Understanding the Major Impact of Planetary Boundary Layer Schemes on Simulation of Vertical Wind Structure

The structure and evolution of the atmospheric planetary boundary layer (PBL) plays an important role in the physical and chemical processes of cloud–radiation interaction, vertical mixing and pollutant transport in the atmosphere. The PBL parameterization scheme describes the vertical transport of atmospheric momentum, heat, water vapor and other physical quantities in the boundary layer. The accuracy of wind field simulation and prediction is one of the most significant parameters in the field of atmospheric science and wind energy. Limited by the observation data, there are few studies on wind energy development. A 3D Doppler wind LiDAR (DWL) providing the high-vertical-resolution wind data over the urban complex underlying surface in February 2018 was employed to systematically evaluate the accuracy of vertical wind field simulation for the first time. 11 PBL schemes of the Weather Research and Forecasting Model (WRF) were employed in simulation. The model results were evaluated in groups separated by weather (sunny days, hazy days and windy days), observation height layers of wind field, and various observation wind speeds. Among these factors, the simulation accuracy is most closely related to the observation height layers of wind field. The simulation is fairly accurate at a height of 1000–2000 m, as most of the relative mean biases for wind speed and wind direction are less than 20% and 6% respectively. Below 1000 m, the wind speed and direction biases are about 30–150% m·s−1 and 6–30%, respectively. Moreover, when the observed wind speed was lower than 5 m·s−1, the biases were usually large, and the wind speed relative mean bias reaches up to 50–300%. In addition, the accuracy of the simulated wind profile is better in the range of 10–15 m·s−1 than other speed ranges, and is better above 1000 m than below 1000 m in the boundary layer. We see that the WRF boundary layer schemes have different applicabilities to different weather conditions. The WRF boundary layer schemes have significant differences in wind field simulations, with larger error under the complex topographies. A PBL scheme is not likely to maintain its advantages in the long term under different conditions including altitude and weather conditions.


Introduction
Wind energy is an inexhaustible source of clean energy. The development of wind power plays an important role in improving the energy infrastructure, protecting the ecological environment, ensuring energy security, and achieving sustainable economic development. The use of wind energy is attracting more and more international attention, The DBS scanning mode of vertical observation was adopted. The LiDAR lens transmits four rays at 0°, 90°, 180° and 270° respectively, with a zenith angle of 15° (the angle with vertical direction), and one ray with a vertical direction; thus, the distributions of 3D wind speed and direction at different heights were obtained. The wavelength of the transmitter was 1.5 μm. Its minimum physical resolution was 25 m. According to the principle of DWL, the blind detection area of the instrument was twice the minimum resolution, so it could only monitor the wind field data above 50 m. DWL has good field observation performance, and it can provide 24 h uninterrupted measurements of meteorological elements such as wind velocity, wind direction, temperature and atmospheric refractive index from 50 m to 3000 m above the surface, with a sampling resolution per 20 s. Following the detection method of Brewster K A [16], the accuracy of the DWL data was verified using the special meteorological observation tower, belonging to the IAP, and the missing DWL data caused by strong noise in the near ground signal were eliminated. The tower is 325 m high, divided into 15 layers, and can provide high-quality observation data for Atmospheric Research and measure wind direction and speed.

Experimental Design
WRF3.9 was used in this study. We conducted a set of model experiments, corresponding to the 11 PBL schemes discussed in the context. Their abbreviations are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, Shin-Hong, and GBM (Table  1). These schemes correspond to either local or nonlocal closure.
Local closure estimates the unknown PBL quantities by the physical quantities or gradients, through predicting the turbulence perturbation kinetic energy (TKE) at the same place, while nonlocal closure estimates quantities with many known physical quantities or gradients besides the unknown grid. The K-profile method of first-order closure is employed to address the turbulence closure schemes. YSU and ACM2 are nonlocal schemes, while the others are local schemes.
We set up three nested domains centered at 116.68° E, 39.87° N ( Figure 1). The horizontal resolutions were 27, 9 and 3 km, with the domain sizes of 100 × 94, 70 × 67 and 64 × 55, respectively. The outermost domain, d01, covered most of China. The second domain, d02, covered the North China Plain and the northwestern mountainous area, including The DBS scanning mode of vertical observation was adopted. The LiDAR lens transmits four rays at 0 • , 90 • , 180 • and 270 • respectively, with a zenith angle of 15 • (the angle with vertical direction), and one ray with a vertical direction; thus, the distributions of 3D wind speed and direction at different heights were obtained. The wavelength of the transmitter was 1.5 µm. Its minimum physical resolution was 25 m. According to the principle of DWL, the blind detection area of the instrument was twice the minimum resolution, so it could only monitor the wind field data above 50 m. DWL has good field observation performance, and it can provide 24 h uninterrupted measurements of meteorological elements such as wind velocity, wind direction, temperature and atmospheric refractive index from 50 m to 3000 m above the surface, with a sampling resolution per 20 s. Following the detection method of Brewster K A [16], the accuracy of the DWL data was verified using the special meteorological observation tower, belonging to the IAP, and the missing DWL data caused by strong noise in the near ground signal were eliminated. The tower is 325 m high, divided into 15 layers, and can provide high-quality observation data for Atmospheric Research and measure wind direction and speed.

Experimental Design
WRF3.9 was used in this study. We conducted a set of model experiments, corresponding to the 11 PBL schemes discussed in the context. Their abbreviations are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, Shin-Hong, and GBM (Table 1). These schemes correspond to either local or nonlocal closure.
Local closure estimates the unknown PBL quantities by the physical quantities or gradients, through predicting the turbulence perturbation kinetic energy (TKE) at the same place, while nonlocal closure estimates quantities with many known physical quantities or gradients besides the unknown grid. The K-profile method of first-order closure is employed to address the turbulence closure schemes. YSU and ACM2 are nonlocal schemes, while the others are local schemes.
We including Beijing city. The third domain is the main research area, and is near the IAP. The atmosphere is divided vertically into 43 layers, including 29 layers below 2 km, and the top layer is at 50 hPa. The physical parameterizations include the Dudhia shortwave radiation scheme, the Rapid Radiative Transfer Model longwave radiation scheme, the Kessler scheme for microphysical processes, and the Grell cumulus convection parameterization scheme. As it is not suitable for this fine resolution, the cumulus convection scheme was only applied in d01 and d02 regions, and was turned off in d03. The model was driven by the NCEP/NCAR reanalysis data and integrated from February 24 to March 2, 2018, with an additional 6 h for spin-up [17]. The model results were output every half an hour. Considers the influence of the entrainment process at the top of the mixed layer on turbulent transport; the height of PBL depends only on the buoyancy profile [18] 2 Mellor-Yamada-Janjic Scheme (MYJ) Local Turbulent kinetic energy (TKE) closure scheme, 1.5-order closure model It was suitable for studying fine PBL structure. The height of PBL was determined by the turbulent energy profile [19] 3 NCEP Global Forecast System (GFS) Nonlocal First-order vertical mixing scheme The height of the PBL was determined by the iterative bulk Rechardson method from the surface up integration. The diffusion coefficient above the surface was a cubic function of the height of the PBL, and its coefficient value was obtained by the coupled surface flux [20] 4 Quasi-normal Scale Elimination (QNSE) Local TKE Closing Scheme, 1.5 Order Closing Model The physical process was complex and suitable for the prediction and simulation of the PBL in the stable layer region [21] 5 Considered the physical process of condensation, the prediction of mixed layer thickness was improved, the TKE magnitude decreased, and the time bias of fog formation and dissipation prediction was reduced [23] 7 Asymmetric Convection Model 2 Scheme (ACM2)

Nonlocal +Local
The upward and downward mixing process were local. First-order Closed Model The thermal penetration and wind shear of the entrainment layer were considered in the PBL height under unstable conditions. The height of the PBL was determined by the Richardson number [ Considered the entrainment process at the top of the PBL, the cloud cover could be well simulated, and the height of the PBL could be calculated according to the grid point heat [28] Figure 2 illustrates the observed DWL wind data in our case. The PBL wind was weak below a height of 800 m on February 24-25, indicating a stable boundary air. The PBL wind speed increased in the daytime on February 26, and the wind direction above 1000 m height changed from southwest to northwest. The wind slowed again on February 27 and became strong on February 28. At the middle troposphere, according to the MICAPS 4.0 analysis, a cold high pressure was maintained at 500 hPa over northern China, and the low atmosphere was stable. On February 26, a shallow trough passed through Beijing, resulting in haze weather. From 14:00-17:00 UTC (Coordinated Universal Time) on February 28, a cold front induced an upper gale over Beijing and a gale at the ground at 17:00-20:00 UTC. After a short break with gentle winds, the southwest wind was enhanced at 02:00 UTC on 1 March. below a height of 800 m on February 24-25, indicating a stable boundary air. The PBL wind speed increased in the daytime on February 26, and the wind direction above 1000 m height changed from southwest to northwest. The wind slowed again on February 27 and became strong on February 28. At the middle troposphere, according to the MICAPS 4.0 analysis, a cold high pressure was maintained at 500 hPa over northern China, and the low atmosphere was stable. On February 26, a shallow trough passed through Beijing, resulting in haze weather. From 14:00-17:00 UTC (Coordinated Universal Time) on February 28, a cold front induced an upper gale over Beijing and a gale at the ground at 17:00-20:00 UTC. After a short break with gentle winds, the southwest wind was enhanced at 02:00 UTC on 1 March.  The height of the PBL was determined by the iterative bulk Rechardson method from the surface up integration. The diffusion coefficient above the surface was a cubic function of the height of the PBL, and its coefficient value was obtained by the coupled surface flux [20]  Apparently, the PBL wind structures changed substantially under different weather conditions. To clarify the performances of PBL schemes, we evaluated the model results in three weather types, sunny days (24)(25), hazy days (26)(27) and windy days (28 February-1 March). The model results at the same height as the DWL vertical observation were compared. Then the model and observation data were grouped depending on the observed wind speeds (i.e., <5, 5-10, 10-15 and >15 m s -1 ) and six layer heights (30-100, 100-320, 320-1000, 1000-1500, 1500-2000 and >2000 m) to attain a reliable statistical result. Table 2 lists the paired sample sizes in each group. The statistical quantities for evaluation include the model mean bias, correlation coefficient and standard deviation for the wind speeds and directions between the model results (x) and the observations (y) across N layer heights: Mean Bias MB = y − x (1) Correlation Coefficient Standard Deviation  Figure 3 shows the PBL wind speed profiles and the model biases with different PBL schemes. The simulated and observed wind speeds varies greatly with altitude. Compared with Figure 2, most of the PBL schemes captured the evolution of wind speed over the days. Figure 4 shows the variation of simulated and observed wind speed with time at an altitude of about 1010 m. During the whole model period, the mean model biases in wind speeds were positive in the layer at 0-1000 m. All PBL schemes had model biases no greater than 10 m·s −1 . The model layers near the surface were greatly affected by the roughness length of urban boundary layers which are parameterized in the model with uncertainty. The model biases changed with weather conditions. On hazy days (February 26-27), the observed wind speeds were lower than on the clear days, because the stagnant weather conditions and the aerosol radiative feedback both enhanced the PBL stability and also lowered the surface wind speeds [29]. For example, when the wind speed was 5-10 m·s −1 , the simulated wind speed on the hazy days was 1-2 m·s −1 (18-38%) lower than the observed wind speed on each level. On windy days (28 February 28-1 March), the model bias in wind direction decreased along the height. In the layer of 1000-1500 m, the wind direction bias of PBL schemes were 1.1 • -9.1 • (0.4-3.4%) (except bias of QNSE was 88 • , 33.4%).     Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20 • . On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80 • or even more than 100 • at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20 • . The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100 • for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180 • at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80 • , or even more than 100 • , while the other schemes had biases within 20 • . The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100 • in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180 • at a height of 1500-2000 m. In Table 3, and their biases (g-n) against the observations. The sunny, haze and windy and 28 February to 1 March, respectively. Figure 5 presents the model biases in for different horizontal speed levels. Gene horizontal wind speed smaller than 2 m· than 20°. On gentle windy days with obse reached up to 10 m·s −1 . On sunny days and at 1000-1500 m and 1500-2000 m, wher showed the maximum model bias in wind On windy days, the biases in wind direc heights of 300-1000 m, 1000-1500 m, and PBL schemes were within 20°. The MYJ sc lation, but overestimated the wind directi level of 5-10 m·s −1 , the biases in wind MYNN2.5, MYNN3 and BouLac schemes. ticularly when the observed wind speeds wind speed was less than 5 m·s −1 , the win more than 180° at 1500-2000 m. Table 3 sh height and wind speed interval. At 1000-1 standard deviation was large when the ob less than 5 m·s −1 . The QNSE schemes gav on sunny days, but the model results beca days, the QNSE scheme led to standard de to 80°, or even more than 100°, while the scheme well simulated the wind speed, b reached up to about 280%. The variations MYNN2.5, MYNN3 and BouLac schemes m·s −1 . On hazy days, for wind speeds less of wind direction were more than 180 ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 1 YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN shows the simulation effect of wind speed (0-5, 5-10, 10-15, greater than 15) under th wind) at different heights (below 100, 100-2000 m). For the convenience of comparis horizontal height of the observation point. observed altitude and the simulated altitud or direction biases lower than 20% can be example, on sunny days, when the heigh speed was less than 5, the wind speed bias the wind speed was between 5 and 10, th less than 20%, which indicates that the sim represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes and were less than 20%, which indicates that the simulation effects of the PBL schemes were better.   Table 3. Under different conditions, the PBL schemes with low biases of wind speed and direction, large correlation coefficients, and close standard deviation on sunny days, hazy days and windy days, and at four wind speeds ranges (0-5, 5-10, 10-15, over 15). The bias of suitable scheme in the table is below 20%. "-" Indicates poor simulation or no data. "All" means all the PBL schemes.

Wind Speed Simulation
--  Table 3. Under different conditions, the PBL schemes with low biases of wind speed and direction, large correlation coefficients, and close standard deviation on sunny days, hazy days and windy days, and at four wind speeds ranges (0-5, 5-10, 10-15, over 15). The bias of suitable scheme in the table is below 20%. "-" Indicates poor simulation or no data. "All" means all the PBL schemes.

0-5 5-10 10-15 >15
Sunny days <100 --100-300 reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better. reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific  height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated  standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.
--300-1000 -1000-1500 -for different horizontal speed levels. Generally, all the PBL schemes had mode horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , th reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m showed the maximum model bias in wind speeds, particularly on haze and w On windy days, the biases in wind direction were about 80° or even more th heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the bias PBL schemes were within 20°. The MYJ scheme performed well in the wind sp lation, but overestimated the wind direction by about 280% below 300 m. At w level of 5-10 m·s −1 , the biases in wind direction were over 100° for the Y MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with h ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy days wind speed was less than 5 m·s −1 , the wind direction biases for these PBL sch more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme fo height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the standard deviation was large when the observed wind speeds exceeded 15 m· less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direc on sunny days, but the model results became worse on hazy and windy days. days, the QNSE scheme led to standard deviations of wind directions at 300-20 to 80°, or even more than 100°, while the other schemes had biases within 20° scheme well simulated the wind speed, but the variation of wind direction be reached up to about 280%. The variations of wind directions when using the MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed le m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard of wind direction were more than 180° at a height of 1500-2000 m. In ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. shows the simulation effect of wind speed and direction in different wind speed (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000 2000 m). For the convenience of comparison, the simulated height is consisten horizontal height of the observation point. Therefore, the altitude here represen observed altitude and the simulated altitude. Additionally, only schemes with w or direction biases lower than 20% can be shown in the table. According to T example, on sunny days, when the height was less than 100 m, and the obse speed was less than 5, the wind speed biases of scheme ③ were less than 20%, the wind speed was between 5 and 10, the wind speed bias of schemes ③ an less than 20%, which indicates that the simulation effects of the PBL schemes w -1500-2000 -- Figure 5 presents the model biases in the horizontal wind components at each for different horizontal speed levels. Generally, all the PBL schemes had model bia horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction wer than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YS reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . showed the maximum model bias in wind speeds, particularly on haze and windy On windy days, the biases in wind direction were about 80° or even more than 1 heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of PBL schemes were within 20°. The MYJ scheme performed well in the wind speed lation, but overestimated the wind direction by about 280% below 300 m. At wind level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with heigh ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, wh wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a sp height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simu standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction on sunny days, but the model results became worse on hazy and windy days. On w days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m to 80°, or even more than 100°, while the other schemes had biases within 20°. Th scheme well simulated the wind speed, but the variation of wind direction below reached up to about 280%. The variations of wind directions when using the YSU MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level o m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard devi of wind direction were more than 180° at a height of 1500-2000 m. In Ta ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; the YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The shows the simulation effect of wind speed and direction in different wind speed seg (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, s wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and 2000 m). For the convenience of comparison, the simulated height is consistent wi horizontal height of the observation point. Therefore, the altitude here represents bo observed altitude and the simulated altitude. Additionally, only schemes with wind or direction biases lower than 20% can be shown in the table. According to Table  example, on sunny days, when the height was less than 100 m, and the observed speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ less than 20%, which indicates that the simulation effects of the PBL schemes were ->2000 -All Hazy days <100 and 28 February to 1 March, respectively. Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.

Horizontal Wind Component in PBL
---100-300 All --300-1000  Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.

Horizontal Wind Component in PBL
-1000-1500  Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.   Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.   Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.

Horizontal Wind Component in PBL
Atmosphere 2021, 12, x FOR PEER REVIEW Figure 4. The wind field simulations (a-f) with the PBL schemes of YSU, MYJ, QNSE, BouLac, UW and Shin-Hong and their biases (g-n) against the observations. The sunny, haze and windy days were on 24-25 February, 26-27 and 28 February to 1 March, respectively. Figure 5 presents the model biases in the horizontal wind components for different horizontal speed levels. Generally, all the PBL schemes had mo horizontal wind speed smaller than 2 m·s −1 , and the biases in wind directi than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YS at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 showed the maximum model bias in wind speeds, particularly on haze and On windy days, the biases in wind direction were about 80° or even more heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the bi PBL schemes were within 20°. The MYJ scheme performed well in the wind lation, but overestimated the wind direction by about 280% below 300 m. A level of 5-10 m·s −1 , the biases in wind direction were over 100° for th MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy da wind speed was less than 5 m·s −1 , the wind direction biases for these PBL s more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, t standard deviation was large when the observed wind speeds exceeded 15 less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and di on sunny days, but the model results became worse on hazy and windy day days, the QNSE scheme led to standard deviations of wind directions at 300to 80°, or even more than 100°, while the other schemes had biases within 2 scheme well simulated the wind speed, but the variation of wind direction reached up to about 280%. The variations of wind directions when using th MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standar of wind direction were more than 180° at a height of 1500-2000 m. ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schem YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM shows the simulation effect of wind speed and direction in different wind spe (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny da wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-20 2000 m). For the convenience of comparison, the simulated height is consis horizontal height of the observation point. Therefore, the altitude here repres observed altitude and the simulated altitude. Additionally, only schemes with or direction biases lower than 20% can be shown in the table. According to example, on sunny days, when the height was less than 100 m, and the ob speed was less than 5, the wind speed biases of scheme ③ were less than 20 the wind speed was between 5 and 10, the wind speed bias of schemes ③ less than 20%, which indicates that the simulation effects of the PBL schemes ->2000 -   Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.

Horizontal Wind Component in PBL
Atmosphere 2021, 12, x FOR PEER REVIEW Figure 4. The wind field simulations (a-f) with the PBL schemes of YSU, MYJ, QNSE, BouLac, UW and Shin-Hon and their biases (g-n) against the observations. The sunny, haze and windy days were on 24-25 February, 26-27 and 28 February to 1 March, respectively. Figure 5 presents the model biases in the horizontal wind component for different horizontal speed levels. Generally, all the PBL schemes had m horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direc than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of Y at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 showed the maximum model bias in wind speeds, particularly on haze and On windy days, the biases in wind direction were about 80° or even mor heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the b PBL schemes were within 20°. The MYJ scheme performed well in the win lation, but overestimated the wind direction by about 280% below 300 m. A level of 5-10 m·s −1 , the biases in wind direction were over 100° for th MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased wi ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy d wind speed was less than 5 m·s −1 , the wind direction biases for these PBL more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL schem height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, standard deviation was large when the observed wind speeds exceeded 15 less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and d on sunny days, but the model results became worse on hazy and windy da days, the QNSE scheme led to standard deviations of wind directions at 300 to 80°, or even more than 100°, while the other schemes had biases within scheme well simulated the wind speed, but the variation of wind direction reached up to about 280%. The variations of wind directions when using MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standa of wind direction were more than 180° at a height of 1500-2000 m ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schem YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GB shows the simulation effect of wind speed and direction in different wind sp (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny d wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2 2000 m). For the convenience of comparison, the simulated height is consi horizontal height of the observation point. Therefore, the altitude here repre observed altitude and the simulated altitude. Additionally, only schemes wi or direction biases lower than 20% can be shown in the table. According example, on sunny days, when the height was less than 100 m, and the o speed was less than 5, the wind speed biases of scheme ③ were less than 2 the wind speed was between 5 and 10, the wind speed bias of schemes ③ less than 20%, which indicates that the simulation effects of the PBL scheme -Windy days <100

Horizontal Wind Component in PBL
--100-300 -All Atmosphere 2021, 12, x FOR PEER REVIEW Figure 4. The wind field simulations (a-f) with the PBL schemes of YSU, MYJ, QNSE, B and their biases (g-n) against the observations. The sunny, haze and windy days wer and 28 February to 1 March, respectively. Figure 5 presents the model biases in the horiz for different horizontal speed levels. Generally, all horizontal wind speed smaller than 2 m·s −1 , and th than 20°. On gentle windy days with observed wind reached up to 10 m·s −1 . On sunny days and hazy day at 1000-1500 m and 1500-2000 m, where the wi showed the maximum model bias in wind speeds, On windy days, the biases in wind direction were heights of 300-1000 m, 1000-1500 m, and 1500-20 PBL schemes were within 20°. The MYJ scheme per lation, but overestimated the wind direction by abo level of 5-10 m·s −1 , the biases in wind direction MYNN2.5, MYNN3 and BouLac schemes. The mod ticularly when the observed wind speeds were less wind speed was less than 5 m·s −1 , the wind directio more than 180° at 1500-2000 m. Table 3 shows the b height and wind speed interval. At 1000-1500 m an standard deviation was large when the observed w less than 5 m·s −1 . The QNSE schemes gave a reason on sunny days, but the model results became wors days, the QNSE scheme led to standard deviations o to 80°, or even more than 100°, while the other sch scheme well simulated the wind speed, but the var reached up to about 280%. The variations of wind MYNN2.5, MYNN3 and BouLac schemes were ove m·s −1 . On hazy days, for wind speeds less than 5 m· of wind direction were more than 180° at a h ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 differen YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM shows the simulation effect of wind speed and direc (0-5, 5-10, 10-15, greater than 15) under three weat wind) at different heights (below 100, 100-300, 300-2000 m). For the convenience of comparison, the si horizontal height of the observation point. Therefor observed altitude and the simulated altitude. Additi or direction biases lower than 20% can be shown i example, on sunny days, when the height was less speed was less than 5, the wind speed biases of sche the wind speed was between 5 and 10, the wind sp less than 20%, which indicates that the simulation e 300-1000 -1000-1500

Horizontal Wind Component in PBL
Atmosphere 2021, 12, x FOR PEER REVIEW  Figure 5 presents the model biases in the horizontal wind components at for different horizontal speed levels. Generally, all the PBL schemes had mode horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , th reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m showed the maximum model bias in wind speeds, particularly on haze and w On windy days, the biases in wind direction were about 80° or even more th heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the bias PBL schemes were within 20°. The MYJ scheme performed well in the wind sp lation, but overestimated the wind direction by about 280% below 300 m. At w level of 5-10 m·s −1 , the biases in wind direction were over 100° for the Y MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with h ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy days wind speed was less than 5 m·s −1 , the wind direction biases for these PBL sch more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme fo height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the standard deviation was large when the observed wind speeds exceeded 15 m· less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direc on sunny days, but the model results became worse on hazy and windy days. days, the QNSE scheme led to standard deviations of wind directions at 300-20 to 80°, or even more than 100°, while the other schemes had biases within 20° scheme well simulated the wind speed, but the variation of wind direction be reached up to about 280%. The variations of wind directions when using the MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed le m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard of wind direction were more than 180° at a height of 1500-2000 m. In ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. shows the simulation effect of wind speed and direction in different wind speed (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000 2000 m). For the convenience of comparison, the simulated height is consisten horizontal height of the observation point. Therefore, the altitude here represen observed altitude and the simulated altitude. Additionally, only schemes with w or direction biases lower than 20% can be shown in the table. According to T example, on sunny days, when the height was less than 100 m, and the obse speed was less than 5, the wind speed biases of scheme ③ were less than 20%, the wind speed was between 5 and 10, the wind speed bias of schemes ③ an less than 20%, which indicates that the simulation effects of the PBL schemes w 1500-2000 --  Figure 5 presents the model biases in the horizontal wind components at ea for different horizontal speed levels. Generally, all the PBL schemes had model horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction w than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the Y reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU w at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s − showed the maximum model bias in wind speeds, particularly on haze and win On windy days, the biases in wind direction were about 80° or even more than heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases PBL schemes were within 20°. The MYJ scheme performed well in the wind spee lation, but overestimated the wind direction by about 280% below 300 m. At win level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YS MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with hei ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, w wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schem more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the si standard deviation was large when the observed wind speeds exceeded 15 m·s −1 less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and directio on sunny days, but the model results became worse on hazy and windy days. O days, the QNSE scheme led to standard deviations of wind directions at 300-2000 to 80°, or even more than 100°, while the other schemes had biases within 20°. T scheme well simulated the wind speed, but the variation of wind direction belo reached up to about 280%. The variations of wind directions when using the YS MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed leve m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard de of wind direction were more than 180° at a height of 1500-2000 m. In ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; t YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. Th shows the simulation effect of wind speed and direction in different wind speed s (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, a 2000 m). For the convenience of comparison, the simulated height is consistent horizontal height of the observation point. Therefore, the altitude here represents observed altitude and the simulated altitude. Additionally, only schemes with win or direction biases lower than 20% can be shown in the table. According to Tab example, on sunny days, when the height was less than 100 m, and the observ speed was less than 5, the wind speed biases of scheme ③ were less than 20%, an the wind speed was between 5 and 10, the wind speed bias of schemes ③ and less than 20%, which indicates that the simulation effects of the PBL schemes wer >2000 ---Atmosphere 2021, 12, x FOR PEER REVIEW Figure 4. The wind field simulations (a-f) with the PBL schemes of YSU, MYJ, QNSE, Bo and their biases (g-n) against the observations. The sunny, haze and windy days were and 28 February to 1 March, respectively. Figure 5 presents the model biases in the horizo for different horizontal speed levels. Generally, all th horizontal wind speed smaller than 2 m·s −1 , and th than 20°. On gentle windy days with observed wind reached up to 10 m·s −1 . On sunny days and hazy days at 1000-1500 m and 1500-2000 m, where the win showed the maximum model bias in wind speeds, p On windy days, the biases in wind direction were a heights of 300-1000 m, 1000-1500 m, and 1500-200 PBL schemes were within 20°. The MYJ scheme perf lation, but overestimated the wind direction by abou level of 5-10 m·s −1 , the biases in wind direction MYNN2.5, MYNN3 and BouLac schemes. The mode ticularly when the observed wind speeds were less t wind speed was less than 5 m·s −1 , the wind direction more than 180° at 1500-2000 m. Table 3 shows the bi height and wind speed interval. At 1000-1500 m and standard deviation was large when the observed wi less than 5 m·s −1 . The QNSE schemes gave a reasona on sunny days, but the model results became worse days, the QNSE scheme led to standard deviations of to 80°, or even more than 100°, while the other sche scheme well simulated the wind speed, but the vari reached up to about 280%. The variations of wind d MYNN2.5, MYNN3 and BouLac schemes were over m·s −1 . On hazy days, for wind speeds less than 5 m·s of wind direction were more than 180° at a he ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2 shows the simulation effect of wind speed and direct (0-5, 5-10, 10-15, greater than 15) under three weath wind) at different heights (below 100, 100-300, 300-1 2000 m). For the convenience of comparison, the sim horizontal height of the observation point. Therefore observed altitude and the simulated altitude. Additio or direction biases lower than 20% can be shown in example, on sunny days, when the height was less speed was less than 5, the wind speed biases of schem the wind speed was between 5 and 10, the wind spe less than 20%, which indicates that the simulation ef   Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.

Horizontal Wind Component in PBL
--300-1000   Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.

All
--1000-1500 -   Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.   , the biases in wind direction were over 100° for th MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased wi ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy d wind speed was less than 5 m·s −1 , the wind direction biases for these PBL more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL schem height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, standard deviation was large when the observed wind speeds exceeded 15 less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and d on sunny days, but the model results became worse on hazy and windy da days, the QNSE scheme led to standard deviations of wind directions at 300 to 80°, or even more than 100°, while the other schemes had biases within scheme well simulated the wind speed, but the variation of wind direction reached up to about 280%. The variations of wind directions when using MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standa of wind direction were more than 180° at a height of 1500-2000 m ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schem YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GB shows the simulation effect of wind speed and direction in different wind sp (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny d wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2 2000 m). For the convenience of comparison, the simulated height is consi horizontal height of the observation point. Therefore, the altitude here repre observed altitude and the simulated altitude. Additionally, only schemes wi or direction biases lower than 20% can be shown in the table. According example, on sunny days, when the height was less than 100 m, and the o speed was less than 5, the wind speed biases of scheme ③ were less than 2 the wind speed was between 5 and 10, the wind speed bias of schemes ③ less than 20%, which indicates that the simulation effects of the PBL scheme   Figure 5 presents the model biases in the h for different horizontal speed levels. Generally, horizontal wind speed smaller than 2 m·s −1 , an than 20°. On gentle windy days with observed w reached up to 10 m·s −1 . On sunny days and hazy at 1000-1500 m and 1500-2000 m, where the showed the maximum model bias in wind spee On windy days, the biases in wind direction w heights of 300-1000 m, 1000-1500 m, and 1500 PBL schemes were within 20°. The MYJ scheme lation, but overestimated the wind direction by level of 5-10 m·s −1 , the biases in wind direct MYNN2.5, MYNN3 and BouLac schemes. The m ticularly when the observed wind speeds were wind speed was less than 5 m·s −1 , the wind dire more than 180° at 1500-2000 m. Table 3 shows t height and wind speed interval. At 1000-1500 m standard deviation was large when the observe less than 5 m·s −1 . The QNSE schemes gave a rea on sunny days, but the model results became w days, the QNSE scheme led to standard deviatio to 80°, or even more than 100°, while the other scheme well simulated the wind speed, but the reached up to about 280%. The variations of wi MYNN2.5, MYNN3 and BouLac schemes were m·s −1 . On hazy days, for wind speeds less than 5 of wind direction were more than 180° at ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 diff YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, AC shows the simulation effect of wind speed and d (0-5, 5-10, 10-15, greater than 15) under three w wind) at different heights (below 100, 100-300, 3 2000 m). For the convenience of comparison, th horizontal height of the observation point. There observed altitude and the simulated altitude. Ad or direction biases lower than 20% can be show example, on sunny days, when the height was speed was less than 5, the wind speed biases of the wind speed was between 5 and 10, the win less than 20%, which indicates that the simulatio

1500-2000
Atmosphere 2021, 12, x FOR PEER REVIEW 8 of 15  Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.   . showed the maximum model bias in wind speeds, particularly on haze and windy On windy days, the biases in wind direction were about 80° or even more than 1 heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of PBL schemes were within 20°. The MYJ scheme performed well in the wind speed lation, but overestimated the wind direction by about 280% below 300 m. At wind level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with heigh ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, wh wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a sp height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simu standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction on sunny days, but the model results became worse on hazy and windy days. On w days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m to 80°, or even more than 100°, while the other schemes had biases within 20°. Th scheme well simulated the wind speed, but the variation of wind direction below reached up to about 280%. The variations of wind directions when using the YSU MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level o m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard devi of wind direction were more than 180° at a height of 1500-2000 m. In Ta ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; the YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The shows the simulation effect of wind speed and direction in different wind speed seg (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, s wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and 2000 m). For the convenience of comparison, the simulated height is consistent wi horizontal height of the observation point. Therefore, the altitude here represents bo observed altitude and the simulated altitude. Additionally, only schemes with wind or direction biases lower than 20% can be shown in the table. According to Table  example, on sunny days, when the height was less than 100 m, and the observed speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ less than 20%, which indicates that the simulation effects of the PBL schemes were   , the biases in wind dir MYNN2.5, MYNN3 and BouLac schemes. The ticularly when the observed wind speeds wer wind speed was less than 5 m·s −1 , the wind d more than 180° at 1500-2000 m. Table 3 show height and wind speed interval. At 1000-1500 standard deviation was large when the obser less than 5 m·s −1 . The QNSE schemes gave a on sunny days, but the model results became days, the QNSE scheme led to standard devia to 80°, or even more than 100°, while the oth scheme well simulated the wind speed, but th reached up to about 280%. The variations of MYNN2.5, MYNN3 and BouLac schemes wer m·s −1 . On hazy days, for wind speeds less than of wind direction were more than 180° a ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 d YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, shows the simulation effect of wind speed and (0-5, 5-10, 10-15, greater than 15) under three wind) at different heights (below 100, 100-300 2000 m). For the convenience of comparison, horizontal height of the observation point. The observed altitude and the simulated altitude. A or direction biases lower than 20% can be sh example, on sunny days, when the height w speed was less than 5, the wind speed biases o the wind speed was between 5 and 10, the w less than 20%, which indicates that the simula >2000 -   Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.   , the biases in wind direction were over 100° for th MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy da wind speed was less than 5 m·s −1 , the wind direction biases for these PBL s more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, t standard deviation was large when the observed wind speeds exceeded 15 less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and di on sunny days, but the model results became worse on hazy and windy day days, the QNSE scheme led to standard deviations of wind directions at 300to 80°, or even more than 100°, while the other schemes had biases within 2 scheme well simulated the wind speed, but the variation of wind direction reached up to about 280%. The variations of wind directions when using th MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standar of wind direction were more than 180° at a height of 1500-2000 m. ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schem YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM shows the simulation effect of wind speed and direction in different wind spe (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny da wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-20 2000 m). For the convenience of comparison, the simulated height is consis horizontal height of the observation point. Therefore, the altitude here repres observed altitude and the simulated altitude. Additionally, only schemes with or direction biases lower than 20% can be shown in the table. According to example, on sunny days, when the height was less than 100 m, and the ob speed was less than 5, the wind speed biases of scheme ③ were less than 20 the wind speed was between 5 and 10, the wind speed bias of schemes ③ less than 20%, which indicates that the simulation effects of the PBL schemes   Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.   , and the biases in wind direc than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of Y at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 showed the maximum model bias in wind speeds, particularly on haze and On windy days, the biases in wind direction were about 80° or even mor heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the b PBL schemes were within 20°. The MYJ scheme performed well in the win lation, but overestimated the wind direction by about 280% below 300 m. A level of 5-10 m·s −1 , the biases in wind direction were over 100° for th MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased wi ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy d wind speed was less than 5 m·s −1 , the wind direction biases for these PBL more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL schem height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, standard deviation was large when the observed wind speeds exceeded 15 less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and d on sunny days, but the model results became worse on hazy and windy da days, the QNSE scheme led to standard deviations of wind directions at 300 to 80°, or even more than 100°, while the other schemes had biases within scheme well simulated the wind speed, but the variation of wind direction reached up to about 280%. The variations of wind directions when using MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standa of wind direction were more than 180° at a height of 1500-2000 m ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schem YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GB shows the simulation effect of wind speed and direction in different wind sp (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny d wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2 2000 m). For the convenience of comparison, the simulated height is consi horizontal height of the observation point. Therefore, the altitude here repre observed altitude and the simulated altitude. Additionally, only schemes wi or direction biases lower than 20% can be shown in the table. According example, on sunny days, when the height was less than 100 m, and the o speed was less than 5, the wind speed biases of scheme ③ were less than 2 the wind speed was between 5 and 10, the wind speed bias of schemes ③ less than 20%, which indicates that the simulation effects of the PBL scheme   Figure 5 presents the model biases in the horizontal wind components for different horizontal speed levels. Generally, all the PBL schemes had mo horizontal wind speed smaller than 2 m·s −1 , and the biases in wind directi than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YS at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 showed the maximum model bias in wind speeds, particularly on haze and On windy days, the biases in wind direction were about 80° or even more heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the bi PBL schemes were within 20°. The MYJ scheme performed well in the wind lation, but overestimated the wind direction by about 280% below 300 m. A level of 5-10 m·s −1 , the biases in wind direction were over 100° for th MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy da wind speed was less than 5 m·s −1 , the wind direction biases for these PBL s more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, t standard deviation was large when the observed wind speeds exceeded 15 less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and di on sunny days, but the model results became worse on hazy and windy day days, the QNSE scheme led to standard deviations of wind directions at 300to 80°, or even more than 100°, while the other schemes had biases within 2 scheme well simulated the wind speed, but the variation of wind direction reached up to about 280%. The variations of wind directions when using th MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standar of wind direction were more than 180° at a height of 1500-2000 m. ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schem YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM shows the simulation effect of wind speed and direction in different wind spe (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny da wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-20 2000 m). For the convenience of comparison, the simulated height is consis horizontal height of the observation point. Therefore, the altitude here repres observed altitude and the simulated altitude. Additionally, only schemes with or direction biases lower than 20% can be shown in the table. According to example, on sunny days, when the height was less than 100 m, and the ob speed was less than 5, the wind speed biases of scheme ③ were less than 20 the wind speed was between 5 and 10, the wind speed bias of schemes ③ less than 20%, which indicates that the simulation effects of the PBL schemes   Figure 5 presents the model biases in the horizontal wind component for different horizontal speed levels. Generally, all the PBL schemes had m horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direc than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of Y at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 showed the maximum model bias in wind speeds, particularly on haze and On windy days, the biases in wind direction were about 80° or even mor heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the b PBL schemes were within 20°. The MYJ scheme performed well in the win lation, but overestimated the wind direction by about 280% below 300 m. A level of 5-10 m·s −1 , the biases in wind direction were over 100° for th MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased wi ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy d wind speed was less than 5 m·s −1 , the wind direction biases for these PBL more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL schem height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, standard deviation was large when the observed wind speeds exceeded 15 less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and d on sunny days, but the model results became worse on hazy and windy da days, the QNSE scheme led to standard deviations of wind directions at 300 to 80°, or even more than 100°, while the other schemes had biases within scheme well simulated the wind speed, but the variation of wind direction reached up to about 280%. The variations of wind directions when using MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standa of wind direction were more than 180° at a height of 1500-2000 m ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schem YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GB shows the simulation effect of wind speed and direction in different wind sp (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny d wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2 2000 m). For the convenience of comparison, the simulated height is consi horizontal height of the observation point. Therefore, the altitude here repre observed altitude and the simulated altitude. Additionally, only schemes wi or direction biases lower than 20% can be shown in the table. According example, on sunny days, when the height was less than 100 m, and the o speed was less than 5, the wind speed biases of scheme ③ were less than 2 the wind speed was between 5 and 10, the wind speed bias of schemes ③ less than 20%, which indicates that the simulation effects of the PBL scheme   , the biases in wind direction were over 100° for th MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased wi ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy d wind speed was less than 5 m·s −1 , the wind direction biases for these PBL more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL schem height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, standard deviation was large when the observed wind speeds exceeded 15 less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and d on sunny days, but the model results became worse on hazy and windy da days, the QNSE scheme led to standard deviations of wind directions at 300 to 80°, or even more than 100°, while the other schemes had biases within scheme well simulated the wind speed, but the variation of wind direction reached up to about 280%. The variations of wind directions when using MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standa of wind direction were more than 180° at a height of 1500-2000 m ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schem YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GB shows the simulation effect of wind speed and direction in different wind sp (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny d wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2 2000 m). For the convenience of comparison, the simulated height is consi horizontal height of the observation point. Therefore, the altitude here repre observed altitude and the simulated altitude. Additionally, only schemes wi or direction biases lower than 20% can be shown in the table. According example, on sunny days, when the height was less than 100 m, and the o speed was less than 5, the wind speed biases of scheme ③ were less than 2 the wind speed was between 5 and 10, the wind speed bias of schemes ③ less than 20%, which indicates that the simulation effects of the PBL scheme 1000-1500 -   Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.   , the biases in wind direction were over 100° for th MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased wi ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy d wind speed was less than 5 m·s −1 , the wind direction biases for these PBL more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL schem height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, standard deviation was large when the observed wind speeds exceeded 15 less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and d on sunny days, but the model results became worse on hazy and windy da days, the QNSE scheme led to standard deviations of wind directions at 300 to 80°, or even more than 100°, while the other schemes had biases within scheme well simulated the wind speed, but the variation of wind direction reached up to about 280%. The variations of wind directions when using MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standa of wind direction were more than 180° at a height of 1500-2000 m ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schem YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GB shows the simulation effect of wind speed and direction in different wind sp (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny d wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2 2000 m). For the convenience of comparison, the simulated height is consi horizontal height of the observation point. Therefore, the altitude here repre observed altitude and the simulated altitude. Additionally, only schemes wi or direction biases lower than 20% can be shown in the table. According example, on sunny days, when the height was less than 100 m, and the o speed was less than 5, the wind speed biases of scheme ③ were less than 2 the wind speed was between 5 and 10, the wind speed bias of schemes ③ less than 20%, which indicates that the simulation effects of the PBL scheme 1500-2000   Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.   . showed the maximum model bias in wind speeds, particularly on haze and wind On windy days, the biases in wind direction were about 80° or even more than heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases o PBL schemes were within 20°. The MYJ scheme performed well in the wind speed lation, but overestimated the wind direction by about 280% below 300 m. At wind level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with heig ticularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, w wind speed was less than 5 m·s −1 , the wind direction biases for these PBL scheme more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the sim standard deviation was large when the observed wind speeds exceeded 15 m·s −1 o less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction on sunny days, but the model results became worse on hazy and windy days. On days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m to 80°, or even more than 100°, while the other schemes had biases within 20°. T scheme well simulated the wind speed, but the variation of wind direction below reached up to about 280%. The variations of wind directions when using the YSU MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard dev of wind direction were more than 180° at a height of 1500-2000 m. In T ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; th YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The shows the simulation effect of wind speed and direction in different wind speed se (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, an 2000 m). For the convenience of comparison, the simulated height is consistent w horizontal height of the observation point. Therefore, the altitude here represents b observed altitude and the simulated altitude. Additionally, only schemes with wind or direction biases lower than 20% can be shown in the table. According to Tabl example, on sunny days, when the height was less than 100 m, and the observe speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ less than 20%, which indicates that the simulation effects of the PBL schemes were   Figure 5 presents the model biases in the for different horizontal speed levels. Generally horizontal wind speed smaller than 2 m·s −1 , a than 20°. On gentle windy days with observed reached up to 10 m·s −1 . On sunny days and haz at 1000-1500 m and 1500-2000 m, where the showed the maximum model bias in wind spe On windy days, the biases in wind direction w heights of 300-1000 m, 1000-1500 m, and 150 PBL schemes were within 20°. The MYJ schem lation, but overestimated the wind direction by level of 5-10 m·s −1 , the biases in wind dire MYNN2.5, MYNN3 and BouLac schemes. The ticularly when the observed wind speeds were wind speed was less than 5 m·s −1 , the wind di more than 180° at 1500-2000 m. Table 3 shows height and wind speed interval. At 1000-1500 m standard deviation was large when the observ less than 5 m·s −1 . The QNSE schemes gave a re on sunny days, but the model results became w days, the QNSE scheme led to standard deviati to 80°, or even more than 100°, while the othe scheme well simulated the wind speed, but th reached up to about 280%. The variations of w MYNN2.5, MYNN3 and BouLac schemes were m·s −1 . On hazy days, for wind speeds less than of wind direction were more than 180° at ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 dif YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, A shows the simulation effect of wind speed and (0-5, 5-10, 10-15, greater than 15) under three w wind) at different heights (below 100, 100-300, 2000 m). For the convenience of comparison, t horizontal height of the observation point. Ther observed altitude and the simulated altitude. A or direction biases lower than 20% can be sho example, on sunny days, when the height wa speed was less than 5, the wind speed biases of the wind speed was between 5 and 10, the win less than 20%, which indicates that the simulat   Figure 5 presents the model biases in the horizontal wind components at each layer for different horizontal speed levels. Generally, all the PBL schemes had model biases in horizontal wind speed smaller than 2 m·s −1 , and the biases in wind direction were less than 20°. On gentle windy days with observed wind speed less than 5 m·s −1 , the YSU bias reached up to 10 m·s −1 . On sunny days and hazy days, the model biases of YSU were large at 1000-1500 m and 1500-2000 m, where the wind speeds exceeded 15 m·s −1 . QNSE showed the maximum model bias in wind speeds, particularly on haze and windy days. On windy days, the biases in wind direction were about 80° or even more than 100° at heights of 300-1000 m, 1000-1500 m, and 1500-2000 m. Meanwhile, the biases of other PBL schemes were within 20°. The MYJ scheme performed well in the wind speed simulation, but overestimated the wind direction by about 280% below 300 m. At wind speed level of 5-10 m·s −1 , the biases in wind direction were over 100° for the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes. The model bias also increased with height, particularly when the observed wind speeds were less than 5 m·s −1 . On hazy days, when the wind speed was less than 5 m·s −1 , the wind direction biases for these PBL schemes were more than 180° at 1500-2000 m. Table 3 shows the biases of the PBL scheme for a specific height and wind speed interval. At 1000-1500 m and 1500-2000 m altitude, the simulated standard deviation was large when the observed wind speeds exceeded 15 m·s −1 or were less than 5 m·s −1 . The QNSE schemes gave a reasonable wind speed and direction value on sunny days, but the model results became worse on hazy and windy days. On windy days, the QNSE scheme led to standard deviations of wind directions at 300-2000 m of up to 80°, or even more than 100°, while the other schemes had biases within 20°. The MYJ scheme well simulated the wind speed, but the variation of wind direction below 300 m reached up to about 280%. The variations of wind directions when using the YSU, GFS, MYNN2.5, MYNN3 and BouLac schemes were over 100° in the wind speed level of 5-10 m·s −1 . On hazy days, for wind speeds less than 5 m·s −1 , the simulated standard deviations of wind direction were more than 180° at a height of 1500-2000 m. In Table 3, ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different boundary layer schemes; these are YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2, BouLac, UW, SH, GBM. The figure shows the simulation effect of wind speed and direction in different wind speed segments (0-5, 5-10, 10-15, greater than 15) under three weather conditions (sunny day, fog, strong wind) at different heights (below 100, 100-300, 300-1000, 1000-1500, 1500-2000, and over 2000 m). For the convenience of comparison, the simulated height is consistent with the horizontal height of the observation point. Therefore, the altitude here represents both the observed altitude and the simulated altitude. Additionally, only schemes with wind speed or direction biases lower than 20% can be shown in the table. According to Table 3, for example, on sunny days, when the height was less than 100 m, and the observed wind speed was less than 5, the wind speed biases of scheme ③ were less than 20%, and when the wind speed was between 5 and 10, the wind speed bias of schemes ③ and ⑨ were less than 20%, which indicates that the simulation effects of the PBL schemes were better.   Figure 5 presents the model biases in the horizo for different horizontal speed levels. Generally, all th horizontal wind speed smaller than 2 m·s −1 , and th than 20°. On gentle windy days with observed wind reached up to 10 m·s −1 . On sunny days and hazy days at 1000-1500 m and 1500-2000 m, where the win showed the maximum model bias in wind speeds, p On windy days, the biases in wind direction were a heights of 300-1000 m, 1000-1500 m, and 1500-200 PBL schemes were within 20°. The MYJ scheme perf lation, but overestimated the wind direction by abou level of 5-10 m·s −1 , the biases in wind direction MYNN2.5, MYNN3 and BouLac schemes. The mode ticularly when the observed wind speeds were less t wind speed was less than 5 m·s −1 , the wind direction more than 180° at 1500-2000 m. Table 3 shows the bi height and wind speed interval. At 1000-1500 m and standard deviation was large when the observed wi less than 5 m·s −1 . The QNSE schemes gave a reasona on sunny days, but the model results became worse days, the QNSE scheme led to standard deviations of to 80°, or even more than 100°, while the other sche scheme well simulated the wind speed, but the vari reached up to about 280%. The variations of wind d MYNN2.5, MYNN3 and BouLac schemes were over m·s −1 . On hazy days, for wind speeds less than 5 m·s of wind direction were more than 180° at a he ①②③④⑤⑥⑦⑧⑨⑩⑪ represent 11 different YSU, MYJ, GFS, QNSE, MYNN2.5, MYNN3, ACM2 shows the simulation effect of wind speed and direct (0-5, 5-10, 10-15, greater than 15) under three weath wind) at different heights (below 100, 100-300, 300-1 2000 m). For the convenience of comparison, the sim horizontal height of the observation point. Therefore observed altitude and the simulated altitude. Additio or direction biases lower than 20% can be shown in example, on sunny days, when the height was less speed was less than 5, the wind speed biases of schem the wind speed was between 5 and 10, the wind spe less than 20%, which indicates that the simulation ef In Figure 6, a comparison is made between the wind field observed near the ground and the simulated wind field with two PBL schemes under the same conditions, with a wind speed of 5-10 m·s −1 on sunny days. Figure 7 shows a comparison between different wind speeds and height schemes under three weather conditions. Better results for the scheme simulations are presented. We can see from the chart that the wind direction and wind speed simulations cover the observation results, but there were still biases, sometimes up to 45 • -60 • .

>2000
-①③⑥⑦⑧⑩⑪ ④ ②⑨⑪ In Figure 6, a comparison is made between the wind field observed near the ground and the simulated wind field with two PBL schemes under the same conditions, with a wind speed of 5-10 m·s −1 on sunny days. Figure 7 shows a comparison between different wind speeds and height schemes under three weather conditions. Better results for the scheme simulations are presented. We can see from the chart that the wind direction and wind speed simulations cover the observation results, but there were still biases, sometimes up to 45°-60°. Figure 6. The model biases in wind speed (left, bias less than 2 m·s −1 ) and wind direction (right, bias less than 20°) depending on the PBL schemes, the layer heights and the wind speeds on sunny, haze and windy days.   In Figure 6, a comparison is made between the wind field observed near the ground and the simulated wind field with two PBL schemes under the same conditions, with a wind speed of 5-10 m·s −1 on sunny days. Figure 7 shows a comparison between different wind speeds and height schemes under three weather conditions. Better results for the scheme simulations are presented. We can see from the chart that the wind direction and wind speed simulations cover the observation results, but there were still biases, sometimes up to 45°-60°. Figure 6. The model biases in wind speed (left, bias less than 2 m·s −1 ) and wind direction (right, bias less than 20°) depending on the PBL schemes, the layer heights and the wind speeds on sunny, haze and windy days.  Obs stands for observation wind field, the GFS scheme simulates the wind field, with wind speed and wind direction bias of 0.68 m·s −1 and 9.8 • , respectively, the BouLac scheme simulates wind field, with wind speed and wind direction biases of −1.1 m·s −1 , 0.8 • . Figure 8 exhibits the Taylor chart for the model results at different heights and wind speeds when the observed wind speed is at 0-5 m·s −1 . The Taylor charts show similar characteristics to the other observed wind speeds (i.e., 5-10, 10-15 and >15 m·s −1 ). The correlation coefficients that failed to pass the significance test with the significance level of 0.05 are not shown in the figure. The horizontal and vertical coordinates represent the ratio of the standard deviation of the simulated value to the standard deviation of the observed value. A ratio of 1 indicates that the standard deviation was perfect. The gray arc represents the isoline with equal distance between each point and the point with a standard deviation of 1. In the left and right columns of the figure, 'spd' in the lower left corner stands for the comparison of wind speed between the simulated value and the observed value, and 'dir' represents the comparison of wind direction. Obs represents the actual wind speed range of the analysis data in the graph. The cases with coefficients that failed to pass the significance test on the three different kinds of days do not appear in the figures. stands for the comparison of wind speed between the simulated value and the observed value, and 'dir' represents the comparison of wind direction. Obs represents the actual wind speed range of the analysis data in the graph. The cases with coefficients that failed to pass the significance test on the three different kinds of days do not appear in the figures. As can be seen from Figure 8, each wind speed segment could have suitable simulation schemes for each height. Biases and standard deviation should also be considered comprehensively. For example, when the Obs was 5-10 m·s −1 , the standard deviation at 100-300 m was approximately 20 times higher than the observation standard deviation. The correlation at 300-1000 m was approximately as weak as 0.1-0.2, while at 1000-1500 m, there was the non-pass hypothesis test. On windy days, when Obs was 0-5 m·s −1 , the simulated value of wind speed was several times the standard deviation of the observed value, and the bias value was greater than 100%.

Classical PBL Schemes
As is shown in Section 1, many previous studies have indicated that YSU, MYJ, ACM2 showed good simulation results. In this study, the PBL conditions changed with the weather evolution, and they were not always stable or unstable. On windy days, with an observed wind speed of 5-10 m·s −1 and at a height greater than 300 m, the YSU bias of wind speed was 50-70%. On sunny days, when the observed wind speed was less than 5 m·s −1 , the MYJ mean bias of wind speed was within the range of 60-290%. A few studies have claimed that the QNSE scheme is suitable in stable conditions, which was also proved in our results. We found that the QNSE scheme performed poorly on windy days, Figure 8. Wind field comparison chart, the observed wind field and simulated wind field with several PBL schemes under different conditions. (a) On sunny days, at a height of 300-1000 m, 5 < Obs <10 m·s −1 , (b) On hazy days, at a height of 300-1000 m, 10 < Obs < 15 m·s −1 , (c) On windy days, at a height of 1000-1500 m, 10 < Obs < 15 m·s −1 .
As can be seen from Figure 8, each wind speed segment could have suitable simulation schemes for each height. Biases and standard deviation should also be considered comprehensively. For example, when the Obs was 5-10 m·s −1 , the standard deviation at 100-300 m was approximately 20 times higher than the observation standard deviation. The correlation at 300-1000 m was approximately as weak as 0.1-0.2, while at 1000-1500 m, there was the non-pass hypothesis test. On windy days, when Obs was 0-5 m·s −1 , the simulated value of wind speed was several times the standard deviation of the observed value, and the bias value was greater than 100%.

Classical PBL Schemes
As is shown in Section 1, many previous studies have indicated that YSU, MYJ, ACM2 showed good simulation results. In this study, the PBL conditions changed with the weather evolution, and they were not always stable or unstable. On windy days, with an observed wind speed of 5-10 m·s −1 and at a height greater than 300 m, the YSU bias of wind speed was 50-70%. On sunny days, when the observed wind speed was less than 5 m·s −1 , the MYJ mean bias of wind speed was within the range of 60-290%. A few studies have claimed that the QNSE scheme is suitable in stable conditions, which was also proved in our results. We found that the QNSE scheme performed poorly on windy days, but showed better results on sunny days and hazy days, especially for the observed wind speed exceeding 5 m·s −1 at layers above 2000 m. The above performances further prove that a scheme cannot be fully suitable for certain weather conditions. The YSU and MYJ schemes, widely applied in previous studies, also presented good performances in our studies. The YSU scheme may be a good choice under the following conditions: to simulate the surface wind direction for observed wind speeds stronger than 5 m·s −1 , or to simulate the wind direction above 300 m on sunny and hazy days, and perhaps to simulate wind speed below 300 m on windy days. It can also be used to simulate the wind direction above 300 m, the wind speed simulation above 1000 m, the wind speed simulation of over 15 m·s −1 , and the simulation of wind direction at 5-15 m·s −1 .
The MYJ scheme was considered suitable for the following conditions. For example, to simulate wind speed below 300 m when the wind speed is more than 5 m·s −1 on sunny days, or to simulate the winds at 300-1000 m, and perhaps to simulate the wind direction when the height is greater than 1000 m, maybe also on windy days when the wind speed is within the range 10-15 m·s −1 and the altitude is greater than 2000 m. Additionally, the MYJ scheme is able to well capture both wind speed and direction on hazy days when the wind speed is 10-15 m·s −1 at 300-1000 m.
In other words, suitable PBL schemes should be chosen for different conditions. In this case, on sunny days, when Obs was 0-5 m·s −1 , we found that the wind speed was simulated well at the height 100-300 m, and the wind direction simulation performed well at 300-1000 m. When the Obs was 5-10 m·s −1 , the wind speed at 100-300 m was better than at 300-1000 m. When the Obs was 10-15 m·s −1 , the wind speed data were mainly distributed in the upper 1000 m; while little data at 1000-2000 m satisfied the hypothesis test, many data satisfied hypothesis test at heights above 2000 m. At this altitude, schemes 7 and 12 can be used. Wind speeds greater than 15 m·s −1 were mainly distributed at heights above 1500 m, and schemes 2, 4, 7 and 11 could be selected. On hazy days, when the height was above 1000 m, the simulation results of several schemes were better. When the Obs was less than 5 m·s −1 and the height was 1000-1500 m, the wind direction could be simulated with PBL schemes 2 and 3, and the wind speed simulation at 300-1000 m was relatively good. Above 2000 m, the simulation results could not be verified completely due to limited observation data. It turns out that no PBL scheme always shows good performances. Figure 9 shows the observation and the simulated vertical wind speeds with three PBL schemes according to the observed vertical wind field. On sunny days and hazy days, the simulated wind speed values were 10% of the observation value, and the wind speed was mostly distributed between 0 and 0.5 under the boundary layer, and the wind direction was vertical downward. However, the simulation results show that the wind direction was mainly vertical upward. On the windy days from 28 February to 1 March, there was strong upward turbulence from the surface to the upper air in the vertical direction, and the maximum wind speed was more than 0.5 m·s −1 . The model failed to capture the change in vertical wind speeds (Figure 10), not only as a consequence of the model's uncertainty, but also potentially due to the biases in the DWL data. It is known that, under a clear sky, the updraft and downdraft of airflow are small. The turbulence echo approached the detection limit of the Doppler LiDAR, which makes an accurate extraction of vertical wind speed difficult. The model failed to capture the change in vertical wind speeds (Figure 10), not only as a consequence of the model's uncertainty, but also potentially due to the biases in the DWL data. It is known that, under a clear sky, the updraft and downdraft of airflow are small. The turbulence echo approached the detection limit of the Doppler LiDAR, which makes an accurate extraction of vertical wind speed difficult. Figure 9. Taylor charts of mean bias, correlation coefficients and standard deviations for the model results with 11 PBL schemes. On (a) sunny days, (b) hazy days, and (c) windy days, with the observed wind speed at 0-5 m·s -1 .

Vertical Wind Component in PBL
The model failed to capture the change in vertical wind speeds (Figure 10), not only as a consequence of the model's uncertainty, but also potentially due to the biases in the DWL data. It is known that, under a clear sky, the updraft and downdraft of airflow are small. The turbulence echo approached the detection limit of the Doppler LiDAR, which makes an accurate extraction of vertical wind speed difficult.

Conclusions
In this study, the accuracy of the vertical wind field simulation for different boundary layer schemes was systematically evaluated using high-resolution wind Doppler LiDAR for the first time, with a typical process simulated by a WRF model in Beijing. The results showed that the wind field was simulated well at a height of 1000-2000 m, as most of the relative mean biases of wind speed and wind direction were less than 20% and 6%, respectively. Below 1000 m, the wind speed and direction biases ranged from about 30% to more than 150% m·s −1 and 6-30%, respectively. The relative mean bias of the simulated wind profile was up to 50-300% when the wind speed was lower than 5 m·s −1 in the boundary layer. As the wind speed range was 10-15 m·s −1 , the model results were better than for other speeds, and were better when the height was above 1000 m. The PBL schemes have different capabilities to reproduce the changes of wind speed profiles under different weather conditions. An appropriate PBL scheme is dependent on the weather conditions, and the model biases showed substantial changes at different heights and in different wind speed ranges, and some PBL schemes were not always likely to be suitable for a certain weather condition. The influence of observation height on the assessment was larger than that due to employing the different PBL schemes. This study provides a reference for further improving the development and use of wind energy and the accuracy of complex wind field predictions.

Conclusions
In this study, the accuracy of the vertical wind field simulation for different boundary layer schemes was systematically evaluated using high-resolution wind Doppler LiDAR for the first time, with a typical process simulated by a WRF model in Beijing. The results showed that the wind field was simulated well at a height of 1000-2000 m, as most of the relative mean biases of wind speed and wind direction were less than 20% and 6%, respectively. Below 1000 m, the wind speed and direction biases ranged from about 30% to more than 150% m·s −1 and 6-30%, respectively. The relative mean bias of the simulated wind profile was up to 50-300% when the wind speed was lower than 5 m·s −1 in the boundary layer. As the wind speed range was 10-15 m·s −1 , the model results were better than for other speeds, and were better when the height was above 1000 m. The PBL schemes have different capabilities to reproduce the changes of wind speed profiles under different weather conditions. An appropriate PBL scheme is dependent on the weather conditions, and the model biases showed substantial changes at different heights and in different wind speed ranges, and some PBL schemes were not always likely to be suitable for a certain weather condition. The influence of observation height on the assessment was larger than that due to employing the different PBL schemes. This study provides a reference for further improving the development and use of wind energy and the accuracy of complex wind field predictions.