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.