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    EARLINET Single Calculus Chain – overview on methodology and strategy
    (München : European Geopyhsical Union, 2015) D'Amico, Giuseppe; Amodeo, A.; Baars, H.; Binietoglou, I.; Freudenthaler, V.; Mattis, I.; Wandinger, U.; Pappalardo, G.
    In this paper we describe the EARLINET Single Calculus Chain (SCC), a tool for the automatic analysis of lidar measurements. The development of this tool started in the framework of EARLINET-ASOS (European Aerosol Research Lidar Network – Advanced Sustainable Observation System); it was extended within ACTRIS (Aerosol, Clouds and Trace gases Research InfraStructure Network), and it is continuing within ACTRIS-2. The main idea was to develop a data processing chain that allows all EARLINET stations to retrieve, in a fully automatic way, the aerosol backscatter and extinction profiles starting from the raw lidar data of the lidar systems they operate. The calculus subsystem of the SCC is composed of two modules: a pre-processor module which handles the raw lidar data and corrects them for instrumental effects and an optical processing module for the retrieval of aerosol optical products from the pre-processed data. All input parameters needed to perform the lidar analysis are stored in a database to keep track of all changes which may occur for any EARLINET lidar system over the time. The two calculus modules are coordinated and synchronized by an additional module (daemon) which makes the whole analysis process fully automatic. The end user can interact with the SCC via a user-friendly web interface. All SCC modules are developed using open-source and freely available software packages. The final products retrieved by the SCC fulfill all requirements of the EARLINET quality assurance programs on both instrumental and algorithm levels. Moreover, the manpower needed to provide aerosol optical products is greatly reduced and thus the near-real-time availability of lidar data is improved. The high-quality of the SCC products is proven by the good agreement between the SCC analysis, and the corresponding independent manual retrievals. Finally, the ability of the SCC to provide high-quality aerosol optical products is demonstrated for an EARLINET intense observation period.
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    EARLINET Single Calculus Chain – technical – Part 1: Pre-processing of raw lidar data
    (München : European Geopyhsical Union, 2016) D'Amico, Giuseppe; Amodeo, Aldo; Mattis, Ina; Freudenthaler, Volker; Pappalardo, Gelsomina
    In this paper we describe an automatic tool for the pre-processing of aerosol lidar data called ELPP (EARLINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of ELPP, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns.
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    3+2 + X : what is the most useful depolarization input for retrieving microphysical properties of non-spherical particles from lidar measurements using the spheroid model of Dubovik et al. (2006)?
    (Katlenburg-Lindau : Copernicus, 2019) Tesche, Matthias; Kolgotin, Alexei; Haarig, Moritz; Burton, Sharon P.; Ferrare, Richard A.; Hostetler, Chris A.; Müller, Detlef
    The typical multiwavelength aerosol lidar data set for inversion of optical to microphysical parameters is composed of three backscatter coefficients (β) at 355, 532, and 1064 nm and two extinction coefficients (α) at 355 and 532 nm. This data combination is referred to as a 3β C 2α or 3 + 2 data set. This set of data is sufficient for retrieving some important microphysical particle parameters if the particles have spherical shape. Here, we investigate the effect of including the particle linear depolarization ratio (δ) as a third input parameter for the inversion of lidar data. The inversion algorithm is generally not used if measurements show values of d that exceed 0.10 at 532 nm, i.e. in the presence of nonspherical particles such as desert dust, volcanic ash, and, under special circumstances, biomass-burning smoke. We use experimental data collected with instruments that are capable of measuring d at all three lidar wavelengths with an inversion routine that applies the spheroidal light-scattering model of Dubovik et al. (2006) with a fixed axis-ratio distribution to replicate scattering properties of non-spherical particles. The inversion gives the fraction of spheroids required to replicate the optical data as an additional output parameter. This is the first systematic test of the effect of using all theoretically possible combinations of d taken at 355, 532, and 1064 nm as input in the lidar data inversion. We find that depolarization information of at least one wavelength already provides useful information for the inversion of optical data that have been collected in the presence of non-spherical mineral dust particles. However, any choice of d will give lower values of the single-scattering albedo than the traditional 3 + 2 data set. We find that input data sets that include d355 give a spheroid fraction that closely resembles the dust ratio we obtain from using β532 and d532 in a methodology applied in aerosol-type separation. The use of d355 in data sets of two or three d? reduces the spheroid fraction that is retrieved when using d532 and d1064. Use of the latter two parameters without accounting for d355 generally leads to high spheroid fractions that we consider not trustworthy. The use of three d instead of two δ, including the constraint that one of these is measured at 355 nm does not provide any advantage over using 3 + 2 + d355 for the observations with varying contributions of mineral dust considered here. However, additional measurements at wavelengths different from 355 nm would be desirable for application to a wider range of aerosol scenarios that may include non-spherical smoke particles, which can have values of d355 that are indistinguishable from those found for mineral dust. We therefore conclude that - depending on measurement capability - the future standard input for inversion of lidar data taken in the presence of mineral dust particles and using the spheroid model of Dubovik et al. (2006) might be 3+2Cδ355 or 3 + 2 + δ355 + δ532. © 2019 The Author(s).
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    Assessment of lidar depolarization uncertainty by means of a polarimetric lidar simulator
    (München : European Geopyhsical Union, 2016) Bravo-Aranda, Juan Antonio; Belegante, Livio; Freudenthaler, Volker; Alados-Arboledas, Lucas; Nicolae, Doina; Granados-Muñoz, María José; Guerrero-Rascado, Juan Luis; Amodeo, Aldo; D'Amico, Giusseppe; Engelmann, Ronny; Pappalardo, Gelsomina; Kokkalis, Panos; Mamouri, Rodanthy; Papayannis, Alex; Navas-Guzmán, Francisco; Olmo, Francisco José; Wandinger, Ulla; Amato, Francesco; Haeffelin, Martial
    Lidar depolarization measurements distinguish between spherical and non-spherical aerosol particles based on the change of the polarization state between the emitted and received signal. The particle shape information in combination with other aerosol optical properties allows the characterization of different aerosol types and the retrieval of aerosol particle microphysical properties. Regarding the microphysical inversions, the lidar depolarization technique is becoming a key method since particle shape information can be used by algorithms based on spheres and spheroids, optimizing the retrieval procedure. Thus, the identification of the depolarization error sources and the quantification of their effects are crucial. This work presents a new tool to assess the systematic error of the volume linear depolarization ratio (δ), combining the Stokes–Müller formalism and the complete sampling of the error space using the lidar model presented in Freudenthaler (2016a). This tool is applied to a synthetic lidar system and to several EARLINET lidars with depolarization capabilities at 355 or 532 nm. The lidar systems show relative errors of δ larger than 100 % for δ values around molecular linear depolarization ratios (∼ 0.004 and up to ∼  10 % for δ = 0.45). However, one system shows only relative errors of 25 and 0.22 % for δ = 0.004 and δ = 0.45, respectively, and gives an example of how a proper identification and reduction of the main error sources can drastically reduce the systematic errors of δ. In this regard, we provide some indications of how to reduce the systematic errors.
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    GARRLiC and LIRIC: Strengths and limitations for the characterization of dust and marine particles along with their mixtures
    (Katlenburg-Lindau : Copernicus, 2017) Tsekeri, Alexandra; Lopatin, Anton; Amiridis, Vassilis; Marinou, Eleni; Igloffstein, Julia; Siomos, Nikolaos; Solomos, Stavros; Kokkalis, Panagiotis; Engelmann, Ronny; Baars, Holger; Gratsea, Myrto; Raptis, Panagiotis I.; Binietoglou, Ioannis; Mihalopoulos, Nikolaos; Kalivitis, Nikolaos; Kouvarakis, Giorgos; Bartsotas, Nikolaos; Kallos, George; Basart, Sara; Schuettemeyer, Dirk; Wandinger, Ulla; Ansmann, Albert; Chaikovsky, Anatoli P.; Dubovik, Oleg
    The Generalized Aerosol Retrieval from Radiometer and Lidar Combined data algorithm (GARRLiC) and the LIdar-Radiometer Inversion Code (LIRIC) provide the opportunity to study the aerosol vertical distribution by combining ground-based lidar and sun-photometric measurements. Here, we utilize the capabilities of both algorithms for the characterization of Saharan dust and marine particles, along with their mixtures, in the south-eastern Mediterranean during the CHARacterization of Aerosol mixtures of Dust and Marine origin Experiment (CHARADMExp). Three case studies are presented, focusing on dust-dominated, marinedominated and dust-marine mixing conditions. GARRLiC and LIRIC achieve a satisfactory characterization for the dust-dominated case in terms of particle microphysical properties and concentration profiles. The marine-dominated and the mixture cases are more challenging for both algorithms, although GARRLiC manages to provide more detailed microphysical retrievals compared to AERONET, while LIRIC effectively discriminates dust and marine particles in its concentration profile retrievals. The results are also compared with modelled dust and marine concentration profiles and surface in situ measurements.
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    Lidar-Radiometer Inversion Code (LIRIC) for the retrieval of vertical aerosol properties from combined lidar/radiometer data: Development and distribution in EARLINET
    (München : European Geopyhsical Union, 2016) Chaikovsky, Anatoli; Dubovik, Oleg; Holben, Brent; Bril, Andrey; Goloub, Philippe; Tanré, Didier; Pappalardo, Gelsomina; Wandinger, Ulla; Chaikovskaya, Ludmila; Denisov, Sergey; Grudo, Jan; Lopatin, Anton; Karol, Yana; Lapyonok, Tatsiana; Amiridis, Vassilis; Ansmann, Albert; Apituley, Arnoud; Allados-Arboledas, Lucas; Binietoglou, Ioannis; Boselli, Antonella; D'Amico, Giuseppe; Freudenthaler, Volker; Giles, David; Granados-Muñoz, María José; Kokkalis, Panayotis; Nicolae, Doina; Oshchepkov, Sergey; Papayannis, Alex; Perrone, Maria Rita; Pietruczuk, Alexander; Rocadenbosch, Francesc; Sicard, Michaël; Slutsker, Ilya; Talianu, Camelia; De Tomasi, Ferdinando; Tsekeri, Alexandra; Wagner, Janet; Wang, Xuan
    This paper presents a detailed description of LIRIC (LIdar-Radiometer Inversion Code) algorithm for simultaneous processing of coincident lidar and radiometric (sun photometric) observations for the retrieval of the aerosol concentration vertical profiles. As the lidar/radiometric input data we use measurements from European Aerosol Research Lidar Network (EARLINET) lidars and collocated sun-photometers of Aerosol Robotic Network (AERONET). The LIRIC data processing provides sequential inversion of the combined lidar and radiometric data. The algorithm starts with the estimations of column-integrated aerosol parameters from radiometric measurements followed by the retrieval of height dependent concentrations of fine and coarse aerosols from lidar signals using integrated column characteristics of aerosol layer as a priori constraints. The use of polarized lidar observations allows us to discriminate between spherical and non-spherical particles of the coarse aerosol mode. The LIRIC software package was implemented and tested at a number of EARLINET stations. Intercomparison of the LIRIC-based aerosol retrievals was performed for the observations by seven EARLINET lidars in Leipzig, Germany on 25 May 2009. We found close agreement between the aerosol parameters derived from different lidars that supports high robustness of the LIRIC algorithm. The sensitivity of the retrieval results to the possible reduction of the available observation data is also discussed.
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    EARLINET Single Calculus Chain – technical – Part 2: Calculation of optical products
    (München : European Geopyhsical Union, 2016) Mattis, Ina; D'Amico, Giuseppe; Baars, Holger; Amodeo, Aldo; Madonna, Fabio; Iarlori, Marco
    In this paper we present the automated software tool ELDA (EARLINET Lidar Data Analyzer) for the retrieval of profiles of optical particle properties from lidar signals. This tool is one of the calculus modules of the EARLINET Single Calculus Chain (SCC) which allows for the analysis of the data of many different lidar systems of EARLINET in an automated, unsupervised way. ELDA delivers profiles of particle extinction coefficients from Raman signals as well as profiles of particle backscatter coefficients from combinations of Raman and elastic signals or from elastic signals only. Those analyses start from pre-processed signals which have already been corrected for background, range dependency and hardware specific effects. An expert group reviewed all algorithms and solutions for critical calculus subsystems which are used within EARLINET with respect to their applicability for automated retrievals. Those methods have been implemented in ELDA. Since the software was designed in a modular way, it is possible to add new or alternative methods in future. Most of the implemented algorithms are well known and well documented, but some methods have especially been developed for ELDA, e.g., automated vertical smoothing and temporal averaging or the handling of effective vertical resolution in the case of lidar ratio retrievals, or the merging of near-range and far-range products. The accuracy of the retrieved profiles was tested following the procedure of the EARLINET-ASOS algorithm inter-comparison exercise which is based on the analysis of synthetic signals. Mean deviations, mean relative deviations, and normalized root-mean-square deviations were calculated for all possible products and three height layers. In all cases, the deviations were clearly below the maximum allowed values according to the EARLINET quality requirements. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns.
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    A methodology for investigating dust model performance using synergistic EARLINET/AERONET dust concentration retrievals
    (München : European Geopyhsical Union, 2015) Binietoglou, I.; Basart, S.; Alados-Arboledas, L.; Amiridis, V.; Argyrouli, A.; Baars, H.; Baldasano, J.M.; Balis, D.; Belegante, L.; Bravo-Aranda, J.A.; Burlizzi, P.; Carrasco, V.; Chaikovsky, A.; Comerón, A.; D'Amico, G.; Filioglou, M.; Granados-Muñoz, M.J.; Haefele, A.; Hervo, M.; Iarlori, M.; Kokkalis, P.; Lange, D.; Mamouri, R.E.; Mattis, I.; Molero, F.; Montoux, N.; Muñoz, A.; Muñoz Porcar, C.; Navas-Guzmán, F.; Nicolae, D.; Nisantzi, A.; Papagiannopoulos, N.; Papayannis, A.; Pereira, S.; Preißler, J.; Pujadas, M.; Rizi, V.; Rocadenbosch, F.; Sellegri, K.; Simeonov, V.; Tsaknakis, G.; Wagner, F.; Pappalardo, G.
    Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAMABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1–6 km range, where most dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of -40 to -20 μg m−3 at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies.
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    Separation of the optical and mass features of particle components in different aerosol mixtures by using POLIPHON retrievals in synergy with continuous polarized Micro-Pulse Lidar (P-MPL) measurements
    (Katlenburg-Lindau : Copernicus, 2018) Córdoba-Jabonero, Carmen; Sicard, Michaël; Ansmann, Albert; del Águila, Ana; Baars, Holger
    The application of the POLIPHON (POlarization-LIdar PHOtometer Networking) method is presented for the first time in synergy with continuous 24/7 polarized Micro-Pulse Lidar (P-MPL) measurements to derive the vertical separation of two or three particle components in different aerosol mixtures, and the retrieval of their particular optical properties. The procedure of extinction-to-mass conversion, together with an analysis of the mass extinction efficiency (MEE) parameter, is described, and the relative mass contribution of each aerosol component is also derived in a further step. The general POLIPHON algorithm is based on the specific particle linear depolarization ratio given for different types of aerosols and can be run in either 1-step (POL-1) or 2 steps (POL-2) versions with dependence on either the 2- or 3-component separation. In order to illustrate this procedure, aerosol mixing cases observed over Barcelona (NE Spain) are selected: a dust event on 5 July 2016, smoke plumes detected on 23 May 2016 and a pollination episode observed on 23 March 2016. In particular, the 3-component separation is just applied for the dust case: a combined POL-1 with POL-2 procedure (POL-1/2) is used, and additionally the fine-dust contribution to the total fine mode (fine dust plus non-dust aerosols) is estimated. The high dust impact before 12:00 UTC yields a mean mass loading of 0.6±0.1 g m'2 due to the prevalence of Saharan coarse-dust particles. After that time, the mean mass loading is reduced by two-thirds, showing a rather weak dust incidence. In the smoke case, the arrival of fine biomass-burning particles is detected at altitudes as high as 7 km. The smoke particles, probably mixed with less depolarizing non-smoke aerosols, are observed in air masses, having their origin from either North American fires or the Arctic area, as reported by HYSPLIT back-trajectory analysis. The particle linear depolarization ratio for smoke shows values in the 0.10-0.15 range and even higher at given times, and the daily mean smoke mass loading is 0.017±0.008 g m'2, around 3 % of that found for the dust event. Pollen particles are detected up to 1.5 km in height from 10:00 UTC during an intense pollination event with a particle linear depolarization ratio ranging between 0.10 and 0.15. The maximal mass loading of Platanus pollen particles is 0.011±0.003 g m'2, representing around 2 % of the dust loading during the higher dust incidence. Regarding the MEE derived for each aerosol component, their values are in agreement with others referenced in the literature for the specific aerosol types examined in this work: 0.5±0.1 and 1.7±0.2 m2 g'1 are found for coarse and fine dust particles, 4.5±1.4 m2 g'1 is derived for smoke and 2.4±0.5 m2 g'1 for non-smoke aerosols with Arctic origin, and a MEE of 2.4±0.8 m2 g'1 is obtained for pollen particles, though it can reach higher or lower values depending on predominantly smaller or larger pollen grain sizes. Results reveal the high potential of the P-MPL system, a simple polarization-sensitive elastic backscatter lidar working in a 24/7 operation mode, to retrieve the relative optical and mass contributions of each aerosol component throughout the day, reflecting the daily variability of their properties. In fact, this procedure can be simply implemented in other P-MPLs that also operate within the worldwide Micro-Pulse Lidar Network (MPLNET), thus extending the aerosol discrimination at a global scale. Moreover, the method has the advantage of also being relatively easily applicable to space-borne lidars with an equivalent configuration such as the ongoing Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) on board NASA CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) and the forthcoming Atmospheric Lidar (ATLID) on board the ESA EarthCARE mission.
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    Microphysical characterization of long-range transported biomass burning particles from North America at three EARLINET stations
    (Katlenburg-Lindau : EGU, 2017) Ortiz-Amezcua, Pablo; Guerrero-Rascado, Juan Luis; Granados-Muñoz, María José; Benavent-Oltra, José Antonio; Böckmann, Christine; Samaras, Stefanos; Stachlewska, Iwona S.; Janicka, Łucja; Baars, Holger; Bohlmann, Stephanie; Alados-Arboledas, Lucas
    Strong events of long-range transported biomass burning aerosol were detected during July 2013 at three EARLINET (European Aerosol Research Lidar Network) stations, namely Granada (Spain), Leipzig (Germany) and Warsaw (Poland). Satellite observations from MODIS (Moderate Resolution Imaging Spectroradiometer) and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) instruments, as well as modeling tools such as HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) and NAAPS (Navy Aerosol Analysis and Prediction System), have been used to estimate the sources and transport paths of those North American forest fire smoke particles. A multiwavelength Raman lidar technique was applied to obtain vertically resolved particle optical properties, and further inversion of those properties with a regularization algorithm allowed for retrieving microphysical information on the studied particles. The results highlight the presence of smoke layers of 1-2 km thickness, located at about 5 km a.s.l. altitude over Granada and Leipzig and around 2.5 km a.s.l. at Warsaw. These layers were intense, as they accounted for more than 30 % of the total AOD (aerosol optical depth) in all cases, and presented optical and microphysical features typical for different aging degrees: Color ratio of lidar ratios (LR532/LR355) around 2, α-related ängström exponents of less than 1, effective radii of 0.3 μm and large values of single scattering albedos (SSA), nearly spectrally independent. The intensive microphysical properties were compared with columnar retrievals form co-located AERONET (Aerosol Robotic Network) stations. The intensity of the layers was also characterized in terms of particle volume concentration, and then an experimental relationship between this magnitude and the particle extinction coefficient was established.