Search

Measurements with a 763 nm channel, located within the oxygen A-band and equipped on the Second-generation Global Imager (SGLI) onboard the JAXA's Global Change Observation Mission – Climate (GCOM-C) satellite, have the potential to retrieve cloud base height (CBH) and cloud geometric thickness (CGT) through passive remote sensing. This study implemented an algorithm to retrieve the CBH using the SGLI 763 nm channel in combination with several other SGLI channels in the visible, shortwave infrared, and thermal infrared regions. In addition to CBH, the algorithm can simultaneously retrieve other key cloud properties, including cloud optical thickness (COT), cloud effective radius, ice COT fraction as the cloud thermodynamic phase, cloud top height (CTH), and CGT. Moreover, the algorithm can be seamlessly applied to global clouds comprised of liquid, ice, and mixed phases. The SGLI-retrieved CBH exhibited quantitative consistency with CBH data obtained from the ground-based ceilometer network, ship-borne ceilometer, satellite-borne radar and lidar observations, as evidenced by sufficiently high correlations and small biases. These results provide practical evidence that the retrieval of CBH is indeed possible using the SGLI 763 nm channel. Moreover, the results lend credence to the future use of SGLI CBH data, including the estimation of the surface downward longwave radiative flux from clouds. Nevertheless, issues remain that must be addressed to enhance the value of SGLI-derived cloud retrieval products. These include the systematic bias of SGLI CTH related to cirrus clouds and the bias of SGLI CBH caused by multi-layer clouds. [ABSTRACT FROM AUTHOR]

Ceilometers are used routinely at aerodromes worldwide to derive the height and sky coverage fraction of cloud layers. This information, possibly combined with direct observations by human observers, contributes to the production of meteorological aerodrome reports (METARs). Here, we present ampycloud, a new algorithm, and its associated Python package for automatic processing of ceilometer data with the aim of determining the sky coverage fraction and base height of cloud layers above aerodromes. The ampycloud algorithm was developed at the Swiss Federal Office of Meteorology and Climatology (MeteoSwiss) as part of the AMAROC (AutoMETAR/AutoReport rOund the Clock) program to help in the fully automatic production of METARs at Swiss civil aerodromes. ampycloud is designed to work with no direct human supervision. The algorithm consists of three distinct, sequential steps that rely on agglomerative clustering methods and Gaussian mixture models to identify distinct cloud layers from individual cloud base hits reported by ceilometers. The robustness of the ampycloud algorithm stems from the first processing step, which is simple and reliable. It constrains the two subsequent processing steps that are more sensitive but also better suited to handling complex cloud distributions. The software implementation of the ampycloud algorithm takes the form of an eponymous, pip-installable Python package developed on GitHub and made publicly accessible. [ABSTRACT FROM AUTHOR]

Air pollution is affected by the atmospheric dynamics. This study aims to determine that air pollution concentration values in İstanbul increased significantly and reached peak values due to atmospheric blocking between the 30th of December 2022 and the 5th of January 2023. In this study, hourly pollutant data was obtained from 16 air quality monitoring stations (AQMS), the exact reanalysis data was extracted from ERA5 database, and inversion levels and meteorological and synoptic analyses were used to determine the effects of atmospheric blocking on air pollution. Also, cloud base heights and vertical visibility measurements were taken with a ceilometer. Statistical calculations and data visualizations were performed using the R and Grads program. Omega-type blocking, which started in İstanbul on December 30, 2022, had a significant impact on the 1st and 2nd of January 2023, and PM10 and PM2.5 concentration values reached their peak values at 572.8 and 254.20 µg/m3, respectively. In addition, it was found that the average concentration values in the examined period in almost all stations were higher than the averages for January and February. As a result, air quality in İstanbul was determined as "poor" between these calendar dates. It was found that the blocking did not affect the ozone (µg/m3) concentration. It was also found that the concentrations of particulate matter (PM) 10 µm or less in diameter (PM10) and PM 2.5 µm or less in diameter (PM2.5) were increased by the blocking effect in the İstanbul area. Finally, according to the data obtained using the ceilometer, cloud base heights decreased to 30 m and vertical visibility to 10 m. [ABSTRACT FROM AUTHOR]

During the Atlantic References and Convection (ARC) ship campaign with the reference MSM114/2, which took place in early 2023, the German research vessel Maria S. Merian travelled from Mindelo, Cape Verde, to Punta Arenas, Chile. One of the main objectives of ARC was to obtain vertically resolved cross sections of the Intertropical Convergence Zone (ITCZ). To this end, we crossed the ITCZ three times in the meridional direction. We present the atmospheric and oceanographic measurements collected during ARC in a standardized way to facilitate working with data from different instruments and to make the data easily accessible. This approach is not limited to ARC but could serve as a prototype for future (and past) ship campaigns. We present data from the integrated ship sensors (DShip), a Humidity and Temperature Profiler (HATPRO), a Ceilometer, aerosol instruments (DustTrak, Microtops, and Calitoo), radiosondes, Uncrewed Aircaft Vehicles (UAV), and Conductivity, Temperature, and Depth (CTD) profiles of the upper ocean. We distinguish temporal continuous data (DShip, HATPRO, Ceilometer, DustTrak) from point measurements (radiosondes, UAVs, CTDs, Calitoo, Microtops). To illustrate the data sets provided, we present examples of measurements taken during the three crossings of the ITCZ and during a storm in the Roaring Forties in the South Atlantic at the end of the campaign. All data sets can be downloaded from Köhler et al. (2024a). An overview of all available data sets, including dois, can be found here: https://doi.pangaea.de/10.1594/PANGAEA.966616. For references to the individual data sets, please refer to the data availability section. [ABSTRACT FROM AUTHOR]

Atmospheric boundary layer (ABL) has been characterized over a high altitude station, Umiam in the North Eastern Region (NER) of India using observations and reanalysis products. In this study, we have used in situ data from Dr. Pisharoty GPS radiosonde launched using meteorological balloons during the years 2009 to 2013 and 2019 to 2020 during the afternoon time. For continuous measurement of ABL we have used the data obtained using ceilometer lidar from December 2019 to November 2023. For long term study of ABL height (ABLH) we have used three reanalysis datasets, viz. ERA5, IMDAA and MERRA2. Seasonal variation of ABLH from the radiosonde, ceilometer and reanalysis datasets showed highest during pre-monsoon followed by winter, post monsoon and minimum during monsoon. On both cloudy and clear-sky days, diurnal variability of ABLH was studied using ceilometer data where more than 55% of the total number of observations in each season, were found to be under cloudy conditions. Rapid growth of the ABL was seen from the morning hours during winter (~ 40 m h− 1), pre-monsoon (~ 210 m h− 1), monsoon (~ 291 m h− 1) and post monsoon (~ 100 m h− 1) season under clear-sky conditions as compared to the cloudy days. Hence lesser ABLH during cloudy conditions was prominent throughout the day during all the seasons. Maximum seasonal mean of 1102 (± 370) m was obtained from radiosonde observations during the pre-monsoon season. Comparison between ABLH retrieved from radiosonde and ceilometer were in good agreement with a correlation coefficient of 0.91. A comparison study of ABLH obtained from the reanalysis products with the ceilometer data showed better results from ERA5 and IMDAA rather than MERRA2. However, both IMDAA and MERRA2 were unable to capture the decaying of the ABL from the noon time peak during all the seasons. Distinct variability was observed in the absolute values of the ABLH obtained from both the observation and reanalysis datasets mainly due to the difference caused by the estimation methods used in the ABLH calculation. [ABSTRACT FROM AUTHOR]

In this study, the cloud macro-physical characteristics in Xiangyang of Hubei Province are statistically analyzed from the aspects of cloud occurrence frequency, number of cloud layers, and cloud base height by using the observation data of ceilometer from 2019 to 2021. The results are as follows. (1) The cloud coverage in Xiangyang is relatively high throughout the year, with an average cloud occurrence frequency of 61.3% in the three years. The frequency of cloud occurrence shows a seasonal variation of higher in summer but lower in winter, and a diurnal variation of higher level during nighttime but lower during daytime. (2) The cloud layer is dominated by single-layer clouds (78.3%), especially in winter (80.1%). In the multi-layer cloud system, two-layer clouds account for the largest proportion (18.5%). The occurrence frequency of multi-layer clouds decreases with the increase in the number of cloud layers, and it is usually high in summer but low in winter, which is mainly related to the relatively sufficient water vapor in summer and the strong convection caused by high temperatures. (3) For clouds with a cloud base height below 1.0 km, the occurrence frequency is 26% in January and 40% in July, indicating that the cloud distribution is relatively dispersed in January but relatively concentrated in July. However, for clouds with a cloud base height between 1.0 and 3.5 km, the occurrence frequency is 57% in January and 24% in July, that is, the cloud distribution is relatively concentrated in January, while relatively dispersed in July. (4) Convective precipitation clouds mainly occur from June to August, accounting for 83.3% of all convective precipitation clouds, and the probability of convective precipitation around the evening is the highest. In terms of cloud base height distribution, the average cloud base height of convective precipitation clouds is lower than that of all precipitation clouds, with a large occurrence frequency of low clouds.

Ceilometers are used routinely at aerodromes world-wide to measure the height and sky coverage fraction of cloud layers. This information, possibly combined with direct observations by human observers, contributes to the production of Meteorological Aerodrome Reports (METARs). Here, we present ampycloud, a new algorithm and associated Python package for automatic processing of ceilometer measurements, with the aim to characterize cloud layers above aerodromes. The ampycloud algorithm has been developed at the Swiss Federal Office of Meteorology and Climatology (MeteoSwiss) as part of the AMAROC (AutoMETAR/AutoReport rOund the Clock) program, to fully automate the creation of METARs at Swiss civil aerodromes. ampycloud is designed to work with no (direct) human supervision. The algorithm consists of three distinct, sequential steps that rely on agglomerative clustering methods and Gaussian mixture models to identify distinct cloud layers. The robustness of the ampycloud algorithm stems from the first processing step, simple and reliable. It constrains the two subsequent processing steps that are more sensitive, but also better suited to handle complex cloud distributions. The software implementation of the ampycloud algorithm takes the form of an eponym, pip-installable Python package developed on Github. The code is made accessible to the general community as an open-source software under the terms of the 3-Clause BSD license. [ABSTRACT FROM AUTHOR]

In May–June 2019, smoke plumes from wildfires in Alberta, Canada, were advected all the way to Europe. To analyze the evolution of the plumes and to estimate the amount of smoke aerosols transported to Europe, retrievals from the spaceborne lidar CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) were used. The plumes were located with the help of a trajectory analysis, and the masses of smoke aerosols were retrieved from the CALIOP observations. The accuracy of the CALIOP mass retrievals was compared with the accuracy of ground-based lidars/ceilometer near the source in North America and after the long-range transport in Europe. Overall, CALIOP and the ground-based lidars/ceilometer produced comparable results. Over North America the CALIOP layer mean mass was 30 % smaller than the ground-based estimates, whereas over southern Europe that difference varied between 12 % and 43 %. Finally, the CALIOP mass retrievals were compared with simulated aerosol concentrations from two reanalysis models: MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) and CAMS (Copernicus Atmospheric Monitoring System). The simulated total column aerosol optical depths (AODs) and the total column mass concentration of smoke agreed quite well with CALIOP observations, but the comparison of the layer mass concentration of smoke showed significant discrepancies. The amount of smoke aerosols in the model simulations was consistently smaller than in the CALIOP retrievals. These results highlight the limitations of such models and more specifically their limitation to reproduce properly the smoke vertical distribution. They indicate that CALIOP is a useful tool monitoring smoke plumes over secluded areas, whereas reanalysis models have difficulties in representing the aerosol mass in these plumes. This study shows the advantages of spaceborne aerosol lidars, e.g., being of paramount importance to monitor smoke plumes, and reveals the urgent need of future lidar missions in space. [ABSTRACT FROM AUTHOR]

Atmospheric aerosols are one of the main factors that contribute to poor air quality. These aerosols are mostly concentrated within the atmospheric boundary layer (ABL) and mixing layer (ML). The ABL extends from ground level to the lowest level of the troposphere directly affected by surface temperature, solar irradiance, the orography and its proximity to coastal areas, causing turbulence in a daily cycle. This turbulence controls the vertical mixing of aerosols and pollutants and their dispersion in the ML. Therefore, proper characterization of these layers is of crucial importance in numerical weather forecasting and climate models; however, their estimation nowadays presents some spatial and temporal limitations. In order to deal with these limitations and to assess the influence of different meteorological conditions on the temporal evolution of the aforementioned layers, the evolution of the ML over Madrid (Spain) has been studied for the year 2020 by means of ceilometer profiles fed into the STRATfinder algorithm. This algorithm is able to give reliable estimates of the height of the ABL (ABLH) and ML (MLH). The results are compared with the ECMWF-IFS model predictions, which is able to compute the MLH under any meteorological condition. Then, the influence of the meteorology in the estimation of MLHs was established by classifying data based on the season and six different prevalent synoptic meteorological situations defined using ground-level pressure fields, as well as by splitting the days into four periods (morning, daytime, evening and nighttime). Our results show that both datasets, the STRATfinder values and the ECMWF-IFS model computations, are very sensitive to the meteorological conditions that play a main role in the MLH temporal evolution. For instance, high solar irradiance and ground radiation cause high turbulence and convection that lead to a well-developed ML. In cases in which the ML is well developed, both methods show similar results, and there are therefore better correlations between them. On the contrary, the results presented here show that the presence of high relative humidity and low temperatures hamper the growth of the ML, causing different errors in both MLH estimations and poor correlations between them. Furthermore, the ECMWF-IFS model has shown a sharp decrease, identified as an artificial behavior from 16:00 UTC, because of the influence of low solar zenith angles and the temporal interpolation. The STRATfinder algorithm also shows a sharp decrease just before the sunset because of the way the algorithm distinguishes between the ML and the residual layer. Thus, this study concludes that the MLH temporal evolution still needs to be characterized using complementary tools, since the methods presented here are strongly affected by the meteorological conditions and do not show enough reliability to work individually. However, ceilometer measurements offer great potential as a correction tool for ABL heights derived from models involved in air pollution dispersion assessments. [ABSTRACT FROM AUTHOR]

This paper presents a study conducted in São Paulo, Brazil, where the planetary boundary layer height (PBLH) was determined using ceilometer data and the wavelet covariance transform method. The retrieved PBLH values were subsequently compared with the concentrations of CO2 and CH4 measured at three distinct experimental sites in the city. The period of study was July 2021. This study also included a comparison between ceilometer data and lidar data, which demonstrated the favorable applicability of the ceilometer data for PBLH estimation. An examination of the correlation between changes in average CO2 concentrations and PBLH values revealed stronger correlations for the IAG and UNICID stations, with correlation coefficients (ρ) of approximately −0.86 and −0.85, respectively, in contrast to the Pico do Jaraguá station, which exhibited a lower correlation coefficient of −0.42. When assessing changes in CH4 concentrations against variations in PBL height, the retrieved correlation coefficients were approximately −0.78 for IAG, −0.66 for UNICID, and −0.38 for Pico do Jaraguá. The results indicated that CO2/CH4 concentrations are negatively correlated with PBL heights, with CO2 concentrations showing more significant correlation than CH4. Additionally, among the three measurement stations, IAG measurements displayed the most substantial correlation. The results from this study contribute to the understanding of the relationship between PBLH and greenhouse gas concentrations, emphasizing the potential of remote sensing systems like ceilometers in monitoring and studying atmospheric processes. [ABSTRACT FROM AUTHOR]

In this work, we demonstrate a three-stage all-fiber master oscillator power amplifier (MOPA) system emitting over 1 W of the linearly polarized narrow-linewidth pulse output power with 10 kHz pulse repetition frequency and 400 ns pulse width without the amplified spontaneous emission (ASE) at ~1.5 µm. Initially, we analyze the effect of the ASE on the first derivative of backscatter intensity via a contrast experiment. The experiment results show that the noise intensity with angle of inclination is affected by the ASE of the amplifier, thereby decreasing the signal-to-noise ratio of the output power. The laser is characterized by a very low or no ASE level of the output signal when acquiring the first derivative of backscatter intensity with low noise. This condition provides a reference for improving the properties of the laser used for cloud detection. [ABSTRACT FROM AUTHOR]

Dynamics in atmospheric structures are analyzed using the Scale Relativity Theory in Schrödinger-type and Madelung-type scenarios. In the Schrödinger-type scenario, the group invariances of the special linear group SL(2R)-type under Riccati-type gauges implies morphological atmospheric manifestations through frequency modulation, particularly through period doubling. In the Madelung-type scenario, the same group invariances type, manifested through harmonic mappings, implies the functionality of atmospheric mass conductions through mass superconducting-type by scale transition from nondifferentiable atmospheric dynamics to differentiable atmospheric dynamics. The compatibility of these two scenarios under the correlations of atmospheric morphologies-functionalities implies Stoler-type coherences of the atmospheric dynamics through the removal of atmospheric turbulence by means of laminar channels. Finally, these theories are successfully employed to analyze the vertical atmospheric dynamics of cases of insect swarms. [ABSTRACT FROM AUTHOR]

Planetary Boundary Layer (PBL) parameterization schemes are employed to handle subgrid-scale processes on atmospheric models, playing a key role in accurately representing the atmosphere. Recent studies have shown that PBL schemes are particularly fundamental to the depiction of PBL height (PBLH), especially over the Amazon. In the present study, we investigated the performance of PBL schemes on the representation of meteorological variables, turbulent fluxes, PBL vertical structures, and PBLH over the central Amazon basin under dry conditions, taking advantage of observations from the Observations and Modeling of the Green Ocean Amazon campaign (GoAmazon2014/5) for validation and evaluation. Numerical experiments were carried out within the WRF model using eight PBL schemes for two dry periods from 2014 (typical year) and 2015 (El-Niño year), and results from the 1-km resolution domain were directly compared to hourly in situ observations. In general, all PBL schemes present good performance to reproduce meteorological variables, with nonlocal (local) PBL schemes producing better performance in the 2014 (2015) study period. All PBL schemes in general overestimate (>100%) daytime turbulent fluxes. Thermodynamic (daytime) vertical structures are better predicted than mechanical (nocturnal) ones. The local MYNN2.5 scheme showed the overall best performance for PBLH prediction, mainly at night. [ABSTRACT FROM AUTHOR]

Studies focusing on virga are rare, even though it is a commonly occurring phenomenon. In this study, we investigated aerosol backscatter profiles from a ceilometer located on The University of Texas at El Paso (UTEP) campus from 2015–2021 to identify virga events. Ceilometer data effectively captured virga events from regular precipitation based on the backscattering intensities. To characterize the virga phenomena, a systematic method was developed using ceilometer profiles, soundings, surface rain gauges, and radar data from the nearest National Weather Service (NWS) site. A total of 50 virga events were identified during the study period. These events appeared only during a specific time of the year, revealing a seasonal occurrence pattern. We identified and classified these virga events and investigated their impact on the surface measurements recorded by the on-campus Continuous Ambient Air Monitoring Station (CAMS). Virga events were classified as columnar and non-columnar events based on their aerosol profiles. We observed that during some of the columnar virga events, surface particulate matter (PM) levels displayed a sudden upward trend indicating aerosol loading in the surface layer after precipitation evaporation. In total, 20 of the virga events showed a columnar structure out of the 50 identified in this study. More detailed analysis of selected events shows that virga affects regional air quality. A significant result of this study is that analysis of sudden changes in local air quality needs to consider the possible effects of virga on the surface layer. [ABSTRACT FROM AUTHOR]

A comparative study and evaluation of boundary layer height (BLH) estimation was conducted during an experimental campaign conducted at the Cape Grim Air Pollution station, Australia, from 1 June to 13 July 2019. The temporal and spatial distributions of BLH were studied using data from a ceilometer, sodar, in situ meteorological measurements, and back-trajectory analyses. Generally, the BLH under continental sources is lower than that under marine sources. The BLH is featured with a shallow depth of 515 ± 340 m under the Melbourne/East Victoria continental source. Especially the mixed continental sources (Melbourne/East Victoria and Tasmania direction) lead to a rise in radon concentration and lower BLH. In comparison, the boundary layer reaches a higher averaged BLH value of 730 ± 305 m when marine air is prevalent. The BLH derived from ERA5 is positively biased compared to the ceilometer observations, except when the boundary layer is stable. The height at which wind profiles experience rapid changes corresponds to the BLH value. The wind flow within the boundary layer increased up to ∼200 m, where it then meandered up to ∼300 m. Furthermore, the statistic shows that BLH is positively associated with near-surface wind speed. This study firstly provides information on boundary layer structure in Cape Grim and the interaction with wind, which may aid in further evaluating their associated impacts on the climate and ecosystem. [ABSTRACT FROM AUTHOR]

The mass concentration of Asian dust in the atmosphere is an essential parameter of the atmospheric environment in East Asia. In April 2016, we conducted simultaneous observations using an optical particle counter (OPC) installed on a tethered balloon and a ceilometer in the Gobi Desert. We estimated the mass-extinction conversion factor MECF (gm-2) from the relationship between the dust extinction coefficient and dust mass concentration obtained by simultaneous observations. The MECF at Dalanzadgad in the Gobi Desert is 2.16 gm-2 at 910 nm and 1.91 gm-2 at 532 nm. A previous study on Asian dust showed that the values of the MECF were 1.78 gm-2 in Beijing, 1.40 gm-2 in Seoul, 1.18 gm-2 in Tsukuba (Japan), and 1.04 gm-2 at averaged AD-Net lidar stations in Japan. The MECF values decreased from the Asian dust source to the lee-side areas. This result suggests that the MECF depends on the size distribution of the dust. [ABSTRACT FROM AUTHOR]

Cloud and aerosol contribution to the Earth's radiative budget constitutes one of the most significant uncertainties in future climate projections. To distinguish between clouds and cloud-free air, atmospheric scientists have been using a wide range of instruments, techniques, and algorithms with various detection thresholds. However, since the change from a cloudy to a cloud-free atmosphere may be gradual and, in some cases, far from obvious, recent research is questioning where the threshold between both phases should be established. These considerations lead to contemplate a transition zone (TZ) between cloud and cloud-free conditions. In the present study, backscatter profiles obtained by a Vaisala CL31 ceilometer were processed to assess the transition zone. First, two widely used cloud detection algorithms were applied and compared: the method provided by the ceilometer manufacturer (Vaisala) and Cloudnetpy, the algorithm from ACTRIS Cloudnet, a project devoted to aerosol, clouds, and trace gases research. Second, a sensitivity analysis was applied to the backscatter and signal-to-noise ratio thresholds used for cloud detection in Cloudnetpy. This methodology has allowed us to assess the vertical distribution of clouds, aerosols, the TZ, and its frequency of occurrence. Results indicate a gradual transition in backscatter retrievals from cloud to cloud-free, where particles detected near cloud boundaries induced higher backscatter values than those found further away. Depending on the thresholds used, we observed a 9.3% (with an estimated range of uncertainty of 5.4 20%) variation in cloud occurrence which can be attributed to TZ conditions. Analysing the whole backscatter profile, we found as many TZ conditions as cloudy values, which emphasises the importance of studying the vertical distribution of the TZ. Moreover, the analysis of TZ occurrence in height and time revealed that such conditions concentrate below 800 m during night periods, although annual height-hour distributions involve a remarkable variability among seasons. These findings highlight the importance of either including an additional phase between 'pure clouds' and 'pure aerosols' or treating them as a continuum of suspended particles in the atmosphere. • Ceilometer backscatter retrievals show a gradual transition from cloud to cloud-free. • Cloud detection is influenced by the set of thresholds used. • There is a 9.3% (5.4 20%) variation in cloud occurrence, attributed to TZ conditions. • The vertical analysis revealed that TZ conditions are as frequent as cloudy ones. • Cloud-aerosol TZ conditions were mainly found below 800 m during night periods. [ABSTRACT FROM AUTHOR]

The lack of reliable and continuous measurements of the atmospheric boundary layer (ABL) height poses a significant problem for accurate weather forecasting and examining the intricate dynamics between the ABL and the free troposphere (FT). To address this crucial scientific problem, the present study investigates the ABL height from various simultaneous observations of multi-remote sensing instruments Micropulse lidar (MPL), Ceilometer (CL), Wind profiler radar (WPR) and Radiosonde (RS) and four different PBL schemes (Asymmetrical Convective Model version 2 (ACM2), Yonsei University (YSU), Mellor-Yamada Nakanishi and Nino level 2.5 (MYNN2), and Bougeault–Lacarrere (BouLac) during different sky and surface conditions. The diurnal variation of ABL heights between observation and model differs by ∼230 m. The ACM2 and MYNN2 show better performance (R > 0.85) of ABL height than other numerical schemes. The ABL height from different observations such as CL, WPR, MPL, RS and simulated ACM2 and MYNN2 is about 1098 ± 196 m, 1303 ± 217 m, 1461 ± 391 m, and 1716 ± 639 m, 1808 ± 407 m, and 1585 ± 393 m respectively, during the radiosonde launching time (∼11:00–12:00 IST). The difference in mean ABL height is observed due to their different measurement techniques and tracer identity between observation and model simulations. The study underscores a consistent and abrupt reduction in ABL height between observations (<480 m), model simulations (∼700 m), and re-analysis data sets (∼550 m) during wet-surface conditions, highlighting the model's ability to replicate consistent ABL behaviour in different surface conditions. While in cloudy conditions, the WRF-model underestimates ∼50–200 m than the observed ABL. This discrepancy is mainly observed due to the underestimation of sensible heat flux and downward shortwave radiation in model simulations. Due to the distinct ABL growth rate difference between the model (∼100–200 m/h) and observations (∼105–130 m/h), the time of attaining peak ABL height differs by one hour among them during different sky conditions. This is attributed to the large deviation in surface temperature, the incoming solar radiation, and the sensible heat fluxes. • This study explores ABL height from observations and four different PBL schemes during different sky and surface conditions. • The ACM2 and MYNN2 shows the better performance of ABL height than other numerical schemes. • SHF and downward SWR in model simulations leads differences in the ABL against observations in different conditions. • Slower growth rate of ABL during cloudy conditions delays reaching the peak ABL height by one hour than clear-sky. [ABSTRACT FROM AUTHOR]

This paper presents a study conducted in São Paulo, Brazil, where the planetary boundary layer height (PBLH) was determined using ceilometer data and the wavelet covariance transform method. The retrieved PBLH values were subsequently compared with the concentrations of CO2 and CH4 measured at three distinct experimental sites in the city. The period of study was July 2021. This study also included a comparison between ceilometer data and lidar data, which demonstrated the favorable applicability of the ceilometer data for PBLH estimation. An examination of the correlation between changes in average CO2 concentrations and PBLH values revealed stronger correlations for the IAG and UNICID stations, with correlation coefficients (ρ) of approximately −0.86 and −0.85, respectively, in contrast to the Pico do Jaraguá station, which exhibited a lower correlation coefficient of −0.42. When assessing changes in CH4 concentrations against variations in PBL height, the retrieved correlation coefficients were approximately −0.78 for IAG, −0.66 for UNICID, and −0.38 for Pico do Jaraguá. The results indicated that CO2/CH4 concentrations are negatively correlated with PBL heights, with CO2 concentrations showing more significant correlation than CH4. Additionally, among the three measurement stations, IAG measurements displayed the most substantial correlation. The results from this study contribute to the understanding of the relationship between PBLH and greenhouse gas concentrations, emphasizing the potential of remote sensing systems like ceilometers in monitoring and studying atmospheric processes.

The scope of this study is to analyze the variations in the mixing layer height (MLH) under different cloud conditions on a daily and monthly basis. For this scope, the data of the first five months from the Campbell ceilometer CS135 were analyzed. The instrument is operating in a rural place on Euboea Island (Greece), and the study presents preliminary results about the atmospheric profile of this area, which is also related to the air transport of the largest airport in Greece (Athen’s airport).

Cities may have local weather and climates that are significantly different from their surrounding rural areas due to the different physical characteristics of urban surfaces and emissions of substances, with the latter being modulated by the rhythm of the urban ecosystem. Radiative, thermal, moisture and aerodynamic properties of the urban surface influence cloud formation as well as their characteristics. By using in situ measurements as well as data from remote sensing instruments (ceilometers) located in the city center and its outskirts, urban impact on cloudiness over the city of Sofia is evaluated. It is found that the cloud base height over the city center reaches more than 200 m higher than that over the rural area. It is shown that clouds over the rural area are more persistent in cold months as well as in the afternoon in spring.

Atmospheric aerosols are one of the main factors that contribute to poor air quality. These aerosols are mostly concentrated within the atmospheric boundary layer (ABL) and mixing layer (ML). The ABL extends from ground level to the lowest level of the troposphere directly affected by surface temperature, solar irradiance, the orography and its proximity to coastal areas, causing turbulence in a daily cycle. This turbulence controls the vertical mixing of aerosols and pollutants and their dispersion in the ML. Therefore, proper characterization of these layers is of crucial importance in numerical weather forecasting and climate models; however, their estimation nowadays presents some spatial and temporal limitations. In order to deal with these limitations and to assess the influence of different meteorological conditions on the temporal evolution of the aforementioned layers, the evolution of the ML over Madrid (Spain) has been studied for the year 2020 by means of ceilometer profiles fed into the STRATfinder algorithm. This algorithm is able to give reliable estimates of the height of the ABL (ABLH) and ML (MLH). The results are compared with the ECMWF-IFS model predictions, which is able to compute the MLH under any meteorological condition. Then, the influence of the meteorology in the estimation of MLHs was established by classifying data based on the season and six different prevalent synoptic meteorological situations defined using ground-level pressure fields, as well as by splitting the days into four periods (morning, daytime, evening and nighttime). Our results show that both datasets, the STRATfinder values and the ECMWF-IFS model computations, are very sensitive to the meteorological conditions that play a main role in the MLH temporal evolution. For instance, high solar irradiance and ground radiation cause high turbulence and convection that lead to a well-developed ML. In cases in which the ML is well developed, both methods show similar results, and there are therefore better correlations between them. On the contrary, the results presented here show that the presence of high relative humidity and low temperatures hamper the growth of the ML, causing different errors in both MLH estimations and poor correlations between them. Furthermore, the ECMWF-IFS model has shown a sharp decrease, identified as an artificial behavior from 16:00 UTC, because of the influence of low solar zenith angles and the temporal interpolation. The STRATfinder algorithm also shows a sharp decrease just before the sunset because of the way the algorithm distinguishes between the ML and the residual layer. Thus, this study concludes that the MLH temporal evolution still needs to be characterized using complementary tools, since the methods presented here are strongly affected by the meteorological conditions and do not show enough reliability to work individually. However, ceilometer measurements offer great potential as a correction tool for ABL heights derived from models involved in air pollution dispersion assessments.

Ceilometer measurements of aerosol backscatter profiles have been widely used to provide continuous planetary boundary layer height (PBLHT) estimations. To investigate the robustness of ceilometer-estimated PBLHT under different atmospheric conditions, we compared ceilometer- and radiosonde-estimated PBLHTs using multiple years of U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) ceilometer and balloon-borne sounding data at ARM fixed-location atmospheric observatories and from ARM mobile facilities deployed around the world for various field campaigns. These observatories cover from the tropics to the polar regions and over both ocean and land surfaces. Statistical comparisons of ceilometer-estimated PBLHTs from the Vaisala CL31 ceilometer data with radiosonde-estimated PBLHTs from the ARM PBLHT-SONDE Value-added Product (VAP) are performed under different atmospheric conditions including stable and unstable atmospheric boundary layer, low-level cloud-free conditions, and cloudy conditions at these ARM observatories. Under unstable conditions, good comparisons are found between ceilometer- and radiosonde-estimated PBLHTs at ARM low- and mid-latitude land observatories. However, it is still challenging to obtain reliable PBLHT estimations over ocean surfaces even using radiosonde data. Under stable conditions, ceilometer- and radiosonde-estimated PBLHTs have weak correlations. We compare different PBLHT estimations utilizing the Heffter, the Liu–Liang, and the bulk Richardson number methods applied to radiosonde data with ceilometer-estimated PBLHT. We find that ceilometer-estimated PBLHT compares better with the Liu–Liang method under unstable conditions and compares better with the bulk Richardson number method under stable conditions. [ABSTRACT FROM AUTHOR]

Observations of mixing layer height (MLH), its dynamics and the extent of homogeneity of the mixing layer are important in the study of air pollution as well as meteorological and air quality model validation. They can contribute to improvements in the application of satellite aerosol optical depth (AOD) products to ground fine particulate matter (PM2.5) estimation that can potentially provide synoptic-scale monitoring of fine particulate matter. Ceilometers have shown great potential for continuous monitoring of MLH and aerosol profiles within the boundary layer. In this study, we report an automated quality control/quality assurance (QC/QA) method that improves the consistency of MLH retrievals from ceilometer measurements and present measurements of MLH variation in New York City (NYC) as observed by ceilometers in summer and winter seasons. Distinct issues due to SNR and quality of overlap correction are addressed within the QC/QA method. We also analyze the diurnal and seasonal correlations between ceilometer-attenuated backscatter and ground-level PM2.5 as a function of height, time of day, and season, to shed light on the homogeneity of aerosol vertical mixing within the MLH, as well as the correlation between aerosol optical properties and PM2.5. The results show that the overall correlation in summer is better than in winter. This correlation decreases with increasing height but the degradation is less severe in summer than in winter, which is qualitatively consistent with urban heating models of convective mixing. However, no significant diurnal variation of the correlation coefficient was observed for both seasons. We also found that the linear regression slope between ceilometer-attenuated backscatter coefficients and ground PM2.5 shows seasonal variation, which can be partially explained by the difference in aerosol size distribution and aerosol species between summer and winter. Finally, we investigated the homogeneity of aerosol vertical distribution within the mixing layer (ML) during the daytime. The results indicate that the aerosols are well-mixed within the lower part of ML up to 500 m. [ABSTRACT FROM AUTHOR]

Cloud and aerosol lidars measuring backscatter and depolarization ratio are the most suitable lidars to detect cloud phase (liquid, ice, or mixed phase). However, such instruments are not widely deployed as part of operational networks. In this study, we propose a new algorithm to detect supercooled liquid water containing clouds (SLCC) based on ceilometers measuring only co-polarization backscatter. We utilize observations collected at Davis, Antarctica, where low-level, mixed-phase clouds, including supercooled liquid water (SLW) droplets and ice crystals, remain poorly understood due to the paucity of ground-based observations. A 3-month set of observations were collected during the austral summer of November 2018 to February 2019, with a variety of instruments including a depolarization lidar and a W-band cloud radar which were used to build a two-dimensional cloud phase mask distinguishing SLW and mixed-phase clouds. This cloud phase mask is used as the reference to develop a new algorithm based on the observations of a single polarization ceilometer operating in the vicinity for the same period. Deterministic and data-driven retrieval approaches were evaluated: an extreme gradient boosting (XGBoost) framework ingesting backscatter average characteristics was the most effective method at reproducing the classification obtained with the combined radar–lidar approach with an accuracy as high as 0.91. This study provides a new SLCC retrieval approach based on ceilometer data and highlights the considerable benefits of these instruments to provide intelligence on cloud phase in polar regions that usually suffer from a paucity of observations. Finally, the two algorithms were applied to a full year of ceilometer observations to retrieve cloud phase and frequency of occurrences of SLCC: SLCC was present 29 ± 6 % of the time for T19 and 24 ± 5 % of the time for G22-Davis over that annual cycle. [ABSTRACT FROM AUTHOR]

This study presents a synergistic approach to the study of the aerosol optical and microphysical properties measured in La Palma, Spain, during the 2021 eruption of the Cumbre Vieja volcano (from 19 September to 13 December 2021). This study aims to characterize the different phases of the volcanic eruption using the spatio-temporal evolution of the event together with the mass concentration quantification of four different atmospheric layers. The impact of the plume's pathway that reached the South of France is analyzed. Here, passive and active remote sensors were used, namely CL51 and CL61 ceilometers and AERONET sunphotometers. The attenuated backscattering ranged from 0.8 to 9.1 × 10 − 6 (msr) − 1 and the volume depolarization ratio measured nearby the volcano was up to 0.3. The ash plume remained within the first 4 km agl, with intense episodes that reached mean aerosol optical depth values of up to 0.4. Thirteen study cases were selected where coarse mode was dominant over fine mode. For the data selection, the fine and coarse lidar ratios found were 3.9 ± 0.8 and 21.0 ± 3.8 sr in the north and 6.9 ± 1.8 and 30.1 ± 10.3 sr in the south. The ash mass concentration reached moderate levels with maximum values of up to 313.7 μ gm − 3 . [ABSTRACT FROM AUTHOR]

Network Function Virtualization (NFV) offers an alternate method to design, deploy and manage network services. The NFV decouples network functions from the dedicated hardware and moves them to the virtual servers so that they can run in the software. One of the major strengths of the NFV is its ability to dynamically extend or reduce resources allocated to Virtual Network Functions (VNF) as needed and at run-time. There is a need for a comprehensive metering component in the cloud to store and process the metrics/samples for efficient auto-scaling or load-management of the VNF. In this paper, we propose an integrating framework for efficient auto-scaling of VNF using Gnocchi; a time-series database that is integrated within the framework to store, handle and index the time-series data. The objective of this study is to validate the efficacy of employing Gnocchi for auto-scaling of VNF, in terms of aggregated data points, database size, data recovery speed, and memory consumption. The employed methodology is to perform a detailed empirical analysis of the proposed framework by deploying a fully functional cloud to implement NFV architecture using several OpenStack components including Gnocchi. Our results show a significant improvement over the legacy Ceilometer configuration in terms of lower metering storage size, less memory utilization in processing and management of metrics, and reduced time delay in retrieving the monitoring data to evaluate alarms for the auto-scaling of VNF. [ABSTRACT FROM AUTHOR]

In this study, we present primary results from the aErosol Vertical profiling with lIdars And droNes (EVIAN) campaign, under the ATMO-ACCESS project, which took place in Nicosia, Cyprus (35°10′21″ N, 33°21′54″ E). Measurements from different instrument techniques, e.g., lidar, ceilometer and “drone-borne” Optical Particle Counter (OPC), have been used in a synergistic way during the campaign to derive the aerosol properties. This study focuses on the comparison of the drone-borne and ceilometer retrievals, mainly in the Planetary Boundary Layer (PBL), and the synergistic use of the above-mentioned instruments in analyzing the geometrical and optical properties of the detected aerosol layers to improve the determination of the lidar overlap function.

Dynamics in atmospheric structures are analyzed using the Scale Relativity Theory in Schrödinger-type and Madelung-type scenarios. In the Schrödinger-type scenario, the group invariances of the special linear group SL(2R)-type under Riccati-type gauges implies morphological atmospheric manifestations through frequency modulation, particularly through period doubling. In the Madelung-type scenario, the same group invariances type, manifested through harmonic mappings, implies the functionality of atmospheric mass conductions through mass superconducting-type by scale transition from nondifferentiable atmospheric dynamics to differentiable atmospheric dynamics. The compatibility of these two scenarios under the correlations of atmospheric morphologies-functionalities implies Stoler-type coherences of the atmospheric dynamics through the removal of atmospheric turbulence by means of laminar channels. Finally, these theories are successfully employed to analyze the vertical atmospheric dynamics of cases of insect swarms.

Planetary Boundary Layer (PBL) parameterization schemes are employed to handle subgrid-scale processes on atmospheric models, playing a key role in accurately representing the atmosphere. Recent studies have shown that PBL schemes are particularly fundamental to the depiction of PBL height (PBLH), especially over the Amazon. In the present study, we investigated the performance of PBL schemes on the representation of meteorological variables, turbulent fluxes, PBL vertical structures, and PBLH over the central Amazon basin under dry conditions, taking advantage of observations from the Observations and Modeling of the Green Ocean Amazon campaign (GoAmazon2014/5) for validation and evaluation. Numerical experiments were carried out within the WRF model using eight PBL schemes for two dry periods from 2014 (typical year) and 2015 (El-Niño year), and results from the 1-km resolution domain were directly compared to hourly in situ observations. In general, all PBL schemes present good performance to reproduce meteorological variables, with nonlocal (local) PBL schemes producing better performance in the 2014 (2015) study period. All PBL schemes in general overestimate (>100%) daytime turbulent fluxes. Thermodynamic (daytime) vertical structures are better predicted than mechanical (nocturnal) ones. The local MYNN2.5 scheme showed the overall best performance for PBLH prediction, mainly at night.

Four methods have been used for the estimation of the total cloud amount and cloud amount for low clouds: visual observations, the Long method applied on pyranometer measurements, the Automatic Partial Cloud Amount Detection Algorithm (APCADA) method applied on pyrgeometers measurements, and ceilometer measurements of the cloud base height. Records from meteorological observers indicate that clear days (0–1 octa) represent the most frequent cloud amount for low clouds. In contrast, the total cloud amount is more aleatory. Results obtained from the Long method show maximum frequency in the extreme cloud amount values. The APCADA method also indicates the predominance of cloudless skies. The ceilometer method shows a predominance of completely clear skies, but the completely cloudy (8 octas) is the second most frequent case. Automatic methods report more cloudless and overcast skies than the observer. Automatic methods agree with the visual method or differ in ±1 octa for 60–76% cases for low cloud amount and for 56–63% cases for total cloud amount. In general, low cloud amount agrees more with observer measurements than total cloud amount and the automatic methods underestimated total cloud amount observer values possibly due to the difficulty in monitoring high clouds. [ABSTRACT FROM AUTHOR]

Infrared hyperspectral remote sensing has been widely used in the field of meteorology. Many scientists have carried out research on inversion methods of meteorological elements such as thermodynamic profile, boundary layer height, cloud base height, etc. In this study, a method based on machine learning for cloud detection using ground-based infrared hyperspectral radiation data is proposed. The features of outliers, the cloudy and cloud-free data of Atmospheric Emitted Radiance Interferometer (AERI) radiation are extracted. The "reference values" of cloudy and cloud-free are determined based on the observation data of Vaisala CL31 ceilometer within the time range of 8 min before the corresponding time of AERI. A support vector machine (SVM) algorithm is used for training. The dataset comes from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site and North Slope Alaska (NSA) site from 2015 to 2017, and the ARM West Antarctic Radiation Experiment (AWARE) site in 2016 is also analyzed. The instruments used in this paper include AERI, ceilometer, etc. The experimental results reveal that the agreement of cloud detection results between the proposed algorithm and ceilometer is about 93% at each site. However, for high clouds or optically thin clouds, the agreement will decrease. [ABSTRACT FROM AUTHOR]

In this manuscript, multifractal theories of motion based on scale relativity theory are considered in the description of atmospheric dynamics. It is shown that these theories have the potential to highlight nondimensional mass conduction laws that describe the propagation of atmospheric entities. Then, using special operational procedures and harmonic mappings, these equations can be rewritten and simplified for their plotting and analysis to be performed. The inhomogeneity of these conduction phenomena is analyzed, and it is found that it can fluctuate and increase at certain fractal dimensions, leading to the conclusion that certain atmospheric structures and phenomena of either atmospheric transmission or stability can be explained by atmospheric fractal dimension inversions. Finally, this hypothesis is verified using ceilometer data throughout the atmospheric profiles. [ABSTRACT FROM AUTHOR]

Blowing snow is a common weather phenomenon in Antarctica and plays an important role in the water vapor cycle and ice sheet mass balance. Although it has a significant impact on the climate of Antarctica, people do not know much about this process. Fog events are difficult to distinguish from blowing snow events using existing detection algorithms by a ceilometer. In this study, based on ceilometer, the meteorological parameters observed by surface meteorology systems are further combined to detect blowing snow and fog using the AdaBoost algorithm. The weather phenomena recorded by human observers are 'true'. The dataset is collected from 1 January 2016 to 31 December 2016 at the AWARE site. Among them, three-quarters of the data are used as the training set and the rest of the data as the testing set. The classification accuracy of the proposed algorithm for the testing set is about 94%. Compared with the Loeb method, the proposed algorithm can detect 89.12% of blowing snow events and 76.10% of fog events, while the Loeb method can only identify 64.29% of blowing snow events and 31.87% of fog events. [ABSTRACT FROM AUTHOR]

In the present paper, correlations between multifractality and stochasticity in atmospheric dynamics are investigated. Starting with two descriptions of atmospheric scenarios, one based on scale relativity theory and another based on stochastic theory, correspondences between parameters and variables belonging to both scenarios are found. In such a context, by replacing an atmospheric conservative passive additive with a non-differentiable component of the atmospheric multifractal velocity, stochastic evolution equations are found for this component, which reveal the multifractal variational transport coefficient and the multifractal molecular diffusion coefficient, along with the multifractal inhomogeneity variation. Furthermore, equations which describe a multifractal Reynolds number and singularity spectrum are also found. Finally, these theoretical results are validated through remote sensing data obtained with the aid of a ceilometer platform. [ABSTRACT FROM AUTHOR]

Cloud and aerosol lidars measuring backscatter and depolarization ratio are most suitable instruments to detect cloud phase (liquid, ice, or mixed phase). However, such instruments are not widely deployed as part of operational networks. In this study, we propose a new algorithm to detect supercooled liquid water clouds based solely on ceilometers measuring only co-polarisation backscatter. We utilise observations collected at Davis, Antarctica, where low-level, mixed phase clouds, including supercooled liquid water (SLW) droplets and ice crystals remain poorly understood, due to the paucity of ground-based observations. A 3-month set of observations were collected during the austral summer of November 2018-February 2019, with a variety of instruments including a depolarization lidar and a W-Band cloud radar which were used to build a 2-dimensional cloud phase mask distinguishing SLW and mixed phase clouds. This cloud phase mask is used as the reference to develop a new algorithm based on the observations of a single polarisation ceilometer operating in the vicinity for the same period. Deterministic and data-driven retrieval approaches were evaluated: an extreme gradient boosting (XGBoost) framework ingesting backscatter average characteristics was the most effective method at reproducing the classification obtained with the combined radar-lidar approach with an accuracy as high as 0.91. This study provides a new SLW retrieval approach based solely on ceilometer data and highlights the considerable benefits of these instruments to provide intelligence on cloud phase in polar regions that usually suffer from a paucity of observations. [ABSTRACT FROM AUTHOR]

A comparative study and evaluation of boundary layer height (BLH) estimation was conducted during an experimental campaign conducted at the Cape Grim Air Pollution station, Australia, from 1 June to 13 July 2019. The temporal and spatial distributions of BLH were studied using data from a ceilometer, sodar, in situ meteorological measurements, and back-trajectory analyses. Generally, the BLH under continental sources is lower than that under marine sources. The BLH is featured with a shallow depth of 515 ± 340 m under the Melbourne/East Victoria continental source. Especially the mixed continental sources (Melbourne/East Victoria and Tasmania direction) lead to a rise in radon concentration and lower BLH. In comparison, the boundary layer reaches a higher averaged BLH value of 730 ± 305 m when marine air is prevalent. The BLH derived from ERA5 is positively biased compared to the ceilometer observations, except when the boundary layer is stable. The height at which wind profiles experience rapid changes corresponds to the BLH value. The wind flow within the boundary layer increased up to ∼200 m, where it then meandered up to ∼300 m. Furthermore, the statistic shows that BLH is positively associated with near-surface wind speed. This study firstly provides information on boundary layer structure in Cape Grim and the interaction with wind, which may aid in further evaluating their associated impacts on the climate and ecosystem.

Better understanding of aerosol-cloud interaction processes is an important aspect to quantify the role of clouds and aerosols in the climate system. There have been significant efforts to explain the ways aerosols modulate cloud properties. However, from the observational point of view, it is indeed challenging to observe and/or verify some of these processes because no single instrument or platform is proven sufficient. With this motivation, a unique set of observational field campaigns named Balloon borne Aerosol Cloud Interaction Studies (BACIS) is proposed and conducted using balloon borne in-situ measurements in addition to the ground-based (Lidars, MST radar, LAWP, MWR, Ceilometer) and space borne (CALIPSO) remote sensing instruments from Gadanki (13.45° N, 79.2° E). So far, 15 campaigns have been conducted as a part of BACIS campaigns from 2017 to 2020. This paper presents the concept of observational approach, lists the major objectives of the campaigns, describes the instruments deployed, and discusses results from selected campaigns. Consistency in balloon borne measurements is assessed using the data from simultaneous observations of ground-based, space borne remote sensing instruments. A good agreement is found among multi-instrumental observations. Balloon borne in-situ profiling is found to complement the information provided by ground-based and/or space borne measurements. A combination of the Compact Optical Backscatter AerosoL Detector (COBALD) and Cloud Particle Sensor (CPS) sonde is employed for the first time to discriminate cloud and aerosol in an in-situ profile. A threshold value of COBALD color index (CI) for ice clouds is found to be between 18 and 20 and CI values for coarse mode aerosol particle range between 11 and 15. Using the data from balloon measurements, the relationship between cloud and aerosol is quantified for the liquid clouds. A statistically significant slope (aerosol-cloud interaction index) of 0.77 (0.86) found between aerosol back scatter from 300 m (400 m) below the cloud base and cloud particle count within the cloud indicates the role of aerosol in the cloud activation process. In a nutshell, the results presented here demonstrate the observational approach to quantify aerosol-cloud interactions and paves the way for further investigations using the approach. [ABSTRACT FROM AUTHOR]

The objective of this work is to evaluate GOES-R (Geostationary Operational Environmental Satellites-R series) data-based fog conditions which occurred during the C-FOG (Toward Improving Coastal Fog Prediction) field campaign. The C-FOG campaign was designed to advance understanding of fog formation, development, and dissipation over coastal environments to improve predictability. The project took place along coastlines and open water environments of eastern Canada (Nova Scotia, and the Island of Newfoundland) during August−October of 2018 where environmental conditions play an important role for late season fog formation. During the C-FOG field campaign, coastal instruments were mainly located at the Ferryland supersite, Newfoundland, with two main sites, and five satellite sites, as well as on the Research Vessel Hugh R. Sharp. Key in-situ measurement instruments included microphysical, meteorological, radiation, and aerosol sensors. A fog spectral probe was used for measuring droplet spectra from 1–50 µm at the Ferryland supersite. A laser precipitation monitor with 100 µm to 10 mm size range and an optical particle counter with 0.3–17 µm at 16 spectral channels provided information for fog and drizzle discrimination. Remote sensing platforms, e.g. profiling microwave radiometer, ceilometer, microwave rain radar, lidar, meteorological towers, tethered balloons, and GOES-R products for fog coverage, and droplet size and liquid water path) were used to evaluate fog over horizontal and vertical dimensions. Results suggest that effective radius, phase, liquid water path, and liquid water content values obtained from GOES-R and the profiling microwave radiometer are comparable to ground-based in-situ observations. It is concluded that integration of observations and nowcasting products may help improve short-term local fog predictions. [ABSTRACT FROM AUTHOR]

An improved version of the near-real-time decision tool PARAFOG (PFG2) is presented to retrieve pre-fog alert levels and to discriminate between radiation (RAD) and stratus lowering (STL) fog situations. PFG2 has two distinct modules to monitor the physical processes involved in RAD and STL fog formation and is evaluated at European sites. The modules are based on innovative fuzzy logic algorithms to retrieve fog alert levels (low, moderate, high) specific to RAD/STL conditions, minutes to hours prior to fog onset. The PFG2-RAD module assesses also the thickness of the fog. Both the PFG2-RAD and PFG2-STL modules rely on the combination of visibility observations and automatic lidar and ceilometer (ALC) measurements. The overall performance of the PFG2-RAD and PFG2-STL modules is evaluated based on 9 years of measurements at the SIRTA (Instrumented Site for Atmospheric Remote Sensing Research) observatory near Paris and up to two fog seasons at the Paris-Roissy, Vienna, Munich, and Zurich airports. At all sites, pre-fog alert levels retrieved by PFG2 are found to be consistent with the local weather analysis. The advanced PFG2 algorithm performs with a hit rate of about 100 % for both considered fog types and presents a false alarm ratio on the order of 10 % (30 %) for RAD (STL) fog situations. Finally, the first high alerts that result in a subsequent fog event are found to occur for periods of time ranging from - 120 min to fog onset, with the first high alerts occurring earlier for RAD than STL cases. [ABSTRACT FROM AUTHOR]

Ceilometer measurements of aerosol backscatter profiles have been widely used to provide continuous PBLHT estimations. To investigate the robustness of ceilometer-estimated PBLHT under different atmospheric conditions, we compared ceilometer- and radiosonde-estimated PBLHTs using long term U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) ceilometer and balloon-borne sounding data at three ARM fixed-location atmospheric observatories and from three ARM mobile observatories deployed around the world for various field campaigns, which cover from Tropics to Polar regions and over both ocean and land surfaces. Statistical comparisons of ceilometer-estimated PBLHTs from the Vaisala CL31 ceilometer data with radiosonde-estimated PBLHTs from the ARM PBLHT-SONDE Value-added Product (VAP) are performed under different atmospheric conditions including stable and unstable atmospheric boundary layer, low-level cloud-free, and cloudy conditions at these ARM observatories. Under unstable atmospheric boundary layer conditions, good comparisons are found between ceilometer- and radiosonde-estimated PBLHTs at ARM low- and mid-latitude land observatories. However, it is still challenging to obtain reliable PBLHT estimations over ocean surfaces even using radiosonde data. Under stable atmospheric boundary layer conditions, ceilometer- and radiosonde-estimated PBLHTs have weak correlations. Among different PBLHT estimations utilizing the Heffter, the Liu-Liang, and the bulk Richardson number methods in the ARM PBLHT-SONDE VAP, ceilometer-estimated PBLHTs have better comparisons with the Liu-Liang method under unstable and with the bulk Richardson number method under stable atmospheric boundary layer conditions. [ABSTRACT FROM AUTHOR]

Observations of mixing layer height (MLH), its dynamics and the extent of homogeneity of the mixing layer are important in the study of air pollution as well as meteorological and air quality model validation. They can contribute to improvements in the application of satellite aerosol optical depth (AOD) products to ground fine particulate matter (PM2.5) estimation that can potentially provide synoptic-scale monitoring of fine particulate matter. Ceilometers have shown great potential for continuous monitoring of MLH and aerosol profiles within the boundary layer. In this study, we report an automated quality control/quality assurance (QC/QA) method that improves the consistency of MLH retrievals from ceilometer measurements and present measurements of MLH variation in New York City (NYC) as observed by ceilometers in summer and winter seasons. Distinct issues due to SNR and quality of overlap correction are addressed within the QC/QA method. We also analyze the diurnal and seasonal correlations between ceilometer-attenuated backscatter and ground-level PM2.5 as a function of height, time of day, and season, to shed light on the homogeneity of aerosol vertical mixing within the MLH, as well as the correlation between aerosol optical properties and PM2.5. The results show that the overall correlation in summer is better than in winter. This correlation decreases with increasing height but the degradation is less severe in summer than in winter, which is qualitatively consistent with urban heating models of convective mixing. However, no significant diurnal variation of the correlation coefficient was observed for both seasons. We also found that the linear regression slope between ceilometer-attenuated backscatter coefficients and ground PM2.5 shows seasonal variation, which can be partially explained by the difference in aerosol size distribution and aerosol species between summer and winter. Finally, we investigated the homogeneity of aerosol vertical distribution within the mixing layer (ML) during the daytime. The results indicate that the aerosols are well-mixed within the lower part of ML up to 500 m.

This study presents a synergistic approach to the study of the aerosol optical and microphysical properties measured in La Palma, Spain, during the 2021 eruption of the Cumbre Vieja volcano (from 19 September to 13 December 2021). This study aims to characterize the different phases of the volcanic eruption using the spatio-temporal evolution of the event together with the mass concentration quantification of four different atmospheric layers. The impact of the plume’s pathway that reached the South of France is analyzed. Here, passive and active remote sensors were used, namely CL51 and CL61 ceilometers and AERONET sunphotometers. The attenuated backscattering ranged from 0.8 to 9.1 × 10−6 (msr)−1 and the volume depolarization ratio measured nearby the volcano was up to 0.3. The ash plume remained within the first 4 km agl, with intense episodes that reached mean aerosol optical depth values of up to 0.4. Thirteen study cases were selected where coarse mode was dominant over fine mode. For the data selection, the fine and coarse lidar ratios found were 3.9 ± 0.8 and 21.0 ± 3.8 sr in the north and 6.9 ± 1.8 and 30.1 ± 10.3 sr in the south. The ash mass concentration reached moderate levels with maximum values of up to 313.7 μgm−3.

A quantitative comparison study for Raman lidar and ceilometer observations, and for model simulations of mass concentration estimates of smoke particles is presented. Layers of biomass burning aerosol particles were observed in the lower troposphere, at 2 to 5 km height on 4 to 6 June 2019, over Kuopio, Finland. These long-range-transported smoke particles originated from a Canadian wildfire event. The most pronounced smoke plume detected on 5 June was intensively investigated. Optical properties were retrieved from the multi-wavelength Raman polarization lidar Polly XT. Particle linear depolarization ratios (PDRs) of this plume were measured to be 0.08±0.02 at 355 nm and 0.05±0.01 at 532 nm, suggesting the presence of partly coated soot particles or particles that have mixed with a small amount of dust or other non-spherical aerosol type. The layer-mean PDR at 355 nm (532 nm) decreased during the day from ∼0.11 (0.06) in the morning to ∼0.05 (0.04) in the evening; this decrease with time could be linked to the particle aging and related changes in the smoke particle shape properties. Lidar ratios were derived as 47±5 sr at 355 nm and 71±5 sr at 532 nm. A complete ceilometer data processing for a Vaisala CL51 ceilometer is presented from a sensor-provided attenuated backscatter coefficient to particle mass concentration (including the water vapor correction for high latitude for the first time). Aerosol backscatter coefficients (BSCs) were measured at four wavelengths (355, 532, 1064 nm from Polly XT and 910 nm from CL51). Two methods, based on a combined lidar and sun-photometer approach, are applied for mass concentration estimations from both Polly XT and the ceilometer CL51 observations. In the first method, no. 1, we used converted BSCs at 532 nm (from measured BSCs) by corresponding measured backscatter-related Ångström exponents, whereas in the second method, no. 2, we used measured BSCs at each wavelength independently. A difference of ∼12 % or ∼36 % was found between Polly XT and CL51 estimated mass concentrations using method no. 1 or no. 2, showing the potential of mass concentration estimates from a ceilometer. Ceilometer estimations have an uncertainty of ∼50 % in the mass retrieval, but the potential of the data lies in the great spatial coverage of these instruments. The mass retrievals were compared with the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) meteorological and aerosol reanalysis. The inclusion of dust (as indicated by MERRA-2 data) in the retrieved mass concentration is negligible considering the uncertainties, which also shows that ceilometer observations for mass retrievals can be used even without exact knowledge of the composition of the smoke-dominated aerosol plume in the troposphere. [ABSTRACT FROM AUTHOR]

Since May 2017 and August 2018, two ground-based MAX-DOAS (multi-axis differential optical absorption spectroscopy) instruments have been continuously recording daytime spectral UV–visible measurements in the northwest (University of Natural Resources and Life Sciences (BOKU) site) and south (Arsenal site), respectively, of the Vienna city center (Austria). In this study, vertical aerosol extinction (AE) profiles, aerosol optical depth (AOD), and near-surface AE are retrieved from MAX-DOAS measurements recorded on cloud-free days applying the Bremen Optimal estimation REtrieval for Aerosols and trace gaseS (BOREAS) algorithm. Measurements of atmospheric profiles of pressure and temperature obtained from routinely performed sonde ascents are used to calculate box-air-mass factors and weighting functions for different seasons. The performance of BOREAS was evaluated against co-located ceilometer, sun photometer, and in situ instrument observations covering all four seasons. The results show that the vertical AE profiles retrieved from the BOKU UV–visible MAX-DOAS observations are in very good agreement with data from the co-located ceilometer, reaching correlation coefficients (R) of 0.936–0.996 (UV) and 0.918–0.999 (visible) during the fall, winter, and spring seasons. Moreover, AE extracted using the lowest part of MAX-DOAS vertical profiles (up to 100 m above ground) is highly consistent with near-surface ceilometer AE (R>0.865 and linear regression slopes of 0.815–1.21) during the fall, winter, and spring seasons. A strong correlation is also found for the BOREAS-based AODs when compared to the AERONET ones. Notably, the highest correlation coefficients (R=0.953 and R=0.939 for UV and visible, respectively) were identified for the fall season. While high correlation coefficients are generally found for the fall, winter, and spring seasons, the results are less reliable for measurements taken during summer. For the first time, the spatial variability of AOD and near-surface AE over the urban environment of Vienna is assessed by analyzing the retrieved and evaluated BOREAS aerosol profiling products in terms of different azimuth angles of the two MAX-DOAS instruments and for different seasons. We found that the relative differences of averaged AOD between different azimuth angles are 7–13 % , depending on the season. Larger relative differences of up to 32 % are found for near-surface AE in the different azimuthal directions. This study revealed the strong capability of BOREAS to retrieve AE profiles, AOD, and near-surface AE over urban environments and demonstrated its use for identifying the spatial variability of aerosols in addition to the temporal variation. [ABSTRACT FROM AUTHOR]