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This study characterizes the variability in different parameters using high-frequency ground-based instruments, i.e., ceilometer and Micro Rain Radar (MRR), on a diurnal scale installed at the Indian Institute of Technology Bhubaneswar, Odisha, India. The study evaluates cloud base height (CBH) and boundary layer height (BLH) to understand their role in influencing convection from liquid water content (LWC), rain rate, radar reflectivity, and fall velocity over a tropical location for different seasons on a diurnal scale. The data retrieved from these surface-based instruments are segregated into four different seasons, i.e., pre-monsoon, monsoon, post-monsoon, and winter, for 2019 and 2020. It is noted that the atmospheric processes influencing convection and associated rainfall over the study location differ for different seasons. The frequency distribution of different types of clouds depending on their vertical levels, i.e., low-level clouds (LLC), mid-level clouds (MLC), and high-level clouds (HLC), during different seasons revealed a high occurrence of low- to mid-level clouds in pre-monsoon and post-monsoon seasons, mid-level clouds in the monsoon season, and low-level clouds in the winter season. The results also illustrate that the rainfall during different seasons largely depends on the types of clouds, i.e., LLC, MLC, and HLC, as detected from the CBH layers, which contribute to convection and rainfall over the study location. It is also revealed that the boundary layer processes in convection and rainfall influence the evolution of BLH during different seasons. Further, the study compares model skills in verifying boundary layer height and rainfall against surface-based observations. Besides characterizing the diurnal variability in these parameters on a daily scale, the study also elucidates the relationship between the cloud types and BLH. The results indicate that LLC occurrences were positively related to BLH during the pre-monsoon and monsoon seasons in 2019 and 2020. In contrast, a negative correlation is observed for cloud types MLC and HLC with BLH for the rest of the seasons of 2019 and 2020. Also, during post-monsoon and monsoon, distinct signatures of deep convection are noted over the study region, suggesting the influence of the boundary layer on MLC and HLC. The results from radar reflectivity and fall velocity during the monsoon and post-monsoon season support the influence of MLC and HLC on deep convection over the region. The diurnal variation in the observed parameters on a seasonal scale will help in understanding the role of various atmospheric parameters and processes in convection and associated rainfall over a tropical location and can provide necessary verification skills for weather and climate regional models against observations. [ABSTRACT FROM AUTHOR]

In this study, we utilize a novel approach to solve the Ekman equations for eddy-viscosity profiles in the stable boundary-layer. By doing so, a well-known expression for the stable boundary-layer height by Zilitinkevich (Boundary-Layer Meteorology, 1972, Vol. 3, 141–145) is rediscovered. [ABSTRACT FROM AUTHOR]

The planetary boundary layer height is a very important parameter in the atmosphere because it determines the range where the most effective dispersion processes take place, and it serves as a medium for the vertical transport of heat, moisture, and pollutants. The accurate estimation of boundary layer height (BLH) is vital for air pollution prediction. In this paper, the BLH estimated by AD-Net was compared with that from the ECMWFs over East Asia from September 2015 to August 2018. A continuous 24 h BLH estimation from AD-Net generally matched with the aerosol vertical structures. Diurnal and seasonal variation and spatial variation of BLH can also be shown, suggesting the good performance of AD-Net BLH. The comparison of seasonal mean BLH between AD-Net and ECMWFs was conducted at 20 lidar sites. On average, there was an underestimation of the ECMWFs, mostly in summer and winter. A significant disagreement between AD-Net and the ECMWFs was noted, especially over coastal areas and mountain areas. In order to investigate the difference between them, two BLHs were compared under different land cover types and climate conditions. In general, the BLH of the ECMWFs was less than that of AD-Net over most of the land cover types in summer and winter. The smallest differences (0.26 km) existed over water surfaces in winter compared with AD-Net, and the largest underestimation (1.42 km) occurred over grassland surfaces in summer. Similarly, all the BLHs of the ECMWFs were lesser than those of AD-Net under different climatological conditions in summer and winter. The mean difference between AD-Net BLH and ECMWFs BLH was 1.05, 0.71, and 0.48 km for arid regions, semi-arid and semi-wet regions, and wet regions, respectively. The largest underestimation occurred over arid regions in winter, with a value of 1.42 km. The smallest underestimation occurred over wet regions, with a value of 0.27 km. The present research provides better insight into the BLH performance in the ECMWFs reanalysis data. The new continuous PBL dataset can be used to improve the model parameterization of PBL and our understanding of the atmospheric transport of pollutants which affect air quality and human health. [ABSTRACT FROM AUTHOR]

The west‐east terrain cross‐section along ∼150 km of the northern part of Israel has a coastal plain—mountain—valley structure; hereafter denoted iCMV. The boundary layer height (BLH) evolution mechanism across the iCMV has not yet been fully understood. We use Weather Research and Forecasting (WRF) simulations and ceilometer measurements to decipher the iCMV BLH evolution mechanism during the late summertime period of 5–14 September 2017, where the daily maximum BLH at the mountainous city of Jerusalem (JrM; 800 m above sea level) varies by ∼1,000 m. We first verify the BLH, simulated by five model configurations (with four different BL schemes). The RMSE for the three best configurations are around 160 and 200 m for the coastal and JrM areas, respectively. An analysis of the simulated daily BL evolution reveals a general mechanism. In the early morning, the upslope flows and synoptic forcing interact to induce a surface flow convergence (SFC) zone. During a westerly (easterly) synoptic flow, the SFC is induced east (west) of JrM. Assisted by the inland propagating sea breeze front, the SFC is advected eastwards during the afternoon, until it collapses at the valley bottom. The SFC zone is accompanied by a substantial positive vertical wind column and a locally elevated BLH. The more western the morning time SFC is, the more likely the elevated BLH will pass during midday through JrM, with a higher daily maximum BLH. The exact dependence of the BLH evolution and of the associated temperature and humidity variations upon the synoptic regime require further study. Key Points: Weather Research and Forecasting simulations are used to study the boundary layer height (BLH) evolution across the Israeli coast—mountain—valley (west‐east) terrainBefore midday, the synoptic, and upslope flows induce a stationary surface convergence zone of hyperelevated BLHThe initial location of the elevated BLH zone depends on the synoptic regime. It is later advected toward the valley by the sea breeze [ABSTRACT FROM AUTHOR]

The planetary boundary layer height (PBLH) is a fundamental variable of the planetary boundary layer (PBL). The effect of surface heterogeneity is challenging in the PBL parameterization for numerical weather and climate models. Here we use large eddy simulation data to investigate the impact of surface heating heterogeneity on the PBLH spatial variations and mean values over a domain of typical mesoscale model grid size. It is found that this impact depends on background wind condition. Variance decomposition and Fourier spectra both reveal that for the fully developed sheared convective PBL, surface heterogeneity contributes little to the spatial variation of PBLH, except for the case with heterogeneity scale of 14.4 km. This suggests that surface heterogeneity with length scales less than ∼10 km, which is typical for mesoscale modeling, does not induce significant subgrid spatial variation of PBLH. The domain‐averaged PBLH is found to generally increase as surface heterogeneity scale decreases, until reaching the scale on the order of PBLH. The findings can be used to inform the parameterization development of PBL processes over heterogeneous surface. Key Points: Surface heterogeneity with scales less than ∼10 km does not induce significant spatial variation of planetary boundary layer (PBL) height for sheared convective PBLThe highest domain‐averaged PBL height occurs with surface heterogeneity scales on the order of PBL heightImpact of surface heterogeneity depends on background wind condition [ABSTRACT FROM AUTHOR]

This study assesses the characteristics of atmospheric boundary layer (ABL) between Facility for Airborne Atmospheric Measurements (FAAM) aircraft observations and NCMRWF Unified Model (NCUM) forecasts on 07 July 2016. On this day the flight was operated over monsoon trough region. Two model forecasts data are utilized (global-17 km; regional-4 km) at a lead time of day-1 to day-3. The chosen variables are boundary layer height (Zi) in km, wind speed (WS) in m s−1, vertical velocity (w) in m s−1, water vapor mixing ratio (r) in g kg−1, and temperature (T) in oC. Special emphasis is given to the evolution of the ABL and peak of low-level jet (LLJ). Results suggest that both the models have noticed warm biases for T, wet biases for r, and negative biases for w. On the other hand, WS found to have negative (positive) biases during the straight level (profile) runs. Point-by-point correlations suggest that T, and r are in good agreement (R > = 0.94), and moderate agreement (ranges from 0.66 to 0.77) for WS, whereas the vertical velocities are poorly predicted (R < 0.2). Strikingly, the correlations (biases) are dropped (increased) with lead time in two models. Small improvements in the statistics (R, bias) are noticed when the model resolution changes from 17 to 4 km. Both models can identify the observed evolution of the ABL; however, Zi values are slightly lower in models compared to observations. Interestingly, the Zi values are slightly dropped (100–200 m) from day-1 to day-3 forecast in two models. The peak of LLJ follows clear time variation, and its height is decreased with forecast lead time. Wind speeds below (above) the ABL height increases (decreases) with lead time, respectively. By considering all flight points across the flight track, the mean Zi is 100–500 m higher in the global model compared to the regional model. The noticed differences between two model ABL heights are discussed in the light of soil moisture conditions, fluxes, temperature advection, and static stability. Overall, a good correspondence is seen between FAAM observations and model forecasts, whereas the regional forecasts have better agreements in predicting ABL characteristics (10–20%). [ABSTRACT FROM AUTHOR]

Traditional observation methods of the boundary layer are susceptible to external factors. In particular, detection data are relatively scarce in special areas such as plateaus and oceans. However, occultation observation data have the unique advantage of global coverage, and the boundary layer information of the occultation profile is rich. Based on the machine learning algorithm, this paper combines GPS occultation technology to improve the algorithm and constructs the boundary layer height simulation model based on the actual situation and analyzes its functional structure one by one. Moreover, in order to verify the validity of the simulation model, a simulation analysis is performed in combination with actual data. In addition, the performance of the model is verified from multiple aspects, and the results of the research are calculated by mathematical statistics, and the corresponding statistical diagram is drawn. Through experimental analysis, it can be known that the model constructed in this paper can effectively simulate the boundary height and has certain practical effects. [ABSTRACT FROM AUTHOR]

Energy consumption in Bangladesh increased for economic, industrial, and digitalization growth. Reductions in conventional sources such as natural gas (54%) and coal (5.6%) are calls to enhance renewable resources. This paper aims to investigate the atmospheric variables for potential wind zones and develop a statistical power-forecasting model. The study-site is Bangladesh, focusing on eight divisions across two regions. First, the southern zone includes Dhaka (Capital), Chittagong, Barishal, and Khulna. The northern regions are Rajshahi, Rangpur, Mymensingh, and Sylhet. This investigation illustrates wind (m/s) speeds at various heights (m) and analyzes the boundary layer height (BLH) from the European Center for Medium Range Weather Forecast reanalysis 5th generation (ERA5). The data is from a period of 40 years from 1979 to 2018, assessing with a climatic base of 20 years (1979 to 2000). The climatological analysis comprises trends, time series, anomalies, and linear correlations. The results for the wind speed (BLH) indicate that the weakest (lower) and strongest (higher) regions are Sylhet and Barishal, respectively. Based on power-curve relationships, a simple power predictive model (SPPM) is developed using global wind atlas (GWA) data (sample: 1100) to estimate the power density (W/m2) and found an accuracy of 0.918 and 0.892 for Exponential (EXP) and Polynomial (PN) with mean absolute percentage errors (MAPE) of 22.92 and 21.8%, respectively. For validation, SPPM also forecasts power incorporating historical observations for Chittagong and obtains correlations of 0.970 and 0.974 for EXP and PN with a MAPE of 10.26 and 7.69% individually. Furthermore, calculations for annual energy production reveal an average megawattage of 1748 and 1070 in the southern and northern regions, with an MAPE of 15.71 and 5.85% for EXP and PN models, except Sylhet. The SPPM's predictability can be improved with observed wind speeds and turbine types. The research wishes to apply SPPM for estimating energy in operational power plants. [ABSTRACT FROM AUTHOR]

• The ASoRA method estimates the atmospheric attenuation in a tower CSP. • The atmospheric attenuation occurs in the atmospehric column and in the slant path. • ASoRA is validated with data observed at Ouarzazate, Morocco. • The aerosols are assumed to lie in a surface layerwith a height varying with time. • A reanalysis data set is tested to show the efficiency of ASoRA in its global mode. • The estimated annual average of the solar resource parameters is given for Ouarzazate in 2014. The ASoRA method consists in estimating the solar resource in tower concentrated solar plants by exploiting global data sets. The solar resource parameters are not only the Direct Normal Irradiance (DNI) but also the slant path transmittance (T sp). The column to surface-level conversion process was validated by comparing the retrieved aerosol extinction coefficient (AEC) to independent measurements performed by a ground-based nephelometer. The Aerosol Robotic NETwork (AERONET) provided column-integrated aerosol extinction properties. The European Centre for Medium-Range Weather Forecasts Reanalysis Interim boundary layer height was used to reproduce the seasonal dependence of the aerosol vertical profile. At the daily resolution, ASoRA reproduced observed AEC with a relative root mean square difference (rRMSD) of 33% and a correlation coefficient of 0.90. The spectral extrapolation from monochromatic measurements to the solar broadband was validated by comparing computations and observations of DNI. ASoRA was also able to reproduce the hourly variability of DNI observed by a pyrheliometer with a RMSD of 38 W/m2, a rRMSD of 4.6%, and a correlation coefficient larger than 0.98. Despite larger uncertainties caused by using Modern-Era Retrospective analysis for Research and Applications (version 2) instead of AERONET, the annual average of T sp was underestimated by only 0.01, and the annual average of the irradiance loss in the slant path by only 4 W/m2. Largest impact on T sp comes from the parameterisation of the aerosol vertical profile, and the annual average of T sp was 0.945 at Ouarzazate (Morocco) in 2014, with an estimated uncertainty of 0.030. [ABSTRACT FROM AUTHOR]

Monthly means, seasonal variances, and trends of a global climatology boundary layer height (BLH) over West Africa are presented based on 36 years (1979 - 2014) of six-hourly ERA-Interim reanalysis. In this region, we found that there is a link between the West Africa Monsoon (WAM) and the monthly means of BLH where largest values of BLH variances are developed in the tropics close to the Inter Tropical Convergence Zone (ITCZ). High temperatures and sufficient moisture are also available close this area. Seasonal trend magnitudes vary from -20 to 20 m per decade during the period 1979 - 2014 and characterize by negative trend over east of the Sahara region. Trends are only included in the analysis, if their probability exceeds the 95% significance level. Case study of diurnal variation was done during the African monsoon multidisciplinary analyses Special Observing Period 3 (AMMA S0P3) experiment (August 2006). We found that the lower boundary-layer appears around 875 hPa in the monsoon layer where the wind decreases at midday in interaction through exchange processes with air originating from above the boundary layer. In the same time, the dust in Saharan Air Layer (SAL) seems to modify the atmospheric boundary layer (ABL) thermodynamic attributes by altering the shortwave and longwave radiative budget. [ABSTRACT FROM AUTHOR]

Using the wind profile radar and microwave radiometer observation data of the Shanghai World Expo Station on July 15 and July 17 of 2017, and August 18 of 2017, which are non-precipitating periods, different remote sensing methods to retrieve boundary layer height were compared, and the conclusions were obtained as follows: 1) The traditional gradient method and the wavelet method that inverse based on SNR have been improved, and the improvement effect is good. The improved gradient method is closer to the SNR gradient, but the nighttime error is larger, and the improved wavelet method is simpler, and the height curve is smoother. 2) The Holzworth method that highly depends on surface temperature is only suitable for the daytime. 3) The humidity gradient method mainly depends on the selection of critical values, and the daily variation of inversion height is not obvious. [ABSTRACT FROM AUTHOR]

The knowledge regarding how the boundary layer height (BLH) changes over time is still poor. Here we analyze the spatial and temporal changes in radiosonde‐derived measurements of BLH over China from 1979 to 2016. A qualitatively robust and abrupt change of BLH occurred in 2004. Over the former period (from 1979 to 2003) a spatially uniform increase was found in the BLH, while over the latter period BLH decreased in a spatially nonuniform way. Second, the meteorological influence on the rising BLH was determined to have a negative association with soil moisture, lower tropospheric stability and relative humidity, and a positive association with the near‐surface temperature. Yet, there was a different influence of meteorology on the BLH over the latter period, where a negative association was revealed with Tsfc and relative humidity. These findings shed new light on the long‐term changes in air pollution across China. Key Points: Long‐term (1979‐2016) trend in the boundary layer height (BLH) over China was examined using newly released radiosonde dataRobust trend analyses revealed a significant temporal disparity in the trend of BLH, with a robust reversal occurring in 2004The meteorological influences on the rising and declining BLH were determined to be quite different [ABSTRACT FROM AUTHOR]

Taiyuan frequently experiences heavy PM2.5 pollution in winter under unfavorable meteorological conditions. To understand how the meteorological factors influence the pollution in Taiyuan, this study involved a systematic analysis for a continuous period from November 2016 to January 2017, using near-surface meteorological observations, radiosonde soundings, PM2.5 measurements, and three-dimension numerical simulation, in combination with backward trajectory calculations. The results show that PM2.5 concentration positively correlates with surface temperature and relative humidity and anti-correlates with near-surface wind speed and boundary layer height (BLH). The low BLH is often associated with a strong thermal inversion layer capping over. In addition to the high local emissions, it is found that under certain synoptic conditions, the southwesterly and southerly winds could bring pollutants from Linfen to Taiyuan, leading to a near-surface PM2.5 concentration higher than 200 μg m−3. Another pollution enhancing issue is due to the semi-closed basin of Taiyuan affecting the planetary boundary layer (PBL): the surrounding mountains favor the formation of a cold air pool in the basin, which inhibits vertical exchanges of heat, flux, and momentum between PBL and the free troposphere, resulting in stagnant conditions and poor air quality in Taiyuan. These findings can be utilized to improve the understanding of PM2.5 pollution in Taiyuan, to enhance the accuracy of forecasting pollution, and to provide scientific support for policy makers to mitigate the pollution. [ABSTRACT FROM AUTHOR]

Satellite-based monitoring can retrieve ground-level PM2.5 concentrations with higher-resolution and continuous spatial coverage to assist in making management strategies and estimating health exposures. The Sichuan Basin has a complex terrain and several city clusters that differ from other regions in China: it has an enclosed air basin with a unique planetary boundary layer dynamic which accumulates air pollution. The spatiotemporal distribution of 1-km resolution Aerosol Optical Depth (AOD) in the Sichuan Basin was retrieved using the improved dark pixel method and Moderate Resolution Imaging Spectroradiometer (MODIS) data in this study. The retrieved seasonal AOD reached its highest values in spring and had the lowest values in autumn. The higher correlation (r = 0.84, N = 171) between the ground-based Lidar AOD and 1-km resolution MODIS AOD indicated that the high-resolution MODIS AOD could be used to retrieve the ground-level PM2.5 concentration. The Lidar-measured annual average extinction coefficient increased linearly with the Planetary Boundary Layer Height (PBLH) in the range of 100~670 m, but exponentially decreased between the heights of 670~1800 m. Both the correlation and the variation tendency of simulated PBLH from the Weather Research and Forecasting (WRF) model & Shin-Hong (SHIN)/California Meteorological (CALMET) model (WRF_SHIN/CALMET) were closer to the Lidar observation than that of three other Planetary Boundary Layer (PBL) schemes (the Grenier-Bretherton-McCaa (GBM) scheme, the Total Energy-Mass Flux (TEMF) scheme and the University ofWashington (UW) scheme), which suggested that the simulated the Planetary Boundary Layer Height (PBLH) could be used in the vertical correction of retrieval PM2.5. Four seasonal fitting functions were also obtained for further humidity correction. The correlation coefficient between the aerosol extinction coefficient and the fitted surface-level PM2.5 concentration at the benchmark station of Southwest Jiao-tong University was enhanced significantly from 0.62 to 0.76 after vertical and humidity corrections during a whole year. During the evaluation of the retrieved ground-level PM2.5 with observed values from three cities, Yibin (YB), Dazhou (DZ), and Deyang (DY), our algorithm performed well, resulting in higher correlation coefficients of 0.78 (N = 177), 0.77 (N = 178), and 0.81 (N = 181), respectively. [ABSTRACT FROM AUTHOR]

The distribution of hurricane boundary layer heights (HBLHs) relative to the hurricane center is investigated in a composite framework, using total 2674 dropsondes collected within four times the radius of maximum wind speed (RMW) of 61 hurricanes during 2002–2020. The HBLH is computed by the bulk Richardson number (Ri b) method, which is sensitive to the critical Ri b choice and more reasonable when the surface friction effect is considered. The sea surface friction velocity is derived from the 10-m wind speed through an air-sea drag relation. The results show that the HBLH is significantly low in the eye zone (0–0.5 RMW), out of which the HBLH is highest in the gale region (0.5–1.5 RMW) and decreases with the radius to the hurricane center. Similar to the hurricane wind field asymmetry, the HBLH is generally higher in the right than in the left in relation to the hurricane motion direction. ERA5 generally overestimates the HBLH, but substantially underestimates the higher HBLHs around the RMW, showing different variation of HBLHs along with the radius compared to dropsonde observations. According to linear regression analyses, the HBLH at least determined by the Ri b method is importantly affected by the hurricane boundary layer dynamic factor, while has no significant correlation with the thermal factor. • The HBLH by the Ri b method is sensitive to considering surface friction effect or not. • The HBLH distribution is asymmetric relative to the hurricane motion direction. • The HBLH is highly correlated with the hurricane boundary layer dynamic factor. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The advantage provided by the unprecedented data density and deeper penetration of Global Navigation Satellite System (GNSS) Radio Occultation (RO) based refractivity profiles from COSMIC-2/FORMOSAT-7 mission over the tropical and subtropical regions is leveraged to get a seasonal picture of daytime planetary boundary layer height (PBLH) distribution from 2 years of data (from October 2019 to September 2021) using the traditional method and a new approach proposed in this study. Traditional PBLH retrieval relies on the minimum refractivity gradient (MRG). In the new method, preference is given to the lowest significant peak in refractivity gradient (if present) rather than the MRG alone for determining PBLH. Comparison with the MRG method shows the highest decrease in seasonal mean PBLH over the oceanic ITCZ regions (by 500–700 m) which is in line with studies reporting low PBLH from in situ observations. The lowest decrease was observed over subtropical oceanic subsidence regions with marine stratocumulus clouds (MSC region; ~100–150 m) where the MRG method was thoroughly validated. The seasonal scale PBLH uncertainty (standard deviation) decreased by ~300 m over the ITCZ regions in the proposed method; it partially increased over the offshore MSC regions by ~100 m indicating detection of infrequent cases of marine boundary layer decoupled from stratocumulus clouds aloft which is not possible in the traditional method. The overestimation and higher uncertainty in PBLH derived from the traditional method over deep convective regions are attributed to the erroneous detection of seasonally varying cloud tops, subsidence base, and elevated water vapour layers as PBL top. An eastward shift by more than 5o longitude is observed in the location of PBLH maxima (seasonal mean) over the southeastern Pacific Ocean in the proposed method (with respect to the traditional method) for all seasons. The proposed method shows a better comparison with daytime PBLH from ERA5 reanalyses over the oceans but there is a partial overestimation of PBLH by ERA5 over continental regions in the summer hemisphere. • Distinctly low RO-based seasonal mean PBLH observed over deep convective regions over the oceans • Detection of boundary layer top decoupled from stratocumulus cloud deck over the subtropical oceans • Indication of super refraction putting a physical limit on the retrieval of GNSS RO refractivity profiles below the PBL top • Distinct eastward shift observed in the location of the PBLH maxima over the southeastern Pacific Ocean in all seasons [ABSTRACT FROM AUTHOR]

Through comparing the mean wind profiles observed overland during the passages of four typhoons, and the gradient wind speeds calculated based on the sea level pressure data provided by a numerical model, the present paper discusses, (a) whether the gradient balance is a valid assumption to estimate the wind speed in the height range of 1250 m ~ 1750 m, which is defined as the upper-level mean wind speed, in a tropical cyclone over land, and (b) if the super-gradient feature is systematically observed below the height of 1500 m in the tropical cyclone wind field over land. It has been found that, (i) the gradient balance is a valid assumption to estimate the mean upper-level wind speed in tropical cyclones in the radial range from the radius to the maximum wind (RMW) to three times the RMW, (ii) the super-gradient flow dominates the wind field in the tropical cyclone boundary layer inside the RMW and is frequently observed in the radial range from the RMW to twice the RMW, (iii) the gradient wind speed calculated based on the post-landfall sea level pressure data underestimates the overall wind strength at an island site inside the RMW, and (iv) the unsynchronized decay of the pressure and wind fields in the tropical cyclone might be the reason for the underestimation. [ABSTRACT FROM AUTHOR]

The present study highlights the importance of examining the contribution of Saharan dust (SD) sources not only in terms of overall mass contribution but also in terms of composition, size distribution and inhaled dose. The effect of SD intrusions on PM and the respective major and trace metals mass concentrations and size distributions was investigated in a suburban site in Athens, Greece. SD events were associated, on average, with lower boundary layer heights (BLH) compared to the non-Sahara (nSD) dust days. During SD events, PM 1-10 concentrations showed an increasing trend with increasing atmospheric BLH, in contrary to the fine PM (PM 1). Generally, increased PM 1 and CO (i.e. anthropogenic origin) levels were observed for BLH lower than around 500 m. The average contribution of SD to PM 10 and PM 2.5 mass concentration was roughly equal to 30.9% and 19.4%, respectively. The mass size distributions of PM and specific major and trace elements (Na, Al, Si, S, Cl, K, Ca, Fe, and Zn) displayed a somewhat different behavior with respect to the mass origin (Algeria-Tunisia vs Libya-Egypt), affecting in turn the regional deposition of inhaled aerosol in the human respiratory tract (HRT). The average PM deposited mass in the upper and lower HRT was 80.1% (Head) and 26.9% (Lung; Tracheobronchial and Pulmonary region) higher for SD days than for nSD days. Higher doses were estimated in the upper and lower HRT for the majority of the elements, when SD intrusions occurred, supporting the increasingly growing interest in exploring the health effects of SD. Only the mass deposition for S, and Na in the lower HRT and Zn in the upper HRT was higher in the case of nSD. [Display omitted] • Mass/Elemental size distributions displayed different structure with air mass origin. • The size limit separating the fine and coarse mode was at 1 μm. • Increase of 80.1% (Head) and 26.9% (Lung) in PM deposition mass during SD events. • The majority of the SD events were associated with an apparent shallow boundary layer. • Health impacts from allergens, pollen and heavy metals need to be assessed further. [ABSTRACT FROM AUTHOR]

The scarcity and sparsity of meteorological vertical observations have caused severe restrictions in the accurate forward prediction and backward analysis of weather and air pollution. In this study, we used a common camera to automatically photograph the daytime and nighttime lights at an urban site in Beijing during 2019–2020, to support or act as a possible alternative to radiosonde measurement. The photo features characterize the scattering effect of atmospheric particulate matter on visible sunlight or lamps and record cloud, fog, and precipitation processes. The probability distributions of the mean blue brightness (B) and the mean red brightness (R) are significantly different for both the sky-part and the ground-part pixels of the photo. The B/R ratio of the sky part (B/R_sky) is exponentially and negatively correlated with ground PM 2.5 concentration. During the daytime, B/R_sky has a higher priority than the boundary layer height (BLH) in the determination of PM 2.5 concentration by a decision tree model, whereas the BLH plays a key role at night, and the importance of B/R_sky is comparable to that of the BLH in the decision tree. The photo features were adopted as input variables into a simple multi-layer perceptron (MLP) model (3-layer neural network) predicting PM 2.5 concentration, with a root mean square error of 1–3 μg/m3, indicating that the auto-shooting camera is a competitive alternative of meteorological measurement. Because of the low cost of installation, the broad application of auto-photography can make up for deficiencies of sounding observation, i.e., sparse temporal and spatial resolution, and can be accessed by the public in real time. • Auto-photography can help to support limited sounding data. • B/R_sky is nonlinearly and negatively correlated with ground PM 2.5 concentration. • B/R_sky is of equal importance to the BLH in decision tree model. [ABSTRACT FROM AUTHOR]

The top of the boundary layer, referred to as the planetary boundary layer height (BLH), is an important physical parameter in atmospheric numerical models, which has a critical role in atmospheric simulation, air pollution prevention, and climate prediction. The traditional methods for determining BLHs using Doppler lidar vertical velocity variance ( σ w 2 ) can be classified into the variance and peak methods, which depend on atmospheric conditions due to their use of a single threshold, hence limiting their ability to estimate diurnal BLHs. Edge detection (ED) was later introduced in BLH estimation due to its ability to identify the 2D gradient of an image. A key step in ED is automatically identifying the edge of BLHs based on the peaks of the profile, hence avoiding the influence of extreme atmospheric conditions. Two cases in the diurnal cycle on 4 March 2019 and 8 July 2019 reveal that ED outperforms both the variance and peak methods in nighttime and extreme atmospheric conditions. The retrieved BLHs from 2018 to 2020 were compared with radiosonde (RS) measurements for the same time at the neutral, stable, and convective boundary layers. The correlation coefficient (R: 0.4 vs. 0.05, 0.14; 0.26 vs. −0.10, −0.16; 0.35 vs. 0.01, 0.16) and root mean square error (RMSE (km): 0.58 vs. 0.82, 0.90; 0.37 vs. 1.01, 0.50; 0.66 vs. 0.98, 0.82) obtained by the ED method were higher and lower than those obtained by the variance and peak methods, respectively. The mean absolute error (MAE) of the ED method under the NBL, SBL, and CBL conditions are lower than the variance and peak methods (MAE (km): 0.44, 0.14, 0.50 vs. 0.62, 0.34, 0.64; 0.59, 0.75, 0.74), respectively. The mean relative error (MRE) of the ED method is lower than the variance and peak methods under the NBL condition (MRE: −8.88% vs. −18.39%, 13.91%). Under the SBL, the MRE of the ED method is lower than the variance method and higher than the peak method (−38.64%, vs. −152.23%; 14.02%). Under the CBL, the MRE of the ED method is lower than the variance method and higher than the peak method (−15.07% vs. 2.24%; 5.64%). In addition, the comparison between ED and wavelet covariance transform (WCT) method and RS measurements showed that the ED method has a similar performance with the WCT method and is even better. In the long-term analysis, the hourly and monthly BLHs in the diurnal and annual cycles, respectively, as obtained by ED, were highly consistent with the RS measurements and obtained the lowest standard error. In the annual cycle, the retrieved BLHs in summer and autumn were higher than those retrieved in spring and winter. [ABSTRACT FROM AUTHOR]

The turbulent mixing and dispersion of air pollutants is strongly dependent on the vertical structure of the wind, which constitutes one of the major challenges affecting the determination of boundary layer height (BLH). Here, an adaptive method is proposed to estimate BLH from measurements of radar wind profilers (RWPs) in Beijing (BJ), Nanjing (NJ), Chongqing (CQ), and Wulumuqi (WQ), China, during the summer of 2019. Validation against simultaneous BLH estimates from radiosondes (RSs) yielded a correlation coefficient of 0.66, indicating that the method can be used to derive BLH from RWPs. Diurnal variations of BLH and the ventilation coefficient (VC) at four sites were then examined. A distinct diurnal cycle of BLH was observed over all four cities; BLH gradually increased from sunset, reached a maximum in the afternoon, and then dropped sharply after sunset. The maximum hourly average BLH (1.426 ± 0.46 km) occurred in WQ, consistent with the maximum hourly mean VC larger than 5000 m2/s observed there. By comparison, the diurnal variation of VC was not strong, with values ranging between 2000 and 3000 m2/s, likely owing to the high-humidity environment. Furthermore, surface sensible heat flux, latent heat flux, and dry mass of particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5) concentrations were found to somehow affect the vertical structure of wind and thermodynamic features, leading to a difference between RS and RWP BLH estimates. This indicates that the atmospheric environment can affect BLH estimates using RWP data. The BLH results from RWPs were better in some specific cases. These findings show great potential of RWP measurements in air quality research, and will provide key data references for policy-making toward emission reductions. [ABSTRACT FROM AUTHOR]