## 3 NWP Plus CFD Coupling  
The Regional Atmospheric Modelling System (RAMS) version 6.3 ([[https://vandenheever.atmos.colostate.edu/vdhpage/rams.php](https://vandenheever.atmos.colostate.edu/vdhpage/rams.php)]([https://vandenheever.atmos.colostate.edu/vdhpage/rams.php](https://vandenheever.atmos.colostate.edu/vdhpage/rams.php)) (accessed on 26 August 2024)) is used as the mesoscale NWP model. The RAMS is nested within the global model of the National Centers for Environmental Prediction (NCEP), i.e., forecast and analysis data from the global model of the NCEP were used to determine the initial and boundary conditions of the RAMS. Five nested grids are used, and the spatial resolutions are 25 km, 5 km, 1 km, 200 m, and 40 m, respectively. All grids are centered at anemometer CB5 on the bridge. The five grids are shown in Figure 5a,b. The outermost grid has a time step of 10 s, and time step ratios of 10 are applied for successive domains. For turbulence parameterization, the Smagorinsky scheme is applied for the two outermost grids and the Deardorff scheme is applied for the remaining three grids [19]. The Leaf-3 land surface model is used [20; 21]. The RAMS is suitable for microscale simulation and has been used for the LES of the atmospheric boundary layer in idealized and realistic conditions [22; 23; 24; 25]. No building or bridge was included in the RAMS simulation in the current study.  
Figure 5: \(Cont.\)Figure 5: (**a**) The 1 st, 2 nd, and 3 rd nested domains of the RAMS simulation. (**b**) The 3 rd, 4 th, and 5 th nested domains of the RAMS simulation. (**c**) The domain of the PALM simulation is denoted by a red rectangle, where the boundary is the 5 th nested domain of the RAMS simulation.  
The PALM is nested inside the innermost RAMS domain, which was formerly an abbreviation for the parallelized large-eddy simulation model and has now become an independent name [26]. The PALM is a parallelized large-eddy simulation (LES) CFD model that solves non-hydrostatic, filtered, incompressible Navier-Stokes equations in Boussinesq-approximated form with subgrid-scale covariance terms parametrized with a 1.5-order closure scheme [19]. The details of the PALM can be found in [26; 27; 28]. Figure 5c shows the innermost domain of the RAMS and the domain of the CFD model. The offline coupling between the RAMS and PALM is performed with a dynamic input file. The PALM provides Python scripts that can be used to extract and interpolate data from the WRF to generate a dynamic input file containing the initial and boundary conditions for the PALM of different meteorological variables, such as the wind, potential temperature, and mixing ratio. Custom modification was applied to the Python scripts such that they could generate the required dynamic input file using the RAMS simulation data.  
The current PALM simulation setup has a spatial resolution down to 4 m with the application of vertical stretching and a stretching ratio of 1.08. The maximum vertical grid size is limited to 12 m. Synthetic turbulence generation is also applied [29; 30]. The study employs a fifth-order upwind difference scheme [31] for momentum advection and a third-order Runge-Kutta scheme [32] for time stepping. Adaptive time steps are used, and the average time steps are about 0.05 s and 0.1 s for the cases of Saola and Koinu. The 3D spatial data of the bridge under study were provided by the Lands Department of the Government of the Hong Kong Special Administrative Region. The high resolution of the PALM allows the explicit representation of the bridge and the buildings in its upstream region. With a higher resolution, it is expected that the turbulent flow around the bridge can be better resolved and hence the wind speed can be more accurately simulated.