Boundary Layer Height Characteristics in Mexico City from Two Remote Sensing Techniques

Abstract. Accurate boundary layer structure and height are critical in the analysis of the features of air pollutants and local circulation. Although surface-based remote sensing instruments provide a high temporal resolution of the boundary layer structure, there are numerous uncertainties in terms of the accurate determination of the atmospheric boundary layer heights (ABLHs). In this study, an algorithm for an integrated system for ABLH estimation (ISABLE) was developed and applied to the vertical profile data obtained using a ceilometer and a microwave radiometer in Seoul city, Korea. A maximum of 19 ABLHs were estimated via the conventional time-variance, gradient, wavelet, and clustering methods using the backscatter coefficient from the ceilometer. Meanwhile, several stable boundary layer heights were extracted through near-surface inversion and environmental lapse rate methods using the potential temperature from the microwave radiometer. The ISABLE algorithm can find an optimal ABLH from post-processing, such as k-means clustering and density-based spatial clustering of applications with noise (DBSCAN) techniques. It was found that the ABLH determined using ISABLE exhibited more significant correlation coefficients and smaller mean bias and root mean square error between the radiosonde-derived ABLHs than those obtained using the most conventional methods. Clear skies exhibited higher daytime ABLH than cloudy skies, and the daily maximum ABLH was recorded in summer because of the more intense radiation. The ABLHs estimated by ISABLE are expected to contribute to the parameterization of vertical diffusion in the atmospheric boundary layer.

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

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.

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.

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.

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.

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.

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.

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.

The Atmospheric Release Advisory Capability (ARAC) is an operational emergency response program which provides real-time dose assessments of airborne pollutant releases. This report reviews methodologies for determining the height of the atmospheric boundary layer (ABL), which were investigated for use in the next generation of ARAC diagnostic and dispersion models. The ABL height, hABL, is an essential parameter in atmospheric dispersion modeling, controlling the extent of the vertical mixing of pollutants near the surface. Although eventually instrumentation (radiosonde, lidar, sodar, etc.) may provide accurate means for determining hABL, at present the availability of such data is too limited to provide a general capability for ARAC. The current operational ARAC diagnostic models use a fixed value of hABL for any given time. ARAC's new models support a horizontally-varying atmospheric boundary layer height, which is used to generate meteorological (mean wind, temperature, etc.) and turbulence fields. The purpose of the present work is to develop methods to derive the ABL height for all atmospheric stability regimes. One of our key requirements is to provide approaches which are applicable to routinely available data, which may be of limited temporal and spatial resolution. The final objective is to generate a consistent set of meteorological and turbulence or eddy diffusivity fields to drive the new ARAC dispersion model. A number of alternative definitions of the atmospheric boundary layer exist, leading to different approaches to deriving hABL. The definitions are based on either the turbulence characteristics of the atmosphere or the vertical structure of one or more meteorological variables. Most diagnostic analyses determine hABL from profiles of temperature or occasionally wind. A class of methods of considerable current interest are based on Richardson number criteria. Prognostic methods calculate the time evolution of the top of the ABL from a rate equation. A number of commonly used methods of both types are reviewed along with considerations on their applicability to various types of meteorological data and atmospheric conditions.

<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.

The atmospheric boundary layer height is important for constraining air pollution and meteorological models. This study attempted to validate the MODIS-estimated atmospheric boundary layer height (ABLH), and variation in the ABLH in Uganda was evaluated. The ABLH was estimated from MODIS data using the mixing ratio profile gradient method and compared to the ABLH estimated from radiosonde data using three different methods. Unlike in studies in other regions of the world, correlations between ABLH estimated using MODIS and radiosonde data were weak, implying limited usefulness of MODIS data for determining ABLH. However, the diurnal variation in MODIS-derived ABLH and particulate matter (PM10) was consistent with the expected inverse relationship between PM10 mass concentration and ABLH, and the mean MODIS-derived ABLH values were significantly lower during wet seasons than dry seasons, as expected.

The atmospheric boundary layer (ABL) height (h) is a crucial parameter for the treatment of the ABL in weather and climate models. About 1000 soundings from 11 cruises between 1995 and 2001 over the eastern Pacific have been analyzed to document the large meridional, zonal, seasonal, and interannual variations of h. In particular, its latitudinal distribution in August has three minima: near the equator, in the intertropical convergence zone (ITCZ), and over the subtropical stratus/stratocumulus region near the west coast of California and Mexico. The seasonal peak of h in the ITCZ zone (between 5.6° and 11.2°N) occurs in the spring (February or April), while it occurs in August between the equator and 5.6°N. Comparison of these data with the 10-yr monthly output of the Community Climate System Model (CCSM2) reveals that overall the model underestimates h, particularly north of 20°N in August and September. Directly applying the radiosonde data to the CCSM2 formulation for computing h shows that, at the original vertical resolution (with the lowest five layers below 2.1 km), the CCSM2 formulation would significantly underestimate h. In particular, the correlation coefficient between the computed and observed h values is only 0.06 for cloudy cases. If the model resolution were doubled below 2.1 km, however, the performance of the model formulation would be significantly improved with a correlation coefficient of 0.78 for cloudy cases.