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Clouds play a pivotal role in determining Earth's climate, impacting several atmospheric processes influencing the weather. The study explores the temporal variations in cloud base height (CBH) over Pune, a tropical station, from 2017 to 2023 using a Laser-Based Ceilometer with a range of 0–7500 m. Our analysis shows seasonal trends in CBH, with the monsoon season exhibiting unique characteristics showing the lowest average CBH and minimal diurnal changes during the study period. Conversely, the pre-monsoon, post-monsoon, and winter season show a gradual rise of CBH in the morning, maintaining higher levels until late afternoon, followed by a decline in the evening. Analysis of the diurnal frequency of cloud occurrence at 500 m intervals reveals the monsoon season's dominance in the 500 m to 1000 m layer. Throughout the year, low cloud bases (CBH <2000 m) are most frequent, outpacing the frequency of mid and high cloud bases. High cloud base (7500 < CBH > 6000 m) is the least common, showing a semi-diurnal pattern in winter with peaks around noon and midnight. These findings not only enhance our understanding of Pune's atmospheric behaviour but also offer valuable information for weather prediction, climate modelling, and environmental monitoring. [ABSTRACT FROM AUTHOR]

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]

The detection of the vertical profiles of atmospheric variables or aerosols is a vital component in the accurate calculation of the atmospheric boundary layer height (ABLH). In many existing techniques, the precise ABLH detection has poor resource consumption, heterogeneous IoT conditions, lack of interoperability, and online and offline analyzers overdue are impacted by the processing of high streaming data from the ceilometer. Hence, a novel Edge AI cosmos blockchain distributed network is proposed to eliminate the efficient lowering parameters to provide a user-scalable networking based on a deep learning algorithm, in which the cosmos ledger blockchain method gets the data without affecting its precision or specificity, eliminates interoperability, increases usability. Moreover, the existing techniques has no real-time adjustment when processing the high streaming data. Hence, a model Real-time batch scheduling technique has been introduced to reduce a significant amount of computing power. In existing techniques, the scheduling process is very complicated as the ABLH layer attribution, precipitation, lofted aerosol layers, low aerosol conditions, and clouds. To overcome these issues, a gubernatorial algorithm is used to detect the ABLH value hourly which is gathered and stored data in a very optimized and efficient manner. Overall, the proposed technique compares effective data management and produces a computer environment which is optimal for ABLH. [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.

This work introduces CAECENET, a new system capable of automatically retrieving columnar and vertically-resolved aerosol properties running the GRASP (Generalized Retrieval of Atmosphere and Surface Properties) algorithm using sun-sky photometer (aerosol optical depth, AOD; and sky radiance measurements) and ceilometer (range corrected signal; RCS) data as input. This method, so called GRASPpac, is implemented in CAECENET, which assimilates sun-sky photometers data from CÆLIS database and ceilometer data from ICENET database (Iberian Ceilometer Network). CAECENET allows for continuous and near-real-time monitoring of both vertical and columnar aerosol properties. The main characteristics and workflow of CAECENET are explained in detail. This work also explores the potential of CAECENET to monitor and analyze the evolution of transported aerosol events on a regional scale by means of the distribution of CAECENET stations across the Iberian Peninsula. As an example, this paper analyzes, using the CAECENET products, the case of a Saharan dust outbreak that occurred between the 3rd and 5th of October 2022. This was an intense event, with AOD at 440 nm values around 0.5 in Madrid and Valladolid, and reaching 1.55 in Granada. Transport from the Canadian wildfires at the end of June 2023 is also studied. Despite the long-range transport of the smoke particles in this event, measured volume concentrations reached and surpassed 80 μ m3/ μ m2 in some stations. The results obtained point to the utility of this CAECENET tool for analyzing changes in the height and speed of the event propagation, in the aerosol concentration, and how this affects the optical properties. [ABSTRACT FROM AUTHOR]

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]

In the present work, a statistical understanding of cloud base height (CBH) behavior over a high-altitude site (Mahabaleshwar, 17.92°N, 73.66°E, and 1348 m above mean sea level) in the Western Ghats, India, has been detailed using Ceilometer measurements. The study focused on the southwest monsoon (June to September) including May and October for a period of three years 2019–2021. Cloud occurrence frequency showed clear monthly variation from May to October with maxima during the southwest monsoon. A clear altitude-temporal variability has been noticed in three level CBH detected i.e., CBH 1, 2, 3, over the study region. May and October showed lower (higher) CBH during daytime (night-time), whereas JJAS exhibited less significant diurnal variability with low values throughout the day. Monthly and seasonal variation of mean CBH (lowest layer) showed high values during May and October whereas low during the southwest monsoon season. Analysis showed the presence of layered clouds over the study region. Cloud type classification based on CBH showed a higher percentage of low and mid-level (mid-level) clouds during May (October). Low-level clouds were dominant during the southwest monsoon over the study region. Further, CBH behavior and cloud types were investigated under various environmental conditions or phases associated with the respective season/month. Distinct variations in CBH frequency distribution and cloud types are noted from the classified conditions/phases. Presented results indicated that the study region receives a good amount of rainfall mostly from the low-level clouds during the southwest monsoon, whereas low-level and mid-level significantly contribute to the total precipitation during May and October. This is the first such report using long-term ground-based observation from a high-altitude complex terrain like the Western Ghats explicitly on CBH behavior. [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]

Mixing layer height (MLH) is an important meteorological parameter for air quality since it significantly affects ground-level pollution in the atmosphere. This study examined the properties of the MLH on diurnal and seasonal timescales over a 3-year period (2020–2022) using high temporal resolution measurements from eight Vaisala CL31 ceilometers situated around Slovakia. Hourly averaged MLH data was retrieved from the BL-View software using merged method. The highest daily maxima for the MLH occurred mostly in summer and spring, while the lowest values occurred predominantly during winter and autumn. The average MLH daily maximum in summer was 2229 m, and just 859 m in winter. During summer, the spatial distribution of the MLH daily maxima was more uniform compared to winter, when the air masses within the individual valleys did not mix well. Correlations between ground-level pollutant concentrations and hourly mean/daily mean MLH were analyzed. The highest correlation, R≈0.6, was found for O3. For PM10, PM2.5, and NOx, the anticorrelations with MLH were found with maximum in winter (R ≈ − 0.3 for hourly data and R ≈ − 0.5 for daily mean data) but no relation in summer. Lastly, the ceilometer MLH was compared to the radiosonde retrieved MLH for various cloud covers. Our analysis is based on an extensive set of empirical data, which can improve the accuracy and effectiveness of meteorological and atmospheric chemistry models. The findings can support air pollution forecasting and warning systems, providing valuable insights for policymakers and researchers. [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]

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 space-borne lidar CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) were used. The plumes were located with the help of a trajectory analysis, and the mass 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 (AOD) 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 space-borne 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]

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]

The aim of the study is to characterize the long‐term variability of the low‐level cloud base heights (CBH) in Poland in the years 1971–2020. Data were used from six weather stations belonging to the Institute of Meteorology and Water Management – the National Research Institute (IMWM‐NRI), where CBH was first measured using the IWO device and, since the 1990s, using a ceilometer. The analysis allowed for data from eight observation periods (0000, 0300, 0600, 0900, 1200, 1500, 1800, 2100 UTC), which referred to several height ranges (between the ground surface and 2500 m a.s.l.). In the analysed multiyear period, in the cool half of the year, the height of the Cumulonimbus cloud bases increased significantly, that is, the number of cases increased at a height of >1000 m and, in the warm half of the year, at >1500 m. In recent years, the number of cases of the Cumulus cloud with a base at a height between 300 and 999 m has clearly decreased, while it has increased at a height of 1000–1499 m (in October–March) and 1500–1999 m (April–September). A similar increase in CBH was found in the case of the Stratocumulus cloud (their greater share between 1500 and 2499 m). It was only in the case of the Stratus cloud that a lowering of the cloud base was noticed, possibly owing to the imperfect measurement of the fractus species. The positive upward trend in the base height of most low‐level clouds can be explained by a statistically significant increase in temperature and a decrease in relative air humidity in the lower troposphere. [ABSTRACT FROM AUTHOR]

The depth of the aerosol layer at the Villum Research Station at Station Nord in the high Arctic is analysed based on 8 years of observations from a ceilometer and one full year from a wind lidar. The layer is of particular interest for aerosol process modelling and atmospheric chemistry studies. The depth of the aerosol layer is assigned to the inflection point in the attenuated backscatter profile by two methods; one is based on polynomial approximation of the profile and the other is direct numerical differentiation. The analysis is based on two types of hourly profiles; one consists of averaging the attenuated backscatter observations and the other by computing the median. Due to sporadic occurrence of outliers in the ranges around 50 m in the ceilometer observations, this part of the profile is not used in this study. Restricting the observations to heights above 100 m, the depths of the aerosol layer are found to be typically ≈230 m. It varies little between winter and summer, but the spread in the depth is larger during the winter as compared to summer. To extend the study of the aerosol‐layer depth below 100 m, a method is applied that combines the ceilometer measurements with the carrier‐to‐noise ratio from the wind lidar. The results are available for 2018 only, and they show aerosol‐layer depths below ≈80 m as well as depths around 230 m and they show few observations between ≈80 and ≈230 m. Near the ground, the observed backscatter exhibits a pronounced seasonal variation, having low values during the summer and high values during the winter. The strength of the seasonal variability decreases with height, especially above the aerosol‐layer depth, and is virtually absent at 1 km. [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]

The government of India imposed a nationwide lockdown to tackle the outbreak of COVID-19 in 2020. This period witnessed record low anthropogenic activity, which had severe socio-economic impacts but also had orthogonal effects on the ambient air quality of the atmosphere. This study focuses on the variations in the atmospheric boundary layer (ABL) over a western Indian urban region in the light of COVID-19. Continuous backscatter recorded by a ceilometer, stationed at Ahmedabad, was used in this study to monitor the ABL during the national lockdown (NLD) in 2020 and state restrictions in 2021, and compared with the control year of 2019. In parallel, improvement in air quality during the NLD was observed by the SAFAR air quality station at Ahmedabad, with decreased particulate matter concentrations. The ground-based observations were substantiated by the ERA5 reanalysis dataset. A decline in the ABL height was recorded during the NLD, which showed improvement in 2021 but which was shy of the ABL in 2019. This was correlated with rain events during the observational period, recorded by an automatic weather station. [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]

In polar regions, blowing snow (BLSN) can play a substantial role in regional thermodynamics and radiation properties. The extent of the impact depends upon the depth of the BLSN layer, a property that is difficult to measure and not well understood. The West Antarctic Radiation Experiment (AWARE) Field Campaign saw the deployment of a large suite of observational instruments to McMurdo Station, Antarctica, allowing for in‐depth investigation of BLSN. During the year of the campaign, BLSN occurred ∼7.4% of the time. In this study, additional remote sensing observations are used to supplement an existing ceilometer‐based BLSN characterization algorithm creating a multi‐instrument (MI) depth estimation algorithm to yield layer depths with more certainty. Backscatter coefficient and linear depolarization ratios from the micropulse and high spectral resolution lidar (HSRL) are incorporated along with color ratio derived from HSRL backscatter and Ka‐band radar reflectivity observations. This provided estimates of BLSN depth that were less impacted by noise/artifacts in any one set of observations. When applied to the data from AWARE, the MI algorithm yielded an average depth of 168.2 m with ∼60% of plumes less than 200 m in depth. Events occurring with precipitation saw the most value in the additional instruments, with the suite of observations allowing for more separation of BLSN particles from fallstreaks. Plain Language Summary: This study used multiple lidar and radar instruments to identify the height of blowing snow (BLSN) layers at McMurdo Station in Antarctica. This information can be used to evaluate and improve BLSN models which have had minimal verification above ground. Results of this study compare well to prior studies, however, the suite of instruments demonstrate that agreement is partially due to compensating errors within single instrument (ceilometer) studies. Key Points: Inclusion of additional lidars and radar improve estimates of blowing snow layer heightsCeilometer only algorithms are prone to offsetting height errors due to extinction and fallstreaksFuture in situ observations are paramount to improving and validating this experimental algorithm [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.