b. Land use change projection and refinement of urban geometric parameters
The default WRF assigns surface roughness length and background albedo values based on a single value for each land use category, which does not accurately reflect the complex urban geography of the PRD. This leads to degraded model simulations. To address this issue, we reassigned roughness length and albedo values for the 2010s using a combination of Baidu Maps, Hong Kong Planning department data, and the World Urban Database and Portal Tool (WUDAPT) level 0 method, which employs the Local Climate Zone (LCZ) classification system. The LCZ system includes 17 classifications, comprising 10 build-up types and 7 natural types (Bechtel et al. 2015; Stewart and Oke 2012). Then the LCZ categories with new set of roughness length and albedo were converted to fit the land use classifications of United State Geological Survey (USGS) land use system available in WRF (Fig. 1 (b), Fig. S1 (a), and (c)). Several studies have shown that this approach improves simulations of 2 m temperature and 10m wind speed (Liu 2020; Yeung et al. 2020). For the future land use projection, we only used the WUDAPT dataset provided by Chen’s group, which conducted LCZ simulations for 2050 using the Global Change Analysis Model (GCAM) and Future Land Use Simulation Model (FLUS) (Chen et al. 2021). The accuracy of this LCZ classification and simulation are assessed in their paper which confirms the reliability of the dataset. Thereafter similar steps of calculating roughness length and albedo were taken and the LCZ classifications were converted to fit WRF USGS land use category (Fig. 1 (c), Fig. S1 (b), and (d)). The land use parameters in the 2090s is assumed to be the same as the 2040s. These refinements improve the accuracy of the WRF model and enhance our ability to project land use change in the PRD.