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This work concerns analysis of turbulence in the Atmospheric Boundary Layer (ABL) short before and after the sunset. Based on a large set of the Doppler lidar measurements at rural and urban sites we analyze frequency spectra of vertical wind at different heights and show that they increasingly deviate from the -5/3 Kolmogorov's prediction in the measured lowwavenumber part of the inertial range. We find that before the sunset the integral length scales tend to decrease with time. These findings contrast with a classical model of equilibrium decay of isotropic turbulence, which predicts that the scaling exponent should remain constant and equal to -5/3 and the integral length scale should increase in time. We explain the observations using recent theories of non-equilibrium turbulence. The presence of non-equilibrium suggests that classical parametrization schemes fail to predict turbulence statistics short before the sunset. By comparing the classical and the non-equilibrium models we conclude that the former may underestimate the dissipation rate of turbulence kinetic energy in the initial stages of decay. [ABSTRACT FROM AUTHOR]

The characteristics, distributions, and trends of the aerosol optical depth (AOD) and dust aerosol optical depth (DAOD) of three major concentrating solar power (CSP)-plant project areas (Hami, Turpan, and Ruoqiang) in Xinjiang, China were investigated and analyzed during 1980–2022 using the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) reanalysis products. The monthly variation, seasonal variation, inter-annual variation, distributions of AOD and DAOD, and proportions of dust in the aerosols in these three CSP-plant project areas were computed and analyzed. Overall, the annual mean AOD at 550 nm in the Turpan project area was the highest (0.20–0.36), while Ruoqiang had the lowest annual mean AOD at 550 nm (0.13–0.30), and the annual mean AOD at 550 nm in Hami was distributed between 0.17 and 0.33. After 2010, the change in the rate of the annual mean AOD showed an overall downward trend in Hami and Ruoqiang, indicating that the atmospheric environmental changes in both areas were more favorable for the operation of CSP plants. In the project areas of Hami, Turpan, and Ruoqiang, more than 90% of the AOD values were mainly in ranges 0.10–0.30, 0.10–0.35, and 0.05–0.30, respectively. As expected, the AOD values in spring and summer were significantly higher than those in autumn and winter in the three study areas. In spring, the dust contents (i.e., ratios of DAOD to AOD) were the highest, accounting for 64% (Hami), 67% (Turpan), and 69% (Ruoqiang) of the total aerosol contents. In all three areas, the proportions of dust in aerosols in spring have shown an increasing trend since 2000, suggesting that the negative impact of the dust on the power generation efficiency in these areas has gradually been increasing. Therefore, it is recommended that the CSP plants in Hami, Turpan, and Ruoqiang develop a strategy for cleaning heliostats, especially in spring, to reduce the impact of dust adhesion on the efficiency of the CSP plants. [ABSTRACT FROM AUTHOR]

Fine scale resolution analysis was applied to the complicated aerosol structures observed with the PollyXT-UW lidar over Warsaw during the night of 9/10 August 2015. The full sets of the particle optical properties profiles, so called 3β+2α+2δ+wv (3 backscattering, 2 extinction coefficients, 2 depolarization ratios and water vapour mixing ratio), were obtained to discriminate multiple aerosol height sectors, which were then used for the microphysical properties inversion. The statistical characterization of the main aerosol/mixture types was obtained.

Smoke layers in the stratosphere were observed during autumn 2017 using PollyXT-UW Raman lidar at the European Aerosol Research Lidar Network in the frame of the Aerosol Cloud and Trace Gases Research Infrastructure, i.e. the EARLINET-ACTRIS site in Warsaw, Poland. The analysis was focused on discriminating very weak signatures of smoke layers in the stratosphere and investigating their optical properties. Preliminary results are presented and discussed. A decrease of the lidar-derived stratospheric aerosol optical depth contribution to the total optical depth was detected after the stratospheric smoke particles circled Northern Hemisphere.

The biomass burning events are analyzed using the EARLINET-ACTRIS atmospheric profiling of aerosols using lidars. The period of 2008-2017 was chosen to analyze all the events assigned in the EARLINET database under Forest Fire category. A number of fourteen stations were considered. The data provided, ranged from complete data sets (backscatter, extinction and particle linear depolarization ratio) to single profiles (backscatter coefficient). A thorough quality control was performed. Smoke layers geometry was evaluated and the mean properties within each layer were computed. The Hysplit backward-trajectory technique and the FIRMS fire database were used to double check the source of each layer. Discussions were made under the following scenarios: fire events seen by two stations, long range transport from North America, and geographical clusters.

This paper presents preliminary results of using an extended POLIPHON method for separation of dust and non-dust aerosol backscatter coefficient, applied on a case study of 9th August 2013. That day, long-range transport of mineral dust over EARLINET-ACTRIS lidar site in Warsaw was observed with the 8-channel PollyXT-UW lidar. The dust particles were also observed by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the CALIPSO satellite. The backward trajectories calculated using the HYSPLIT model confirmed the air-mass transport from Northern Africa. Results yield possible dust separation for the mixture of dust with other aerosol types, such as pollution, marine type, etc.

The paper presents the preliminary results of the lidar&radiometer measurement campaign (LRMC-2017), estimation of statistical relations between aerosol mode concentrations retrieved from CALIOP and ground-based lidar stations and case study of fire smoke events in the Eurasian regions using combined ground-based and space lidar and radiometer observations.

This paper presents a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection, named DeLiAn, is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarization lidar measurements, conducted mainly with lidars that have been developed at the Leibniz Institute for Tropospheric Research. The intensive optical properties are presented at two wavelengths, 355 and 532 nm, for 13 aerosol categories. The categories cover the basic aerosol types (i.e., marine, pollution, continental European background, volcanic ash, smoke, mineral dust), as well as the most frequently observed mixtures they form. This extensive collection also incorporates more peculiar aerosol categories, including dried marine aerosol that, compared to marine aerosol, exhibits a significantly enhanced depolarization ratio (up to 15 %). Besides Saharan dust, additional mineral dust types related to their source region were identified due to their lower lidar ratios (Central Asian and Middle Eastern dust). In addition, extreme wildfire events (such as in north America and Australia) emitted smoke into the stratosphere showing significantly different optical properties, i.e., high depolarization values (up to 25 %), compared to tropospheric smoke. The data collection reflects and underlines the variety of aerosol mixtures in the atmosphere and can be used for the development of aerosol-typing schemes. The paper contains the most up-to-date and comprehensive overview of optical properties from aerosol lidar measurements and, therefore, provides a solid basis for future aerosol retrievals in the frame of both spaceborne and ground-based lidars. Furthermore, DeLiAn can assist the efforts for the harmonization of satellite records of aerosol properties performed at different wavelengths. [ABSTRACT FROM AUTHOR]

There is the need of integration of atmospheric and ecosystem research in order to assess the habitats reaction in the future since the recent climate changes. Peatlands due to their vulnerability are important ecosystems since their strong interaction with the climate system. In stable climatic conditions, they are atmospheric carbon sinks. The study of the atmosphere properties in the context of peatlands productivity requires the application of the multidimensional strategy of field measurements. These kind of measurements are conducted using the following sensors: sun photometer, cloud radar, Raman lidar and eddy covariance (EC) system. They are located and operated at the Rzecin peatland in the framework of the POLIMOS project. So far, aerosols presence in the air was found as a factor that increases the peatland production. This presents the novel strategy of extensive atmospheric studies in order to identify the selected particles type impact on peatlands carbon uptake capabilities.

A Python code was developed to automatically retrieve the aerosol type (and its predominant component in the mixture) from EARLINET’s 3 backscatter and 2 extinction data. The typing relies on Artificial Neural Networks which are trained to identify the most probable aerosol type from a set of mean-layer intensive optical parameters. This paper presents the use and limitations of the code with respect to the quality of the inputed lidar profiles, as well as with the assumptions made in the aerosol model.

The aerosol layers of different origin, suspended in the atmosphere on 9-11 August 2015 were observed with the PollyXT-UW lidar in Warsaw, Poland. The HYSPLIT ensemble backward trajectories indicate that the observed air-masses attribute to a few different sources, among others, possible transport paths from Ukraine, Slovakia, and Africa. In this paper, we attempt to analyse and discuss the properties of aerosol particles of different origin that were suspended over Warsaw during this event.

PollyNET is a network of portable, automated, and continuously measuring Ramanpolarization lidars of type Polly operated by several institutes worldwide. The data from permanent and temporary measurements sites are automatically processed in terms of optical aerosol profiles and displayed in near-real time at polly.tropos.de. According to current schedules, the network will grow by 3-4 systems during the upcoming 2-3 years and will then comprise 11 permanent stations and 2 mobile platforms.

During an exceptionally warm September of 2016, the unique, stable weather conditions over Poland allowed for an extensive testing of the new algorithm developed to improve the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) aerosol optical depth (AOD) retrieval. The development was conducted in the frame of the ESA-ESRIN SAMIRA project. The new AOD algorithm aims at providing the aerosol optical depth maps over the territory of Poland with a high temporal resolution of 15 minutes. It was tested on the data set obtained between 11-16 September 2016, during which a day of relatively clean atmospheric background related to an Arctic airmass inflow was surrounded by a few days with well increased aerosol load of different origin. On the clean reference day, for estimating surface reflectance the AOD forecast available on-line via the Copernicus Atmosphere Monitoring Service (CAMS) was used. The obtained AOD maps were validated against AODs available within the Poland-AOD and AERONET networks, and with AOD values obtained from the PollyXT-UW lidar. of the University of Warsaw (UW).

The Cloud-Aerosol Transport System (CATS) onboard the International Space Station (ISS), is a lidar system providing vertically resolved aerosol and cloud profiles since February 2015. In this study, the CATS aerosol product is validated against the aerosol profiles provided by the European Aerosol Research Lidar Network (EARLINET). This validation activity is based on collocated CATS-EARLINET measurements and the comparison of the particle backscatter coefficient at 1064nm.

Arctic Haze event was observed on 5-8 April 2015 using simultaneously Near-range Aerosol Raman Lidar of IGFUW and Koldewey Aerosol Raman Lidar of AWI, both based at AWIPEV German-French station in Ny-Ålesund, Spitsbergen. The alterations in particle abundance and altitude of the aerosol load observed on following days of the event is analyzed. The daytime profiles of particle optical properties were obtained for both lidars, and then served as input for microphysical parameters inversion. The results indicate aerosol composition typical for the Arctic Haze. However, in some layers, a likely abundance of aqueous aerosol or black carbon originating in biomass burning over Siberia, changes measurably the Arctic Haze properties.

Aerosol absorption profiling is crucial for radiative transfer calculations and climate modelling. Here, we utilize the synergy of lidar with sun-photometer measurements to derive the absorption coefficient and single scattering albedo profiles during the ACTRIS-2 campaigns held in Germany, Greece and Cyprus. The remote sensing techniques are compared with in situ measurements in order to harmonize and validate the different methodologies and reduce the absorption profiling uncertainties.

The aim of the research was to determine the impact of July 2015 biomass burning event on radiative budget, atmospheric stratification and turbulence over the Arctic using information about the vertical structure of the aerosol load from the ground–based data. MODTRAN simulations indicated very high surface radiative cooling (forcing of –150 Wm–2) and a heating rate of up to 1.8 Kday–1 at 3 km. Regarding LES results, a turbulent layer at around 3 km was clearly seen after 48 h of simulation.

This document is an editorial titled "Lidar and ocean color remote sensing for marine ecology" published in the journal Frontiers in Remote Sensing. The editorial highlights the advancements and applications of lidar and ocean color remote sensing in marine ecology. It discusses four papers published in the research topic, which cover topics such as machine learning algorithms for cloud and aerosol detection, estimation of planetary boundary layer height, underwater laser detection, and validation protocols for space-borne lidar measurements. The editorial emphasizes the importance of interdisciplinary approaches in advancing marine ecological studies and points towards future directions for research and application in this field. [Extracted from the article]

This paper presents a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection, named DeLiAn, is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarisation lidar measurements, conducted mainly with lidars that have been developed at the Leibniz Institute for Tropospheric Research. The intensive optical properties are presented at two wavelengths, 355 and 532 nm, for 13 aerosol categories. The categories cover the basic aerosol types (i.e., marine, pollution, continental European background, volcanic ash, smoke, mineral dust) as well as the most frequently observed mixtures they form. This extensive collection also incorporates more peculiar aerosol categories, including dried marine aerosol that, compared to marine aerosol, exhibits a significantly enhanced depolarization ratio (up to 15 %). Besides Saharan dust, additional mineral dust types related to their source region were identified due to their lower lidar ratios (Central Asian and Middle Eastern dust). In addition, extreme wildfire events (such as in north America and Australia) emitted smoke into the stratosphere showing significant different optical properties, i.e., high depolarization values (up to 25 %), compared to tropospheric smoke. The data collection reflects and underlines the variety of aerosol mixtures in the atmosphere and can be used for the development of aerosol typing schemes. The paper contains the currently most comprehensive overview of optical properties from aerosol lidar measurements and, therefore, provides a solid basis for future aerosol retrievals in the frame of both spaceborne and ground-based lidars. Furthermore, DeLiAn can assist the efforts for harmonization of satellite records of aerosol properties performed at different wavelengths. [ABSTRACT FROM AUTHOR]