Analysis of Boundary Layer Height Calculation Methods Based on Boundary Layer Events over Yongxing Island

The planetary boundary layer (BL) height and stratification are key parameters in determining the exchange of heat, momentum, moisture and trace gases between the surface and the free troposphere. Numerous different methods have been used to quantify the BL height and these methods have been applied to a wide variety of observational data sets obtained from different instruments and to numerical model output. We investigate the BL height at the Hyytiälä SMEAR II station in southern Finland diagnosed from radiosonde observations, a microwave radiometer (MWR) and ERA5 reanalysis. Four different algorithms are used to diagnose the BL height from the radiosondes. The diagnosed BL height is sensitive to the method used and the level of agreement, and the sign of systematic bias, between the 4 different methods depends on the surface-layer stability. For example, for very unstable situations, the median BL height diagnosed from the radiosondes varies from 600 m to 1500 m depending on which method is applied. Good agreement between the BL height in ERA5 and diagnosed from the radiosondes using Richardson number-based methods is found for almost all stability classes, suggesting that ERA5 has adequate vertical resolution near the surface to resolve the BL structure. However, ERA5 overestimates the BL height in very stable conditions highlighting the on-going challenge for numerical models to correctly resolve the stable BL. Furthermore, ERA5 BL height differs most from the radiosondes at 18 UTC suggesting ERA5 does not resolve the evening transition correctly. This study has also shown that BL height estimates from the MWR are reliable in unstable situations but often are inaccurate under stable conditions when, in comparison to ERA5 BL heights, they are much deeper. The errors in the MWR BL height estimates originate from the limitations of the manufacturers algorithm for stable conditions and also the mis-identification of the type of BL. A climatology of the annual and diurnal cycle of BL height and observed surface layer stability was created. The shallowest (353 m) monthly median BL height occurs in February and the deepest (576 m) in June. In winter there is no diurnal cycle in BL height, unstable BLs are rare yet so are very stable BLs. The shallowest BLs occur at night in spring and summer and very stable conditions are most common at night in the warm season. Finally, using ERA5 gridded data we determined that the BL height observed at Hyytiälä is representative of most land areas in southern and central Finland. However, the spatial variability of the BL height is largest during daytime in summer reducing the area over which BL height observations from Hyytiälä would be representative of.

The planetary boundary layer (BL) height and stratification are key parameters in determining the exchange of heat, momentum, moisture and trace gases between the surface and the free troposphere. Numerous different methods have been used to quantify the BL height and these methods have been applied to a wide variety of observational data sets obtained from different instruments and to numerical model output. We investigate the BL height at the Hyytiälä SMEAR II station in southern Finland diagnosed from radiosonde observations, a microwave radiometer (MWR) and ERA5 reanalysis. Four different algorithms are used to diagnose the BL height from the radiosondes. The diagnosed BL height is sensitive to the method used and the level of agreement, and the sign of systematic bias, between the 4 different methods depends on the surface-layer stability. For example, for very unstable situations, the median BL height diagnosed from the radiosondes varies from 600 m to 1500 m depending on which method is applied. Good agreement between the BL height in ERA5 and diagnosed from the radiosondes using Richardson number-based methods is found for almost all stability classes, suggesting that ERA5 has adequate vertical resolution near the surface to resolve the BL structure. However, ERA5 overestimates the BL height in very stable conditions highlighting the on-going challenge for numerical models to correctly resolve the stable BL. Furthermore, ERA5 BL height differs most from the radiosondes at 18 UTC suggesting ERA5 does not resolve the evening transition correctly. This study has also shown that BL height estimates from the MWR are reliable in unstable situations but often are inaccurate under stable conditions when, in comparison to ERA5 BL heights, they are much deeper. The errors in the MWR BL height estimates originate from the limitations of the manufacturers algorithm for stable conditions and also the mis-identification of the type of BL. A climatology of the annual and diurnal cycle of BL height and observed surface layer stability was created. The shallowest (353 m) monthly median BL height occurs in February and the deepest (576 m) in June. In winter there is no diurnal cycle in BL height, unstable BLs are rare yet so are very stable BLs. The shallowest BLs occur at night in spring and summer and very stable conditions are most common at night in the warm season. Finally, using ERA5 gridded data we determined that the BL height observed at Hyytiälä is representative of most land areas in southern and central Finland. However, the spatial variability of the BL height is largest during daytime in summer reducing the area over which BL height observations from Hyytiälä would be representative of.

The planetary boundary layer (BL) height and stratification are key parameters in determining the exchange of heat, momentum, moisture and trace gases between the surface and the free troposphere. Numerous different methods have been used to quantify the BL height and these methods have been applied to a wide variety of observational data sets obtained from different instruments and to numerical model output. We investigate the BL height at the Hyytiälä SMEAR II station in southern Finland diagnosed from radiosonde observations, a microwave radiometer (MWR) and ERA5 reanalysis. Four different algorithms are used to diagnose the BL height from the radiosondes. The diagnosed BL height is sensitive to the method used and the level of agreement, and the sign of systematic bias, between the 4 different methods depends on the surface-layer stability. For example, for very unstable situations, the median BL height diagnosed from the radiosondes varies from 600 m to 1500 m depending on which method is applied. Good agreement between the BL height in ERA5 and diagnosed from the radiosondes using Richardson number-based methods is found for almost all stability classes, suggesting that ERA5 has adequate vertical resolution near the surface to resolve the BL structure. However, ERA5 overestimates the BL height in very stable conditions highlighting the on-going challenge for numerical models to correctly resolve the stable BL. Furthermore, ERA5 BL height differs most from the radiosondes at 18 UTC suggesting ERA5 does not resolve the evening transition correctly. This study has also shown that BL height estimates from the MWR are reliable in unstable situations but often are inaccurate under stable conditions when, in comparison to ERA5 BL heights, they are much deeper. The errors in the MWR BL height estimates originate from the limitations of the manufacturers algorithm for stable conditions and also the mis-identification of the type of BL. A climatology of the annual and diurnal cycle of BL height and observed surface layer stability was created. The shallowest (353 m) monthly median BL height occurs in February and the deepest (576 m) in June. In winter there is no diurnal cycle in BL height, unstable BLs are rare yet so are very stable BLs. The shallowest BLs occur at night in spring and summer and very stable conditions are most common at night in the warm season. Finally, using ERA5 gridded data we determined that the BL height observed at Hyytiälä is representative of most land areas in southern and central Finland. However, the spatial variability of the BL height is largest during daytime in summer reducing the area over which BL height observations from Hyytiälä would be representative of.

The planetary boundary layer (BL) height and stratification are key parameters in determining the exchange of heat, momentum, moisture and trace gases between the surface and the free troposphere. Numerous different methods have been used to quantify the BL height and these methods have been applied to a wide variety of observational data sets obtained from different instruments and to numerical model output. We investigate the BL height at the Hyytiälä SMEAR II station in southern Finland diagnosed from radiosonde observations, a microwave radiometer (MWR) and ERA5 reanalysis. Four different algorithms are used to diagnose the BL height from the radiosondes. The diagnosed BL height is sensitive to the method used and the level of agreement, and the sign of systematic bias, between the 4 different methods depends on the surface-layer stability. For example, for very unstable situations, the median BL height diagnosed from the radiosondes varies from 600 m to 1500 m depending on which method is applied. Good agreement between the BL height in ERA5 and diagnosed from the radiosondes using Richardson number-based methods is found for almost all stability classes, suggesting that ERA5 has adequate vertical resolution near the surface to resolve the BL structure. However, ERA5 overestimates the BL height in very stable conditions highlighting the on-going challenge for numerical models to correctly resolve the stable BL. Furthermore, ERA5 BL height differs most from the radiosondes at 18 UTC suggesting ERA5 does not resolve the evening transition correctly. This study has also shown that BL height estimates from the MWR are reliable in unstable situations but often are inaccurate under stable conditions when, in comparison to ERA5 BL heights, they are much deeper. The errors in the MWR BL height estimates originate from the limitations of the manufacturers algorithm for stable conditions and also the mis-identification of the type of BL. A climatology of the annual and diurnal cycle of BL height and observed surface layer stability was created. The shallowest (353 m) monthly median BL height occurs in February and the deepest (576 m) in June. In winter there is no diurnal cycle in BL height, unstable BLs are rare yet so are very stable BLs. The shallowest BLs occur at night in spring and summer and very stable conditions are most common at night in the warm season. Finally, using ERA5 gridded data we determined that the BL height observed at Hyytiälä is representative of most land areas in southern and central Finland. However, the spatial variability of the BL height is largest during daytime in summer reducing the area over which BL height observations from Hyytiälä would be representative of.

There is a deep atmospheric boundary layer on the Tibetan Plateau (TP) that has always been of interest to researchers. The variation in the atmospheric boundary layer under the influence of the southern branch of the westerly wind and that of the Asian monsoon was analyzed using sounding data collected in 2014 and 2019. Then, the hourly high-resolution comprehensive observation data for the land-atmosphere interaction on the TP and the ERA5 reanalysis data were used to study the influence of the atmospheric boundary layer’s structure in Mount Everest, Nyingchi, Nam Co, Nagqu, and Shiquan River regions. The results show that the height of the convective boundary layer observed at the Mount Everest, Nyingchi, Nam Co, Nagqu, and Shiquan River stations on the TP under the influence of the southern branch of the westerly wind was higher than that during the Asian monsoon season. The height of the convective boundary layer in the Shiquan River area was often highest at 20:00. The structure of the boundary layer in the Mount Everest area was often affected by the westerly jets and glacial winds. The inversion layer developed earlier in the Nyingchi area than at the other stations. The height of the boundary layer was positively correlated with the sensible heat flux and negatively correlated with the latent heat flux. The vertical velocity in the atmospheric boundary layer in the Nyingchi area decreased, which may be one of the reasons why the height of the convective boundary layer was lower in this area than at the other stations and humidity inversion often occurred in this area.

There is a deep atmospheric boundary layer on the Tibetan Plateau (TP) that has always been of interest to researchers. The variation in the atmospheric boundary layer under the influence of the southern branch of the westerly wind and that of the Asian monsoon was analyzed using sounding data collected in 2014 and 2019. Then, the hourly high-resolution comprehensive observation data for the land-atmosphere interaction on the TP and the ERA5 reanalysis data were used to study the influence of the atmospheric boundary layer’s structure in Mount Everest, Nyingchi, Nam Co, Nagqu, and Shiquan River regions. The results show that the height of the convective boundary layer observed at the Mount Everest, Nyingchi, Nam Co, Nagqu, and Shiquan River stations on the TP under the influence of the southern branch of the westerly wind was higher than that during the Asian monsoon season. The height of the convective boundary layer in the Shiquan River area was often highest at 20:00. The structure of the boundary layer in the Mount Everest area was often affected by the westerly jets and glacial winds. The inversion layer developed earlier in the Nyingchi area than at the other stations. The height of the boundary layer was positively correlated with the sensible heat flux and negatively correlated with the latent heat flux. The vertical velocity in the atmospheric boundary layer in the Nyingchi area decreased, which may be one of the reasons why the height of the convective boundary layer was lower in this area than at the other stations and humidity inversion often occurred in this area.

There is a deep atmospheric boundary layer on the Tibetan Plateau (TP) that has always been of interest to researchers. The variation in the atmospheric boundary layer under the influence of the southern branch of the westerly wind and that of the Asian monsoon was analyzed using sounding data collected in 2014 and 2019. Then, the hourly high-resolution comprehensive observation data for the land-atmosphere interaction on the TP and the ERA5 reanalysis data were used to study the influence of the atmospheric boundary layer’s structure in Mount Everest, Nyingchi, Nam Co, Nagqu, and Shiquan River regions. The results show that the height of the convective boundary layer observed at the Mount Everest, Nyingchi, Nam Co, Nagqu, and Shiquan River stations on the TP under the influence of the southern branch of the westerly wind was higher than that during the Asian monsoon season. The height of the convective boundary layer in the Shiquan River area was often highest at 20:00. The structure of the boundary layer in the Mount Everest area was often affected by the westerly jets and glacial winds. The inversion layer developed earlier in the Nyingchi area than at the other stations. The height of the boundary layer was positively correlated with the sensible heat flux and negatively correlated with the latent heat flux. The vertical velocity in the atmospheric boundary layer in the Nyingchi area decreased, which may be one of the reasons why the height of the convective boundary layer was lower in this area than at the other stations and humidity inversion often occurred in this area.

<strong class="journal-contentHeaderColor">Abstract.</strong> There is a deep atmospheric boundary layer on the Tibetan Plateau (TP) that has always been of interest to researchers. The variation in the atmospheric boundary layer under the influence of the southern branch of the westerly wind and that of the Asian monsoon was analyzed using sounding data collected in 2014 and 2019. Then, the hourly high-resolution comprehensive observation data for the land-atmosphere interaction on the TP and the ERA5 reanalysis data were used to study the influence of the atmospheric boundary layer&rsquo;s structure in Mount Everest, Nyingchi, Nam Co, Nagqu, and Shiquan River regions. The results show that the height of the convective boundary layer observed at the Mount Everest, Nyingchi, Nam Co, Nagqu, and Shiquan River stations on the TP under the influence of the southern branch of the westerly wind was higher than that during the Asian monsoon season. The height of the convective boundary layer in the Shiquan River area was often highest at 20:00. The structure of the boundary layer in the Mount Everest area was often affected by the westerly jets and glacial winds. The inversion layer developed earlier in the Nyingchi area than at the other stations. The height of the boundary layer was positively correlated with the sensible heat flux and negatively correlated with the latent heat flux. The vertical velocity in the atmospheric boundary layer in the Nyingchi area decreased, which may be one of the reasons why the height of the convective boundary layer was lower in this area than at the other stations and humidity inversion often occurred in this area.

There is a deep atmospheric boundary layer on the Tibetan Plateau (TP) that has always been of interest to researchers. The variation in the atmospheric boundary layer under the influence of the southern branch of the westerly wind and that of the Asian monsoon was analyzed using sounding data collected in 2014 and 2019. Then, the hourly high-resolution comprehensive observation data for the land-atmosphere interaction on the TP and the ERA5 reanalysis data were used to study the influence of the atmospheric boundary layer’s structure in Mount Everest, Nyingchi, Nam Co, Nagqu, and Shiquan River regions. The results show that the height of the convective boundary layer observed at the Mount Everest, Nyingchi, Nam Co, Nagqu, and Shiquan River stations on the TP under the influence of the southern branch of the westerly wind was higher than that during the Asian monsoon season. The height of the convective boundary layer in the Shiquan River area was often highest at 20:00. The structure of the boundary layer in the Mount Everest area was often affected by the westerly jets and glacial winds. The inversion layer developed earlier in the Nyingchi area than at the other stations. The height of the boundary layer was positively correlated with the sensible heat flux and negatively correlated with the latent heat flux. The vertical velocity in the atmospheric boundary layer in the Nyingchi area decreased, which may be one of the reasons why the height of the convective boundary layer was lower in this area than at the other stations and humidity inversion often occurred in this area.

In this paper, we propose a new method of numerical differentiation to determine the height of the top layer of the atmospheric boundary layer. In this method, a regularization technique is used to convert the problem of calculating the differential of the curve of the corners into the problem of finding the minimum value of the objective function. The two-parameter model function method is used to select the regularization parameters. Finally, the maximum gradient method is used to determine the top height of the boundary layer. Firstly, the effectiveness of the new method is validated through two numerical experiments. The experimental results show that as the noise of the occultation data increases, the fluctuation of the height of the boundary layer top obtained by the difference method and the numerical differentiation method combined with the L curve scheme increases. And the height obtained by the two-parameter model function method is very stable, which shows that the new method can filter the noise well, thereby retaining the main information about the profile. Then, based on the COSMIC angle data in January, April, July and October 2007－2011, the new method is used to analyze the seasonal characteristics of the height of the global oceanic and atmospheric boundary layer, compared with the seasonal distribution obtained by “zbalmax” with the occultation data. The results show that the seasonal distribution characteristics of the two data are very consistent: the height of the boundary layer is higher in the area where the sea surface temperature is higher than that in the surrounding sea area; on the contrary, the height of the boundary layer top is lower. In the sea area where the warm current passes, the height of the boundary layer is higher; in the sea area where the cold current passes, the height of the boundary layer is lower.

The boundary-layer height and stability are two key parameters that control the exchange of energy between the surface and the atmosphere and strongly influence air quality and pollution dispersion. In this study, we investigate the boundary layer (BL) height and stability at the long-term measurement station of Hyyti&amp;#228;l&amp;#228;, located in the Boreal forest of southern Finland at a latitude of 61.85N. A 41-year climatology of the annual and diurnal cycle of BL height was created based on ERA5 reanalysis data. The ability of ERA5 to correctly capture the BL height was determined by comparing ERA5 to BL heights derived from 847 radiosondes that were released from Hyyti&amp;#228;l&amp;#228; as part of the 7.5 month &amp;#8220;Biogenic Aerosols - Effects on Clouds and Climate&amp;#8221; (BAECC) campaign in 2014. Four different methods to estimate the BL height were applied to the radiosondes. A 25-year climatology of surface-layer stability was created based on eddy covariance measurements and was used to identified under which conditions ERA5 can best capture the BL height and to better understand the annual and diurnal cycle of the BL height. The climatology results show that the shallowest (353~m) monthly median BL height occurs in February and the deepest (576~m) in June. The largest variability in BL height, and the largest diurnal range, was found in April and May. Notably, the shallowest BLs were found to occur at night in spring and summer which is also when very stable conditions were most likely to occur. Between November and February, there was no diurnal cycle in BL height due to the limited solar radiation at this time of year. Unstable conditions were rare during the cold season but so were very stable BLs. The absence of very stable conditions in winter is related to the stronger winds, and hence more shear-driven turbulence, compared to either spring of summer. Very shallow and stable BLs are also prevented from developing in autumn and winter due to the increased amount of cloud compared to spring and summer. Good agreement was found between the BL height in ERA5 and the BL height diagnosed from the radiosondes for almost all stability classes but ERA5 does overestimates the BL height in very stable conditions. In addition, ERA5 BL height differs most from the radiosondes at 18 UTC. These results suggest that ERA5 has adequate vertical resolution to correctly resolve the BL height in most conditions, that ERA5 struggles to correctly simulated stable BLs, and lastly that ERA5 does not resolve the evening transition correctly.&amp;#160;&amp;#160;&amp;#160;&amp;#160;

The thermodynamic structure of the lower troposphere over the Southern Ocean is analysed by employing over 16 years of high resolution upper air soundings from Macquarie Island (54.62 S, 158.85 E). The soundings are analysed to develop an understanding of the structure of the boundary layer and wind shear occurring through the lower levels over this region, and to compare this to European Centre for Medium-Range Weather Forecasts (ECMWF) model level reanalysis data for the Year of Tropical Convection (YOTC). A multiple layered structure is commonly observed in the high resolution soundings, and is also observed in YOTC, but with a lower frequency. The climatological mean and variability of a number of variables are calculated for both data sets, which reveals that YOTC performs well, but has weaknesses in modelling the observed moisture and wind fields, particularly evident in wind shear profiles. A distinction between a number of boundary layer types is made, and the frequency with which they occur is quantified for both data sets. Proxy cloud fields are constructed for the two data sets, and these suggest that clouds are commonly observed in a region between the top of the boundary layer and a secondary temperature inversion. An examination of the wind shear across the cloud boundaries finds wind shear over cloud base occurs more frequently than cloud top, suggesting that the cloud fields are not embedded in a well-mixed boundary layer. Next, an attempt to generalise these results to a broad region across the Southern Ocean is made using the Constellation Observing System for Meteorology, Ionosphere, and climate (COSMIC) Global Positioning System (GPS) Radio Occultation (RO) observations. A direct comparison of temporally and spatially co-located COSMIC profiles and radiosonde profiles from Macquarie Island shows the performance of COSMIC is variable. COSMIC often struggles to reproduce the profiles over strong inversions in temperature or large changes in moisture, and the height and occurrence of the boundary layer, as well as any decoupled layers, rarely agree between the two data sets. A statistical analysis is performed on a large set of COSMIC profiles in the vicinity of Macquarie Island, and shows COSMIC reproduces the height of the boundary layer and decoupled layers well, but the frequency is underestimated. The analysis is extended to a large region of the Southern Ocean to investigate any spatial patterns in the height of the layers. There is a north-south gradient in the height of the boundary layer, as well as the frequency of occurrence of the boundary layer. Decoupling of the boundary layer is found to be a frequent and wide spread feature of the Southern Ocean. Next, the WRF model is used to simulate the boundary layer over the ocean south of Tasmania during a period of observed decoupling. A variety of model runs are performed to investigate the performance of three common PBL schemes. Other parameters investigated include increasing the vertical resolution, and the effect of varying the model initial conditions through 3D Variational data assimilation. An extensive model evaluation reveals the WRF model rarely captures main or secondary temperature inversions in the lowest few kilometers with the strength or frequency of in-situ observations. In reproducing the thermodynamics, the 3D Variational data assimilation model run performs the best. The YSU PBL scheme consistently performs best at simulating the Southern Ocean boundary layer and the associated clouds, and the benefit of improving the model initial conditions through data assimilation is significant. Finally, an analysis of trends in the wind over Macquarie Island is performed with a radiosonde database spanning nearly four decades. The results indicate that the surface wind speed is increasing, with the trend for the upper levels being less well defined. The surface wind is highly correlated with the upper level winds, and the wind at all levels are moderately correlated with the Southern Annular Mode. ECMWF ERA-Interim reanalysis data shows significant trends in wind speed over several levels, however slightly smaller than trends in the soundings over a similar time period. The correlations in ERA-Interim are similar to those in the soundings. A clustering analysis of the wind reveals four distinct regimes, with a trend towards a regime characterised by strong north westerly winds.

The height of the atmospheric boundary layer is derived with the help of two different measuring systems and methods. From radiosoundings the boundary layer height is determined by the parcel method and by temperature and humidity gradients. From lidar backscatter measurements a combination of the averaging variance method and the high-resolution gradient method is used to determine boundary layer heights. In this paper lidar-derived boundary layer heights on a 10 min basis are presented. Datasets from four experiments – two over land and two over the sea – are used to compare boundary layer heights from both methods. Only the daytime boundary layer is investigated because the height of the nighttime stable boundary layer is below the range of the lidar. In many situations the boundary layer heights from both systems coincide within ±200 m. This corresponds to the standard deviation of lidar-derived 10-min values within a 1-h interval and is due to the time and space variability of the boundary layer height. Deviations appear for certain situations and depend on which radiosonde method is applied. The parcel method fails over land surfaces in the afternoon when the boundary layer stabilizes and over the ocean when the boundary layer is slightly stable. An automatic radiosonde gradient method sometimes fails when multiple layers are present, e.g. a residual layer above the growing convective boundary layer. The lidar method has the advantage of continuous tracing and thus avoids confusion with elevated layers. On the other hand, it mostly fails in situations with boundary layer clouds

The height of the atmospheric boundary layer on the Antarctic plateau is of particular importance to designers of optical telescopes for Antarctica. Snodar was developed at the University of New South Wales to measure the height of the atmospheric boundary layer at Dome A and Dome C on the Antarctic plateau. Snodar, or Surface layer Non-Doppler Acoustic Radar, is a true monostatic high-frequency acous tic radar (SODAR) operating between 5 kHz and 15 kHz. As the height of the boundary layer at Dome C is expected to be less then 30 m, and unknown at Dome A, Snodar was designed to have a minimum sampling height of 5 m with a vertical resolution of 1 m or better. Snodar uses a PC/104 computer to perform signal processing in real time, and a USB sound card for low-latency analog IO. Snodar was designed to run autonomously storing data on USB flash disks for retrieval the following summer, while uploading of data acquisition scripts and spot checking of data is possible via Iridium satellite through UNSW's PLATO facility. Snodar also incorporates a unique in-situ calibration sphere. We present details of the design and results from testing of Snodar. Keywords: atmosphere, boundary layer, SODAR, Antarcti ca, Antarctic plateau, astronomy, site-testing

The aerosol optical depth (AOD) from satellites or ground-based sun photometer spectral observations has been widely used to estimate ground-level PM2.5 concentrations by regression methods. The boundary layer height (BLH) is a popular factor in the regression model of AOD and PM2.5, but its effect is often uncertain. This may result from the structures between the stable and convective BLHs and from the calculation methods of the BLH. In this study, the boundary layer is divided into two types of stable and convective boundary layer, and the BLH is calculated using different methods from radiosonde data and National Centers for Environmental Prediction (NCEP) reanalysis data for the station in Beijing, China during 2014–2015. The BLH values from these methods show significant differences for both the stable and convective boundary layer. Then, these BLHs were introduced into the regression model of AOD-PM2.5 to seek the respective optimal BLH for the two types of boundary layer. It was found that the optimal BLH for the stable boundary layer is determined using the method of surface-based inversion, and the optimal BLH for the convective layer is determined using the method of elevated inversion. Finally, the optimal BLH and other meteorological parameters were combined to predict the PM2.5 concentrations using the stepwise regression method. The results indicate that for the stable boundary layer, the optimal stepwise regression model includes the factors of surface relative humidity, BLH, and surface temperature. These three factors can significantly enhance the prediction accuracy of ground-level PM2.5 concentrations, with an increase of determination coefficient from 0.50 to 0.68. For the convective boundary layer, however, the optimal stepwise regression model includes the factors of BLH and surface wind speed. These two factors improve the determination coefficient, with a relatively low increase from 0.65 to 0.70. It is found that the regression coefficients of the BLH are positive and negative in the stable and convective regression models, respectively. Moreover, the effects of meteorological factors are indeed related to the types of BLHs.