## 3 Performance Evaluation of WRF
### Ideal Experiment: WRF-LES  
The Large Eddy Simulation (LES) using WRF was constructed for analyzing ideal turbulence. LES was first developed by [PERSON] (1963) [9] and has been continuously studied by [PERSON] (1974) [10]. LES is an important tool for studying turbulence in the atmosphere and explicitly calculates the large turbulence vortex that carries most of the turbulent kinetic energy and flux. Thus, LES provides more accurate estimates of turbulence statistics than Planetary Boundary Layer (PBL) parameterization methods ([PERSON] et al., 2010) [11]. WRF-ARW is a non-hydrostatic model that is suitable for simulating micro and medium scale meteorological phenomena. WRF model provides a LES scheme that directly calculates turbulence near the surface for numerical simulations of high-resolution grids. The WRF-LES experiment simulated large eddies in the free Convective Boundary Layer (CBL). The initial wind field was set to zero and the turbulence of the CBL was calculated by the heat flux of the surface, which was specified as tke_heat_flux = 0.24. Random perturbation was applied to the average temperature in the lowest four layers of the vertical grid for turbulent motion. The LES grid had a \(3200\times 3200\) resolution divided by \(\mathrm{dx}=\mathrm{dy}=1.25\) m in the 4 km square domain, which is a considerably higher resolution than the general grid resolution of LES (\(\mathrm{dx}=\mathrm{dy}=50\) m). This ideal case uses [PERSON]'s TKE system, which is set to the eddy viscosity (diff_opt = 2), eddy diffusion coefficient (km_opt = 2) for the turbulent mixing and Coriolis parameter (f = 10\({}^{-4}\)/s). Figure 1 shows the wind speed field at 10 m above the surface in the LES simulation. Figure 1a is the result of the ultra-high resolution model used in this study, and (b) is the result of the low-resolution model of the basic configuration (\(40\times 40\) resolution, \(\mathrm{dx}=\mathrm{dy}=100\) m) officially provided by the WRF development team. Compared with (b), (a) reproduces large eddies in more detail, and a scientific analysis is presented in [PERSON] et al., (2007) [12]. The benchmark experiment for the ideal case is suitable for comparing the performance rates of computational resources because of the smaller I/O loads for data. We used 128, 256, and 512 cores to compare the performance of parallel systems according to the experiment (ref. Table 3). In addition, a 1024 ultra-high resolution-experiment was performed on the KNL system for testing performance limits. This is difficult to simulate in general systems (SKL and CLS) due to their insufficient resources. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Experiment** & **KNL** & **CLS** & **SKL** \\ \hline
128 cores & \(16n\times 8c\) (W-ir), \(8n\times 16c\) (W-ir) & \(4n\times 32c\) & \(4n\times 32c\) \\  & \(4n\times 32c\) (R\&F-r), \(2n\times 64c\) (W-ir, R\&F-i) & (W\&R\&F-ir) \\ \hline
256 cores & \(32n\times 8c\) (W-ir), \(16n\times 16c\) (W-ir) & \(8n\times 32c\) & \(8n\times 32c\) \\  & \(8n\times 32c\) (R\&F-r), \(4n\times 64c\) (W-ir, R\&F-i) & (W\&F-ir) \\ \hline
512 cores & \(64n\times 8c\) (W-ir), \(32n\times 16c\) (W-ir) & \(16n\times 32c\) & \(16n\times 32c\) \\  & \(16n\times 32c\) (R\&F-r), \(8n\times 64c\) (W-ir, R\&F-i) & (W\&F-ir) \\ \hline
1024 cores & \(128n\times 8c\) (W-ir), \(64n\times 16c\) (W-ir) & - & - \\  & \(32n\times 32c\) (R\&F-r), \(16n\times 64c\) (W-ir, R\&F-i) & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Experimental configuration by system (KNL, SKL and CLS) (n: node, c: core, W: Weather Research and Forecasting System (WRF), R: Regional Ocean Modeling System (ROMS), F: Unstructured Grid Finite Volume Community Ocean Model (FVCOM), i: ideal experiment, r: real experiment). The results of each experiment are summarized in Figure 2. The performance rate of the KNL system was approximately 54%, compared to the SKL or CLS systems. The performance rate is defined as the sum of the simulation time of SKL and CLS divided by twice the simulation time of KNL.