## 5 Results and Discussion
### Validation  
We selected three sea breeze cases for the validation: 17 April 2018, 11 April 2020, and 15 April 2021. The verification duration is 11 h at 1 h intervals from the onset time of the sea breeze to the onset time of the land breeze, which is the same as the optimization  
Figure 4: Evolution of the fitness function in terms of the generations during the optimization process. \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Domain 1** & **Domain 2** & **Domain 3** \\ \hline Horizontal resolution & 9 km \(\times\) 9 km & 3 km \(\times\) 3 km & 1 km \(\times\) 1 km \\ Vertical layers & & 45 eta levels & \\ Cumulus physics & \multirow{2}{*}{Kain-Fritsch} & \multirow{2}{*}{Kain-Fritsch} & \multirow{2}{*}{-} \\ Microphysics & & WDM 5 & WDM 5 \\ Initial and Boundary & \multirow{2}{*}{NCEP FNL Global Analysis Data (0.25\({}^{\circ}\)\(\times\) 0.25\({}^{\circ}\))} \\ conditions & & & \\ Initial time & 2018/04/15 1800 UTC & 2019/04/11 1800 UTC & 2019/05/02 1800 UTC \\ Forecast time & & 18 h (6 h spin-up) & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Overview of the WRF model configuration. period. The surface meteorological variables, including \(T_{2m}\), \(RH_{2m}\), \(WS_{10m}\), and \(WD_{10m}\), and vertical wind profile variables, are compared between the model outputs and the observational data for the validation. We compared the optimal combination of the physical parameterization schemes with the combination of physical parameterization schemes mainly used in numerical simulations of the general sea breeze research [18; 58; 62; 63]. Table 4 summarizes the combinations of the physical parameterization schemes including optimal combination scheme for the comparison experiments. We used Equations (1)-(3) to evaluate the prediction performance in terms of all variables, surface meteorological variables, and winds at vertical levels, respectively, for different combinations of physical parameterization schemes (see Figure 5). The best performances were obtained by OPTM in terms of all variables (Figure 5a) and surface variables (Figure 5b), followed by EXP1. For the vertical wind profile variables (Figure 5c), the combination of physical parameterization schemes with the best performance differed for each sea breeze case: EXP1 on 11 April 2020 and EXP2 on 15 April 2021, respectively, outperformed OPTM. Overall, OPTM produced the best performance for the sea breeze circulations. Compared to EXP4, the largest improvement rates by OPTM, with regard to NRMSE, were as follows: 29 % for all variables on 11 April 2020 (see Figure 5a); 38 % for the surface meteorological variables on 15 April 2021 (see Figure 5b); and 24 % for the vertical wind profile variables on 11 April 2020 (see Figure 5c). Both OPTM and EXP1 showed good performances, possibly due to the influence of Noah-MP that is shown to simulate well the PBL height and heat flux associated with formation of a shallow unstable boundary layer near the coast during the sea breeze time [17]. Table 5 summarizes the statistical results of the model performances in surface meteorological variables and wind variables at vertical levels. The results of \(RMSE\) and Bias are as follows: the OPTM showed the best results in all sea breeze cases for \(T_{2m}\) and indicated good performance of \(WD_{10m}\) and \(WD\). In \(T_{2m}\), all experiments showed underestimation with a cold bias, and OPTM showed the best performance. In \(RH_{2m}\), OPTM, EXP2, and EXP3 performed well in each case. In \(WS_{10m}\), EXP1 simulated the closest to observation while the performance of OPTM is moderate. \(WS_{10m}\) was overestimated, which was consistent with various studies using WRF [33; 61].