## 3 Performance Evaluation of WRF
### Real Experiment: WRF-Nwp  
We aim to simulate the realistic case in order to evaluate the computational performance of each model depending on the number of supercomputer cores. The realistic case selected is a typhoon occurred in August 2018, where two typhoons (Soulik and Cimaron) simultaneously affected the Korean Peninsula severely. Experiments were configured with real topography and external forces for the Northwestern Pacific Ocean (NWP). A 2048 \(\times\) 2048 grid was constructed with an interval of approximately 1.35 minute in the region between 102\({}^{\circ}\) to 158\({}^{\circ}\) longitude and 15\({}^{\circ}\) to 53\({}^{\circ}\) latitude using the Lambert Conformal Conic projection, surrounding the Korean Peninsula (Figure 5). The vertical grid was divided into equal intervals of 33 layers up to 10 km height from surface. Global Forecast System (GFS, [[ftp://nomads.ncdc.noaa.gov/GFS/Grid4](ftp://nomads.ncdc.noaa.gov/GFS/Grid4)]([ftp://nomads.ncdc.noaa.gov/GFS/Grid4](ftp://nomads.ncdc.noaa.gov/GFS/Grid4))) data was used for the initial fields and external forces. The experiment was simulated for 3 h from 0:00 to 3:00 a.m. on 28 August 2018. This is the period when the twin typhoons of Soulik and Cimaron severely damaged the Korean Peninsula and represents an appropriate integration time for performance analysis. The external forces data from GFS were interpolated to fit the ultra-high resolution model grid. The time interval of the model integration was 5 s. Comparisons of accuracy with scientific results would not be useful since this experiment was simulated over a short period for performance analysis. Therefore, the computational performance was evaluated without analyzing the accuracy of the simulation results. In addition, a detailed description of how to simulate ultra-high resolution models has been omitted from this study as it falls beyond the scope of this study. Figure 6 shows the surface pressure field on the ocean from the results of the simulation in the KNL system. The surface pressure distribution is well simulated for the period when typhoon Soulik passed near South Korea. Figure 5: The simulation area of WRF-Northwestern Pacific Ocean (NWP); 2048 \(\times\) 2048 resolution, \(\mathrm{dt}=5\,\mathrm{s}\). NWP experiments were performed with a grid configuration of \(2048\times 2048\times 33\) (refer to Table 3). This configuration is suitable for evaluating the overall performance of the system because it considers the impact of the I/O performance on the system's ability to read real topography and external forces. Instances of 128, 256, and 512 cores were used to compare the performances of the parallel systems according to the experiment. In addition, a 1024 ultra-high resolution experiment was performed on the KNL system to determine its performance limits. The results of each experiment are summarized in Figure 7. The KNL system exhibited an overall rate of 37% compared to the performances of SKL and CLS. This result is a little slower than the benchmark (LES) experiment due to the I/O access loads. Notably, the calculation amounts are different between cores because of the differing I/O loads. The CLS system shows a stable improvement in the performance depending on the number of cores used compared to the SKL system (see the performance slope of the green and blue lines in Figure 7). The CLS system can thus run a model exclusively and consists of a simple network of 16 nodes, whereas the SKL system consists of a complex network of 132 nodes with many users. Even the 1024 cores experiment shows a continuous increase in the parallel performance of the KNL system; thus, it is more suitable system for an ultra-high parallel numerical model. In the KNL system, the performance was also analyzed according to the number of cores. Figure 8 shows that It is more efficient to use half the number of cores per node in KNL when the total number of cores is less than 256. However, there was no significant difference when more than 256 cores were used.