## 3 Results and Discussion
### Sensitivity Analysis
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{2}{c}{**July 2013**} & **10 m** & **40 m** & **80 m** & **Average of Three Levels** \\ \hline \multirow{4}{*}{Bias} & MYJ & 0.76 & 0.87 & 1.04 & 0.89 \\ \cline{2-6}  & MYNN & 0.26 & 0.87 & 0.99 & 0.7 \\ \cline{2-6}  & ACM2 & 0.68 & 0.5 & 0.62 & 0.6 \\ \cline{2-6}  & YSU & 0.32 & 1.01 & 1.21 & 0.84 \\ \cline{2-6}  & QNSE & 0.31 & 0.88 & 1.08 & 0.76 \\ \hline \multirow{4}{*}{RMSE} & MYJ & 3.32 & 3.88 & 4.03 & 3.74 \\ \cline{2-6}  & MYNN & 3.21 & 3.82 & 3.96 & 3.66 \\ \cline{2-6}  & ACM2 & 3.15 & 3.46 & 3.61 & 3.4 \\ \cline{2-6}  & YSU & 3.25 & 3.75 & 3.97 & 3.66 \\ \cline{2-6}  & QNSE & 3.47 & 4 & 4.2 & 3.89 \\ \hline \multirow{4}{*}{STDE} & MYJ & 3.12 & 3.65 & 3.75 & 3.51 \\ \cline{2-6}  & MYNN & 3.06 & 3.61 & 3.72 & 3.46 \\ \cline{1-1} \cline{2-6}  & ACM2 & 2.96 & 3.29 & 3.41 & 3.22 \\ \cline{1-1} \cline{2-6}  & YSU & 3.01 & 3.41 & 3.56 & 3.33 \\ \cline{1-1} \cline{2-6}  & QNSE & 3.24 & 3.8 & 3.92 & 3.65 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Statistical parameters calculated from the comparison between the model outputs and wind observations at mast stations for different PBL schemes in July 2013. To further analyze this issue, the mean bias error of the wind speed simulation at SATBA stations and the difference between the actual stations' elevation and the elevation used in the model simulation grid are shown in Table 6. A link seems to be established between the elevation difference and an increased simulated wind speed bias, with minor exceptions as in the case of Songhor. Overall, the results show that the accurate representations of the local topography and the elevation in the grid simulations are important factors affecting the accuracy of the wind speed simulations. In addition, this study compared the monthly and annual average 10 m wind speeds between the simulated and observed data at 110 meteorological stations. The results show that in 95.45% of the cases, the model overestimated the measured winds. However, an examination of the error values at each station justified the consistency of the model results. The range of the bias error (BE) was from \(-0.69\) to 3.71 m/s, which was categorized into five groups (Table 7). Table 7 presents the percentage of stations according to the BE for each classification group. In more than 77% of the stations, the BE was less than 2 m/s, which is considered satisfactory for wind modelling studies [102]. We also calculated the correlation coefficient (r) values between monthly and annual average simulation and observation data of 10 m wind speed. Initially, this analysis was performed for 110 stations, but then, nine stations with maximum errors (outliers) were removed, leaving 101 stations for analysis. Table 8 provides a summary of the monthly and annual correlation coefficients for the stations, categorized into three levels of BE (BE \(\geq\) 2 m/s, 1 m/s \(\leq\) BE \(<\) 2 m/s, and BE \(<\) 1 m/s). The highest r values occur during the warm season (June to September), when thermal low-pressure systems associated with upper-level anticyclones dominate over the country [103]. On the other hand, the minimum r values are observed during spring (April and May) and the cold season. In winter, unstable conditions arise due to the passing of transition eddies, frontal dust events and convection conditions [103]. As expected, as the BE decreases, the r values increase significantly. Figure 3 displays the topography of Iran and the location of the stations categorized based on their BE (\(-0.69\) m/s \(\leq\) BE \(<\)\(-0.01\) m/s, 0 m/s \(\leq\) BE \(<\) 1 m/s, 1 m/s \(\leq\) BE \(<\) 2 m/s, and BE \(\geq\) 2 m/s). The highest errors typically occurred in stations located in mountainous regions and along the coastlines of the Persian Gulf and Oman Sea.