mechanism behind the heatwave-dependence on the urban agglomeration changes were explained using landscape metrics.