Integrated System for Atmospheric Boundary Layer Height Estimation (ISABLE) using a ceilometer and microwave radiometer

The Atmospheric Boundary Layer (ABL) height is a key parameter in air quality research as well as for numerical simulations and forecasts. The identification of thermally stable layers, often with radiosondes, has been a common approach for estimating ABL height, though with limited temporal coverage. Remote sensing techniques offer essentially continuous measurements. Nevertheless, ABL height retrievals from different methods can vary greatly when compared, which is particularly notable for topographically complex terrains, such as that surrounding Mexico City. This study, employing one year of data in Mexico City, reveals that the daytime convective boundary layer height (retrieved from Doppler lidar data) is typically lower than the aerosol layer height (retrieved from ceilometer data). Although both estimated heights evolved diurnally, the more elevated aerosol layer decays more slowly, suggesting that the mechanisms that elevate aerosols are not limited to convective motions. Additionally, both diurnal and seasonal variability are investigated, comparing remotely sensed-retrieved heights with thermally stable layers estimated from radiosonde data. Multiple stable layers often develop, those at higher levels have similar values to the ceilometer-retrieved heights, while stable layers at lower heights are similar to Doppler lidar height retrievals. The present research constitutes the first detailed analysis of ceilometer backscatter and Doppler lidar thresholding methods for estimating ABL height over Mexico City, and our results illustrate the complexity of mixing mechanisms on the ABL in this region of complex orography.

The atmospheric boundary layer (ABL) height defines the volume of air within which heat, moisture and pollutants released at the Earth’s surface are rapidly diluted. Despite the importance for air quality interpretation, numerical weather prediction, greenhouse gas assessment and renewable energy applications, amongst others, quantitative knowledge on the temporal and spatial variation in ABL height is still scarce. With continuous profiling of the entire ABL vertical extent at high temporal and vertical resolution now increasingly possible due to recent advances in ground-based remote sensing measurement technology and algorithm development, there are also dense measurement networks emerging across Europe and other parts of the world. To effectively monitor the spatial and temporal evolution of the ABL continuously at continent-scale, harmonised operations and data processing are key. Autonomous ground-based remote sensing instruments, such as microwave radiometers, radar wind profilers, Doppler wind lidars or automatic lidars and ceilometers, each offer different capabilities. The overarching objective of this review is to emphasize how these instruments are best exploited with informed network design, algorithm implementation, and data interpretation. A summary of the capability and limitations of each instrument type is provided together with a review of the vast number of retrieval methods developed for ABL height detection from different atmospheric quantities (temperature, humidity, wind, turbulence, aerosol). It is outlined how the diurnal evolution of the ABL can be monitored effectively with a combination of methods, highlighting where instrument or methodological synergy promise to be particularly valuable. To demonstrate the vast potential of increased ABL monitoring efforts, long-term observational studies are reviewed summarising our current understanding of ABL height variations. The review emphasizes that harmonised data acquisition and careful data processing are key to obtaining high-quality products, which are essential to capture the spatial and temporal complexity of the lowest part of the atmosphere in which we live and breathe.

A solar-blind lidar system is developed by using Nd:YAG laser to produce 266nm wavelength at the frequency of 10Hz as the light source to to detect the height of boundary layer in Xi'an area. The observation experiment and analysis are made.The solar background light has no 266nm wavelength and the influence of it can be ignored in the daytime, and then all day detection can be realized. It can be detected in the daytime and nighttime. The wavelength of 266nm absorbed by ozone is considered only. The absolute minimum of first derivative and second derivative of the range-squared-corrected lidar signal are employed to retrieve height of boundary layer. Based on the observation of atmosphere in daytime and nighttime, the heights of atmospheric boundary layer are 0.44km and 0.47km, and the influences of meteorological factors and human activities on the height of atmospheric boundary layer are analyzed. The results showed that the lidar can satisfied the need for detection of troposphere atmospheric aerosol particles at all time and are beneficial to offer practical and effective data for monitoring atmospheric environment in Xi'an aera.

The boundary layer height obtained by the spline numerical differentiation method using COSMIC GPS radio occultation data: A case study of the Qinghai-Tibet Plateau

The lack of sounding observations in the western Tibetan Plateau (TP), the highest terrain in the world, has resulted in few efforts to evaluate the quality of the atmospheric reanalysis results in this region. Using the sounding observations from the Third Tibetan Plateau Atmospheric Scientific Experiment during 2013–2015, the NCEP and ERA-Interim reanalysis temperature and humidity fields in the TP are evaluated and the characteristics of the reanalysis Atmospheric Boundary Layer (ABL) height are utilized to explain the reasons for the differences in temperature and humidity between the western and eastern TP. The results show that the NCEP and ERA-Interim reanalysis temperature and humidity products generally have larger errors at low level (such as 500 hPa) in the western TP (WTP) than in the eastern one (ETP) at 12:00 UTC. However, this difference is small at 00:00 UTC. Further analysis reveals that the temporal and spatial variations of temperature and humidity errors at low level are closely associated with the differences in the terrain and ABL between the western and eastern TP. In the early morning when the ABL height is low over the TP, the 500 hPa pressure level in both the WTP and ETP is significantly above the top of ABL, with weak spatial variations of temperature and humidity errors. However, in the late afternoon when there is a larger increase in ABL height over the WTP than over the ETP, the 500 hPa pressure level is located inside the ABL in the WTP and is still above the ABL in the ETP, which causes significant regional differences in these errors.

We present here a new heuristic framework for the variability of the atmospheric boundary layer (ABL) height h based on an extended concept of the similarity theory retaining non-local effects. Based on several sets of well-known data (Wangara, JASIN, ICE-77), the locus of variability of h in the phase-space determined from this similarity framework points to a new combination for the most relevant scales affecting the ABL height. We show that the most likely length scales to explain the variability of the ABL height are the classical MoninObukhov length L and the background static stratification scale LfluJN, where U, is the friction velocity and N the Brunt-Vaisala frequency above the ABL. This concept is applied to a new set of data obtained above a hgh-latitude forested site, i.e., very different from the above mentioned field experiments. The correlation between the heuristic model and observed values of h reaches high values. This model can be applied to a wide range of quasi-stationary situations, so that relatively simple point measurements can be used to implement the model without calling for prognostic model equations and calculations.

This thesis tackles the problem of the automated detection of the atmospheric boundary layer (BL) height, h, from aerosol lidar/ceilometer observations. A new method, the Bayesian Selective Method (BSM), is presented. It implements a Bayesian statistical inference procedure which combines in an statistically optimal way different sources of information. Firstly atmospheric stratification boundaries are located from discontinuities in the ceilometer back-scattered signal. The BSM then identifies the discontinuity edge that has the highest probability to effectively mark the BL height. Information from the contemporaneus physical boundary layer model simulations and a climatological dataset of BL height evolution are combined in the assimilation framework to assist this choice. The BSM algorithm has been tested for four months of continuous ceilometer measurements collected during the BASE:ALFA project and is shown to realistically diagnose the BL depth evolution in many different weather conditions. Then the BASE:ALFA dataset is used to investigate the boundary layer structure in stable conditions. Functions from the Obukhov similarity theory are used as regression curves to fit observed velocity and temperature profiles in the lower half of the stable boundary layer. Surface fluxes of heat and momentum are best-fitting parameters in this exercise and are compared with what measured by a sonic anemometer. The comparison shows remarkable discrepancies, more evident in cases for which the bulk Richardson number turns out to be quite large. This analysis supports earlier results, that surface turbulent fluxes are not the appropriate scaling parameters for profiles of mean quantities in very stable conditions. One of the practical consequences is that boundary layer height diagnostic formulations which mainly rely on surface fluxes are in disagreement to what obtained by inspecting co-located radiosounding profiles.

Abstract. This study evaluates methods to derive the surface mixing layer (SML) height of the Arctic atmospheric boundary layer (ABL) using in situ measurements inside the Arctic ABL during winter and the transition period to spring. An instrumental payload carried by a tethered balloon was used for the measurements between December 2019 and May 2020 during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Vertically highly resolved (centimeter scale) in situ profile measurements of mean and turbulent parameters were obtained, reaching from the sea ice to several hundred meters above ground. Two typical conditions of the Arctic ABL over sea ice were identified: cloudless situations with a shallow surface-based inversion and cloudy conditions with an elevated inversion. Both conditions are associated with significantly different SML heights whose determination as accurately as possible is of great importance for many applications. We used the measured turbulence profile data to define a reference of the SML height. With this reference, a more precise critical bulk Richardson number of 0.12 was derived, which allows an extension of the SML height determination to regular radiosoundings. Furthermore, we have tested the applicability of the Monin–Obukhov similarity theory to derive SML heights based on measured turbulent surface fluxes. The application of the different approaches and their advantages and disadvantages are discussed.

The Atmospheric Boundary Layer (ABL) height is measured with the help of Monostatic SODAR (Sonic Detection And Ranging) System [1]. Meteorological aspects of Doppler free acoustic sounding (Mono-static SODAR system) of the atmosphere are considered [2, 3]. This instrument plays an important role in ABL studies using remote sensing techniques, where other techniques (like Radio-sonde, LIDAR, and Mast etc.) are difficult and expensive. Various features of Mono-static SODAR records with direct measurements with meteorological sensors in ABL are analysed. Some primary results regarding the statistical analysis of the ABL height, meteorological parameters, atmospheric pollutants of main physical parameter of the ABL (Atmosphere) were shown and discussed for the metropolitan city Delhi during the periods of October 2016 to February 2017. During mid-October to mid-November low height of ABL were observed due to high concentration of atmospheric pollutants and low wind speed. During the period of mid-December 2016 to mid-January 2017, fog episodes and strong low level elevated and inversions were observed most of the time.

Methods of estimation of the atmospheric boundary layer height according to the rawinsonde measurements are considered. Calculations based on the data obtained during observations from the Perm land-based rawinsonde station for the period 2018 to 2024. The atmospheric boundary layer height was estimated based on calculations of the bulk Richardson number and the vertical gradient of the virtual potential temperature. The critical value of the Richardson number indicates atmospheric stability and turbulence. The first point at which the value of bulk Richardson number first reached the critical value is taken as the atmospheric boundary layer height. In other words, the atmospheric boundary layer it is the most turbulent layer of the atmosphere. The article suggests using four critical values of the Richardson number RiBC = {0,1; 0,25; 0,5; 1,0} . The critical value of the Richardson number RiBC = 1,0 shows the most accurate values of the atmospheric boundary layer height. It was determined that the maximum thickness of the atmospheric boundary layer is observed during daytime in summer (1800 m), and the minimum at nighttime in summer (500 m). Moreover, during daytime there is a trend of increasing of the atmospheric boundary layer height from winter to summer, and at nighttime the atmospheric boundary layer height has maximum values in the spring and autumn. Virtual potential temperature profiles are nearly adiabatic in the atmospheric boundary layer. The first point at which the vertical gradient of the virtual potential temperature becomes non-adiabatic is taken as the height of the atmospheric boundary layer. The article shows that values of the atmospheric boundary layer height based on calculations of the vertical gradient of the virtual potential temperature are too large. The use of the considered methods allows to estimate the atmospheric boundary layer height based on the rawinsonde data without making additional measurements, and these methods can be used to study the atmospheric processes occurring in this layer.

The differences in planetary boundary layer characteristics, in particular atmospheric boundary layer height (ABLH), humidity, and local circulations in pre-monsoon and monsoon period over the Erhai Lake, were simulated by the lake-atmosphere coupled model WRF v3.7.1. No lake simulations were also conducted to investigate lake effects over complex topography. During pre-monsoon period, local circulation was fully developed under weak synoptic system. The ABLH ran up to 2300 m or so. During monsoon period, temperature difference between land and lake became smaller, resulting in weaker local circulations. The height of circulation reduced by 500 m, and ABLH ran up to 1100 m during the day. Enhanced soil moisture and low surface temperature due to monsoon rainfalls in July could be the main reason for the slightly lower ABLH over the Erhai Lake area. Specific humidity of the boundary layer increased 8.8 g kg−1 or so during monsoon period. The Erhai Lake enlarged thermal contrast between valley and mountain slope in the Dali Basin. The lake reduced air temperature by 2~3 °C during daytime and increased air temperature by nearly 2 °C in the evening. Due to its small roughness length and large thermal capacity, the Erhai Lake enlarged lake-land temperature difference and local wind speed. A cyclonic circulation was maintained by the combination of mountain breeze and land breeze in the south of the lake. The lake decreased air temperature, increased specific humidity, and reduced ABLH during daytime, whereas the opposite effect is presented at night.

Abstract. We investigate the boundary-layer (BL) height at Hyytiälä in southern Finland diagnosed from radiosonde observations, a microwave radiometer (MWR) and ERA5 reanalysis. Four different, pre-existing algorithms are used to diagnose the BL height from the radiosondes. The diagnosed BL height is sensitive to the method used. The level of agreement, and the sign of systematic bias between the four different methods, depends on the surface-layer stability. For very unstable situations, the median BL height diagnosed from the radiosondes varies from 600 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 ongoing challenge for numerical models to correctly resolve the stable BL. Furthermore, ERA5 BL height differs most from the radiosondes at 18:00 UTC, suggesting ERA5 does not resolve the evening transition correctly. BL height estimates from the MWR are also found to be 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 manufacturer's algorithm for stable conditions and also the misidentification of the type of BL. A climatology of the annual and diurnal cycle of BL height, based on ERA5 data, and surface-layer stability, based on eddy covariance observations, 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.

<strong class="journal-contentHeaderColor">Abstract.</strong> The important roles of the atmospheric boundary layer (ABL) over the Arctic Ocean in the Arctic climate system have been recognized, but the atmospheric boundary layer height (ABLH), as a fundamental variable to characterize the vertical structure of ABL, has rarely been investigated. Analyzing a year-round radiosonde dataset during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), we suggest the optimal critical value of 0.15 of bulk Richardson number to derive ABLH. Based on this algorithm, the hourly ABLH values are derived to analyze the characteristics and variability of ABLH over the Arctic Ocean. The results reveal that the annual cycle is clearly characterized by a distinct peak in May and an abrupt decrease in the following July and August, with a second minimum in December and January. The annual ABLH variation is primarily controlled by the evolution of ABL thermal structure. The temperature inversions in the winter and summer are intensified by seasonal radiative cooling and surface melting, respectively, leading to the low ABLH. The near-surface conditions can also play a significant role in ABLH variation, with turbulent parameters (e.g., friction velocity and turbulent dissipation rate) well correlated with the ABL development. In addition, the MOSAiC ABLH is more suppressed than the ABLH during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment in the summer, which indicates that there is large variability in the Arctic ABL structure during summer melting season.

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.

&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;Atmospheric boundary layer height (BLH) is a key parameter for air quality forecast. To measure it, a common practice is to use aerosol lidars: a strong decrease in the backscatter signal indicates the top of the boundary layer. This work explains and compares two methods of machine learning to derive BLH from backscatter profiles: the K-means algorithm and the AdaBoost algorithm. As K-means is unsupervised, it has less dependency on instrument settings, hence more generalization skills. AdaBoost was used for binary classification: boundary layer/free atmosphere. It has been trained on 2 days, labelled by hand, therefore it has less generalization skills but a better representation of the diurnal cycle. &amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;Both methods are compared to the lidar manufacturer's software and to the BLH derived from collocated radiosondes. The radiosondes are taken as reference for all other methods. The comparison is carried out on a 2 years period (2017-2018) on 2 sites (Trappes and Brest). Data come from Meteo-France's operational network. The code and the data that produced these results will be put under a fully open access licence, with the name of KABL (K-means for Atmospheric Boundary Layer) and ADABL (AdaBoost for Atmospheric Boundary Layer).&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;