## 3 Results and Discussion
### Sensitivity Analysis
\begin{table}
\begin{tabular}{c c c c c c} \hline \multicolumn{2}{c}{**January 2013**} & **10 m** & **40 m** & **80 m** & **Average of Three Levels** \\ \hline \multirow{4}{*}{Bias} & MYJ & 1 & 0.97 & 0.75 & 0.9 \\ \cline{2-6}  & MYNN & 1.87 & 0.77 & 0.74 & 1.12 \\ \cline{2-6}  & ACM2 & 1.25 & 0.7 & 0.83 & 0.93 \\ \cline{2-6}  & YSU & 1.25 & 0.91 & 1.04 & 1.06 \\ \cline{2-6}  & QNSE & 1.03 & 0.69 & 0.63 & 0.78 \\ \hline \multirow{4}{*}{RMSE} & MYJ & 4.28 & 4.17 & 4.2 & 4.21 \\ \cline{2-6}  & MYNN & 4.41 & 4.13 & 4.2 & 4.25 \\ \cline{2-6}  & ACM2 & 4.39 & 4.08 & 4.24 & 4.24 \\ \cline{2-6}  & YSU & 4.44 & 4.18 & 4.3 & 4.31 \\ \cline{2-6}  & QNSE & 4.28 & 4.07 & 4.08 & 4.14 \\ \hline \multirow{4}{*}{STDE} & MYJ & 4.12 & 4.04 & 4.11 & 4.09 \\ \cline{2-6}  & MYNN & 4.18 & 4.05 & 4.12 & 4.12 \\ \cline{1-1} \cline{2-6}  & ACM2 & 4.16 & 4.01 & 4.06 & 4.07 \\ \cline{1-1} \cline{2-6}  & YSU & 4.22 & 4.06 & 4.17 & 4.15 \\ \cline{1-1} \cline{2-6}  & QNSE & 4.12 & 3.99 & 4.03 & 4.05 \\ \hline \end{tabular}
\end{table} 
Table 4: Statistical parameters calculated from the comparison between the model outputs and wind observations at mast stations for different PBL schemes in January 2013. As mentioned by [PERSON] et al. [88], these differences in model simulations using several PBL schemes are mostly related to localized and non-localized closure schemes of the PBL parameterizations. Local PBL schemes (such as MYJ, MYNN, and QNSE) calculate the turbulent kinetic energy (TKE) considering the local variance and covariance of potential temperature and water vapor mixing ratio [11] and apply the predicted TKE to estimate the PBL height [89]. Non-local closure schemes, such as YSU and ACM2, use several vertical levels in a single column for estimating turbulent fluxes and unknown atmospheric variables in every grid cell and they try to simulate the effects of larger eddies on the converging boundary layer [89]. Non-local closure schemes usually do not calculate the TKE and the height of the PBL is estimated using experimental formulas based on the wind speed [89]. As can be detected from the current results, non-local PBL schemes exhibit slightly better performance during the warm months of the year. Although ACM2 is often considered as a non-local scheme, this parameterization is actually a combination of local and non-local closure formulations, since it uses a local closure scheme when the atmospheric regime is stable or neutral. The local PBL schemes are more suitable for a stable atmospheric regime [90], since gradients of these types of schemes in unstable atmospheric conditions maybe lead to some errors, in which turbulent motions are affected by large eddies and are able to transmit variables over longer distances [91; 92]. In contrast, non-local schemes are more appropriate for simulating unstable boundary-layer conditions [93; 94]. On the other hand, non-local schemes often tend to demonstrate a deeper boundary layer under windy conditions [95], which tampers with the boundary layer turbulence simulation. It should also be noted that the performance of the boundary layer parameterizations is influenced by other physical parameters such as cloud microphysics, aerosol-induced forcing, and surface reflectivity, which play an important role in simulation of inversion conditions [96; 4; 97]. One of the main sources of error in NWP models when simulating near-surface winds is the limited representation of the local terrain characteristics such as topography, vegetation coverage and roughness [98; 99; 100]. In addition, WRF physical parameterizations related to boundary-layer processes have mainly been developed through the observation data obtained from smooth surfaces [101], thus further contributing to WRF's limitations in accurately representing the wind regime over complex terrain.