Modelling urban meteorology with increasing refinements for the complex morphology of a typical Chinese city (Xi'an)

Urban areas are vulnerable to intensive heatwave periods. In order to understand heat stress in cities, the single-layer urban canopy model (SLUCM) coupled with the weather research and forecasting model (WRF) have been widely used to quantify and forecast the urban climate. However, the model performance in WRF/SLUCM is limited by the coarse classification of urban canopy parameters (UCPs), and further improvements may require great effort. Therefore, this study was a new attempt at organizing the gridded UCPs in the 'National Urban Database and Access Portal Tool (NUDAPT) approach' and exploring its application in the WRF/SLUCM model in four simulations with contrasting UCP configurations. The model performances were evaluated for a heatwave period in 2018 in the typical Chinese city of Xi'an, using a near-surface observational network consisting of 39 meteorological stations in various urban spatial categories. We found that the increased accuracy in UCPs brought about gradual and overall improvements in the urban heat island effect (UHI) and air temperature (Ta), and had relatively slight effects on absolute humidity (pv) and wind speed (WP). Furthermore, the station-tostation bias analyses indicated that optimization efficiency varied among urban spatial categories. Areas with an open form or areas densely covered with vegetation showed constant sensitivity to the increasing refinements of UCPs. Input of the gridded and multi-dimensional descriptions of urban canyon geometry contributed to more accurate results in dense urban areas and areas with mixed and inhomogeneous morphology.