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Coincident profiles from the space-borne and ground-based lidar measurements provide a unique opportunity to estimate the planetary boundary layer height (PBLH). In this study, PBLHs derived from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) were assessed by comparing them with those obtained from the ground-based lidar at Seoul National University (SNU) in Korea for both day and night from 2006 to 2019, and sounding data. CALIOP-derived PBLHs using wavelet covariance transform (WCT) are generally higher than those derived from the SNU lidar for both day and night. The difference in PBLH tends to increase as the signal-to-noise ratio for CALIOP decreases. The difference also increases as aerosol optical depth increases, implying that the PBLH estimated from CALIOP could be higher than that determined from the SNU lidar because of the signal attenuation within the aerosol layer under optically thick aerosol layer conditions. The higher PBLH for CALIOP in this study is mainly attributed to multiple aerosol layers. After eliminating multilayer cases, the PBLHs estimated from both the lidars showed significantly improved agreement: a mean difference of 0.09 km (R = 0.81) for daytime and 0.25 km (R = 0.51) for nighttime. The results from this study suggest that PBL detection using CALIOP is reliable for daytime if multilayer cases are removed. For nighttime, PBLHs derived from the SNU lidar and CALIOP showed a relatively large difference in frequency distribution compared with sounding data. It suggests that further investigations are needed for nighttime PBLHs, such as investigations about discriminating the residual layer and the difference between lidar-derived PBLH based on the aerosol layer and thermally derived PBLH from radiosonde data for the stable boundary layer during the nighttime.

Turbulent mixing in the planetary boundary layer (PBL) governs the vertical exchange of heat, moisture, momentum, trace gases, and aerosols in the surface–atmosphere interface. The PBL height (PBLH) represents the maximum height of the free atmosphere that is directly influenced by Earth’s surface. This study uses a multidata synthesis approach from an ensemble of multiple global datasets of radiosonde observations, reanalysis products, and climate model simulations to examine the spatial patterns of long-term PBLH trends over land between 60°S and 60°N for the period 1979–2019. By considering both the sign and statistical significance of trends, we identify large-scale regions where the change signal is robust and consistent to increase our confidence in the obtained results. Despite differences in the magnitude and sign of PBLH trends over many areas, all datasets reveal a consensus on increasing PBLH over the enormous and very dry Sahara Desert and Arabian Peninsula (SDAP) and declining PBLH in India. At the global scale, the changes in PBLH are significantly correlated positively with the changes in surface heating and negatively with the changes in surface moisture, consistent with theory and previous findings in the literature. The rising PBLH is in good agreement with increasing sensible heat and surface temperature and decreasing relative humidity over the SDAP associated with desert amplification, while the declining PBLH resonates well with increasing relative humidity and latent heat and decreasing sensible heat and surface warming in India. The PBLH changes agree with radiosonde soundings over the SDAP but cannot be validated over India due to lack of good-quality radiosonde observations.

Climate change’s impact on lightning and thunderstorms is uncertain. This study evaluates the sensitivity of multiple Planetary Boundary Layer (PBL) parameterisation schemes within the WRF-ELEC model for simulating a severe lightning and thunderstorm event in Bihar on 25 June 2020. The aim is to understand how these schemes affect lightning and thunderstorm intensity. The model was integrated for 54 h at 0000 UTC on 24 June 2020 using 6-hourly NCEP FNL Operational Global Analysis data at 1° × 1° resolution over Bihar with double nested domains of 9 km (D1) and 3 km (D2). It effectively captures the peak lightning and thunderstorm activity from 0000 to 0900 UTC on 25 June 2020, significantly impacting certain regions. The study utilised ERA5 and IMDAA reanalysis datasets and NASA GPM IMERG daily data to analyse the event and assess the model’s performance. Among the PBL schemes tested, ACM2, BouLac, SHsa, and MRF exhibit robust performance. Flash Origin Density (FOD) patterns broadly match observations, although occasional discrepancies occur in southern Bihar. Convective Available Potential Energy (CAPE) and precipitation (mm) analysis reveals anticipated trends. Statistical scores highlight strong performance by ACM2, UW, and GBM schemes in POFD/FAR. The MRF scheme excels in POD/Hit Rate, and the UW scheme achieves the highest score for 24-h accumulated total precipitation. HSS and GSS/ETS underscore the superior performance of the UW and GBM schemes. This study offers insights into lightning and thunderstorm simulations over Bihar with diverse PBL parameterisation schemes in the WRF-ELEC model.

We studied the influence of the Planetary Boundary Layer (PBL) on the air masses sampled at the mountaintop Hellenic Atmospheric Aerosol and Climate Change station ((HAC)2) at Mount Helmos (Greece) during the Cloud-AerosoL InteractionS in the Helmos background TropOsphere (CALISTHO) Campaign from September 2021 to March 2022. The PBL Height (PBLH) was determined from the standard deviation of the vertical wind velocity (σw) measured by a wind Doppler lidar (over a 30-min time window with 30 m spatial resolution); the height for which σw drops below a characteristic threshold of 0.1 m s–1 corresponds to the PBLH. The air mass characterization is independently carried out using in situ measurements sampled at (HAC)2 (equivalent black carbon, eBC; fluorescent particle number, aerosol size distributions, absolute humidity).We found that a distinct diurnal cycle of aerosol properties is seen when the station is inside the PBL (i.e., PBLH exceeds the (HAC)2 altitude); and a complete lack thereof when it is in the Free Tropospheric Layer (FTL). Additionally, we identified transition periods where the (HAC)2 site location alternates between the FTL (usually during the early morning hours) and the PBL (usually during the midday and late afternoon hours), during which the concentration and characteristics of the aerosols vary the most. Transition periods are also when orographic clouds are formed. The highest PBLH values occur in September [400 m above (HAC)2] followed by a transition period in November, while the lowest ones occur in January [200 m below (HAC)2]. We found also that the PBLH increases by 16 m per 1°C increase of the ground temperature.

This study presents an intercomparison of planetary boundary layer height (PBLH) estimates derived from three distinct approaches: the Morphological Image Processing Approach (MIPA) algorithm applied to ground-based lidar measurements, European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th Generation (ERA5) and Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) reanalysis model outputs, and radiosonde (RS) observations, this latter being taken as reference. The intercomparison was conducted during three measurement episodes, encompassing a total of 153 h (6 days), as part of the Boundary Layer Extensive Campaign with muLti-instrumentaL Analysis (BELLA), carried out in spring and early summer 2024 at the CNR-IMAA Atmospheric Observatory (CIAO) in southern Italy (40.60N, 15.72E). The study provides insights into the performance and reliability of these PBLH estimation approaches under diverse atmospheric scenarios. Visual and statistical analyses of selected case studies indicate that MIPA often tracked the aerosol layering structure and diurnal PBLH evolution more closely than ERA5 and MERRA-2, particularly during convective growth and evening transitions. On the other hand, it is found that ERA5 provides more accurate estimates of the nighttime PBLH, where MIPA shows poor nighttime estimation capabilities. Quantitative comparison against radiosonde data reveals that MIPA reaches a weighted root mean square error (RMSEw) of 380±41 m with a coefficient of determination (R2) of 0.68±0.16, while ERA5 shows an RMSEw of 292±72 m and an R2 of 0.81±0.11; and MERRA-2 shows an RMSEw of 631±124 m and an R2 of 0.34±0.21. By combining MIPA daytime and ERA5 nighttime PBLH, the overall results are improved, obtaining an R2=0.86±0.08 and an RMSEw of 213±40 m. This intercomparison highlights the strengths and limitations of each method and demonstrates the benefits of combining complementary PBLH retrieval techniques. The findings contribute to refining boundary layer monitoring methodologies and provide guidance for operational atmospheric observation networks.

What are the main findings? The gradient method and standard deviation method based on Micro-Pulse Lidar and the parcel method based on Microwave Radiometers are more sensitive to abrupt changes in boundary layer height. During the observation period, Shenzhen’s PBLH characteristics exhibited significant diurnal variation and high sensitivity to pollution, the daytime mean PBLH ranged from approximately 512 to 1345 m, while nighttime values generally decreased to around 500 to 650 m. And under high aerosol loading conditions, PBLH was significantly suppressed to approximately 500 m, indicating that pollution limits atmospheric mixing by inhibiting boundary layer development. What are the implications of the main findings? By comparing different retrieval methods, we can identify the strengths and weaknesses of each method, providing guidance on selecting appropriate algorithm for similar urban environments. The study of boundary layer characteristics in Shenzhen holds significant scientific value for future research on factors influencing boundary layer height in megacities. The PBLH affects the intensity of the surface turbulence and the state of pollutant dispersion. Current research on PBLH characteristics and their relationship with pollution in coastal megacities remains insufficient. Moreover, existing studies rarely evaluate the consistency of various boundary layer solution methods, making it difficult to identify deviations in single methods. So, we conducted enhanced observation experiments in Shenzhen, a megacity in China, between March and July 2023. The characteristics of the PBLH was analyzed by five months of observations from Micro-Pulse Lidar (MPL) and Microwave Radiometer (MWR). Five retrieval methods (Parcel, GRA, STD, WCT, and Theta) were applied for comparative assessment. The results shows that all methods captured similar diurnal patterns. During daytime, the PBLH ranged from 512 to 1345 m, with Theta yielding the highest and STD the lowest average values. At night, PBLH decreased overall, and method-dependent differences persisted. Under different pollution levels, this study also discussion the properties of PBLH using MPL and microwave radiometer. And aerosol optical depth (AOD) and PBLH showed a strong negative correlation, indicating aerosol-induced suppression of boundary layer growth. The study of boundary layer characteristics in coastal megacities can provide reference for atmospheric physics research in economically developed coastal areas.

This paper reviews the evolution of planetary boundary layer (PBL) parameterization schemes that have been used in the operational version of the Hurricane Weather Research and Forecasting (HWRF) model since 2011. Idealized simulations are then used to evaluate the effects of different PBL schemes on hurricane structure and intensity. The original Global Forecast System (GFS) PBL scheme in the 2011 version of HWRF produces the weakest storm, while a modified GFS scheme using a wind-speed dependent parameterization of vertical eddy diffusivity (Km) produces the strongest storm. The subsequent version of the hybrid eddy diffusivity and mass flux scheme (EDMF) used in HWRF also produces a strong storm, similar to the version using the wind-speed dependent Km. Both the intensity change rate and maximum intensity of the simulated storms vary with different PBL schemes, mainly due to differences in the parameterization of Km. The smaller the Km in the PBL scheme, the faster a storm tends to intensify. Differences in hurricane PBL height, convergence, inflow angle, warm-core structure, distribution of deep convection, and agradient force in these simulations are also examined. Compared to dropsonde and Doppler radar composites, improvements in the kinematic structure are found in simulations using the wind-speed dependent Km and modified EDMF schemes relative to those with earlier versions of the PBL schemes in HWRF. However, the upper boundary layer in all simulations is much cooler and drier than that in dropsonde observations. This model deficiency needs to be considered and corrected in future model physics upgrades.

This work investigates the spatio-temporal variability of planetary boundary layer height (PBLH) characteristics by leveraging multi-decadal (1980–2019) data from India’s first high-resolution regional atmospheric reanalysis–IMDAA, in conjunction with ERA5 and MERRA-2. The spatial variability in the seasonal and annual climatological mean PBLH obtained from IMDAA agrees well with ERA5 and MERRA-2, albeit with some differences. The IMDAA and ERA5 PBLH exhibit a high correlation (> 0.6) over the entire India and also show a significant positive (negative) correlation with MERRA-2 over northwest and central (southern and eastern) Indian regions. However, IMDAA tends to overestimate ERA5 PBLH ( ~ < 500 m) and underestimate MERRA-2 PBLH ( ~ > 500 m) during all seasons. Despite these discrepancies, IMDAA successfully captures the diurnal changes in PBLH similar to ERA5 and MERRA-2. Furthermore, the evaluation of IMDAA PBLH in conjunction with other meteorological factors suggests that PBLH exhibits a negative correlation with relative humidity (RH), indicating a decrease in PBLH as RH increases. On the other hand, PBLH shows positive correlations with surface temperature and surface zonal winds. Surface sensible and latent heat flux exhibit positive and negative correlations with PBLH, respectively, over Indian sub-regions throughout all seasons. Moreover, IMDAA realistically represents the declining trend of PBLH (-1.1 to -76.2 m decade − 1 ) compared to ERA5 in India during all seasons. The results from IMDAA, in concurrence with other reanalyses, demonstrate that the decreasing trend in PBLH over India is associated with rising surface temperatures and weakening surface zonal winds. This trend is also attributed to increasing latent heat flux and decreasing sensible heat flux. The changes in surface fluxes over India are attributed to the intensification of Indian monsoon rainfall in the last three decades. Moreover, El Niño appears to be an important control on PBLH variability over India during different seasons, which is realistically represented by IMDAA as in ERA5 and MERRA-2.

Planetary boundary layer (PBL) height plays a significant role in climate modeling, weather forecasting, air quality prediction, and pollution transport processes. This study examined the climatology of PBL-associated meteorological parameters over the Korean peninsula and surrounding sea using data from the ERA5 dataset produced by the European Centre for Medium-range Weather Forecasts (ECMWF). The data covered the period from 2008 to 2017. The bulk Richardson number methodology was used to determine the PBL height (PBLH). The PBLH obtained from the ERA5 data agreed well with that derived from sounding and Global Positioning System Radio Occultation datasets. Significant diurnal and seasonal variability in PBLH was observed. The PBLH increases from morning to late afternoon, decreases in the evening, and is lowest at night. It is high in the summer, lower in spring and autumn, and lowest in winter. The variability of the PBLH with respect to temperature, relative humidity, surface pressure, wind speed, lower tropospheric stability, soil moisture, and surface fluxes was also examined. The growth of the PBLH was high in the spring and in southern regions due to the low soil moisture content of the surface. A high PBLH pattern is evident in high-elevation regions. Increasing trends of the surface temperature and accordingly PBLH were observed from 2008 to 2017.

Air pollution is a severe problem in Almaty (Kazakhstan), especially during the cold half of the year (October-March). Almaty is one of the most polluted cities in Kazakhstan and Central Asia, with average winter PM 2.5 (particulate matter with aerodynamic diameter ≤ 2.5 µm) concentration of 94.0 µg m −3 . High pollution in the wintertime in Almaty could be caused by emissions from coal combustion for power and heat generation (at power plants and small-scale heating), which could also be worsened by poor dispersion of air pollutants due to certain atmospheric conditions. Based on one-year radiosonde data, the characteristics of the planetary boundary layer height (PBLH) and its effect on ground-level PM 2.5 concentrations in Almaty were analyzed in this study using the bulk Richardson number (Ri) and potential temperature increase (PT) methods. During an annual cycle, the concentrations of PM 2.5 were highest in the winter months when the daily concentrations were above 100 µg m −3 for 38 days during this period. The results show a clear negative relationship between the daily average PM 2.5 concentrations and PBLH at 12.00 UTC. For instance, high PM 2.5 concentrations in winter months (94.0 µg m −3 ) corresponded to a lower PBLH (393 m), and low PM 2.5 concentrations in summer months (9.9 µg m −3 ) corresponded to a higher PBLH (1970 m). During the cold half of the year, the top 20% of PM 2.5 concentrations were associated with a lower PBLH and calm wind conditions (lower average wind speeds within the PBL and a lower ventilation coefficient). The results show that PBLH variations during the year have a significant effect on PM 2.5 concentrations; however, further analysis is needed with a more substantial amount of observational data to understand this interaction further and to investigate the role of synoptic processes that lead to a shallow PBLH.