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    The vertical aerosol type distribution above Israel – 2 years of lidar observations at the coastal city of Haifa
    (Katlenburg-Lindau : EGU, 2022) Heese, Birgit; Floutsi, Athena Augusta; Baars, Holger; Althausen, Dietrich; Hofer, Julian; Herzog, Alina; Mewes, Silke; Radenz, Martin; Schechner, Yoav Y.
    For the first time, vertically resolved long-term lidar measurements of the aerosol distribution were conducted in Haifa, Israel. The measurements were performed by a PollyXT multi-wavelength Raman and polarization lidar. The lidar was measuring continuously over a 2-year period from March 2017 to May 2019. The resulting data set is a series of manually evaluated lidar optical property profiles. To identify the aerosol types in the observed layers, a novel aerosol typing method that was developed at TROPOS is used. This method applies optimal estimation to a combination of lidar-derived intensive aerosol properties to determine the statistically most-likely contribution per aerosol component in terms of relative volume. A case study that shows several elevated aerosol layers illustrates this method and shows, for example, that coarse dust particles are observed up to 5ĝ€¯km height over Israel. From the whole data set, the seasonal distribution of the observed aerosol components over Israel is derived. Throughout all seasons, coarse spherical particles like sea salt and hygroscopically grown continental aerosol were observed. These particles originate from continental Europe and were transported over the Mediterranean Sea. Sea-salt particles were observed frequently due to the coastal site of Haifa. The highest contributions of coarse spherical particles are present in summer, autumn, and winter. During spring, mostly coarse non-spherical particles that are attributed to desert dust were observed. This is consistent with the distinct dust season in spring in Israel. An automated time-height-resolved air mass source attribution method identifies the origin of the dust in the Sahara and the Arabian deserts. Fine-mode spherical particles contribute significantly to the observed aerosol mixture during all seasons. These particles originate mainly from the industrial region at the bay of Haifa.
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    Measurements of particle backscatter, extinction, and lidar ratio at 1064 nm with the rotational raman method in Polly-XT
    (Les Ulis : EDP Sciences, 2018) Engelmann, Ronny; Haarig, Moritz; Baars, Holger; Ansmann, Albert; Kottas, Michael; Marinou, Eleni; Nicolae, D.; Makoto, A.; Vassilis, A.; Balis, D.; Behrendt, A.; Comeron, A.; Gibert, F.; Landulfo, E.; McCormick, M.P.; Senff, C.; Veselovskii, I.; Wandinger, U.
    We replaced a 1064-nm interference filter of a Polly-XT lidar system by a 1058-nm filter to observe pure rotational Raman backscattering from atmospheric Nitrogen and Oxygen. Polly-XT is compact Raman lidar with a Nd:YAG laser (20 Hz, 200 mJ at 1064 nm) and a 30-cm telescope mirror which applies photomultipliers in photoncounting mode. We present the first measured signals at 1058 nm and the derived extinction profile from measurements aboard RV Polarstern and in Leipzig. In combination with another Polly-XT system we could also derive particle backscatter and lidar ratio profiles at 1064 nm.
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    EARLINET instrument intercomparison campaigns: Overview on strategy and results
    (München : European Geopyhsical Union, 2016) Wandinger, Ulla; Freudenthaler, Volker; Baars, Holger; Amodeo, Aldo; Engelmann, Ronny; Mattis, Ina; Groß, Silke; Pappalardo, Gelsomina; Giunta, Aldo; D'Amico, Giuseppe; Chaikovsky, Anatoli; Osipenko, Fiodor; Slesar, Alexander; Nicolae, Doina; Belegante, Livio; Talianu, Camelia; Serikov, Ilya; Linné, Holger; Jansen, Friedhelm; Apituley, Arnoud; Wilson, Keith M.; de Graaf, Martin; Trickl, Thomas; Giehl, Helmut; Adam, Mariana; Comerón, Adolfo; Muñoz-Porcar, Constantino; Rocadenbosch, Francesc; Sicard, Michaël; Tomás, Sergio; Lange, Diego; Kumar, Dhiraj; Pujadas, Manuel; Molero, Francisco; Fernández, Alfonso J.; Alados-Arboledas, Lucas; Bravo-Aranda, Juan Antonio; Navas-Guzmán, Francisco; Guerrero-Rascado, Juan Luis; Granados-Muñoz, María José; Preißler, Jana; Wagner, Frank; Gausa, Michael; Grigorov, Ivan; Stoyanov, Dimitar; Iarlori, Marco; Rizi, Vincenco; Spinelli, Nicola; Boselli, Antonella; Wang, Xuan; Feudo, Teresa Lo; Perrone, Maria Rita; De Tomas, Ferdinando; Burlizzi, Pasquale
    This paper introduces the recent European Aerosol Research Lidar Network (EARLINET) quality-assurance efforts at instrument level. Within two dedicated campaigns and five single-site intercomparison activities, 21 EARLINET systems from 18 EARLINET stations were intercompared between 2009 and 2013. A comprehensive strategy for campaign setup and data evaluation has been established. Eleven systems from nine EARLINET stations participated in the EARLINET Lidar Intercomparison 2009 (EARLI09). In this campaign, three reference systems were qualified which served as traveling standards thereafter. EARLINET systems from nine other stations have been compared against these reference systems since 2009. We present and discuss comparisons at signal and at product level from all campaigns for more than 100 individual measurement channels at the wavelengths of 355, 387, 532, and 607 nm. It is shown that in most cases, a very good agreement of the compared systems with the respective reference is obtained. Mean signal deviations in predefined height ranges are typically below ±2 %. Particle backscatter and extinction coefficients agree within ±2  ×  10−4 km−1 sr−1 and ± 0.01 km−1, respectively, in most cases. For systems or channels that showed larger discrepancies, an in-depth analysis of deficiencies was performed and technical solutions and upgrades were proposed and realized. The intercomparisons have reinforced confidence in the EARLINET data quality and allowed us to draw conclusions on necessary system improvements for some instruments and to identify major challenges that need to be tackled in the future.
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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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    An automatic observation-based aerosol typing method for EARLINET
    (Katlenburg-Lindau : EGU, 2018) Papagiannopoulos, Nikolaos; Mona, Lucia; Amodeo, Aldo; D'Amico, Giuseppe; Gumà Claramunt, Pilar; Pappalardo, Gelsomina; Alados-Arboledas, Lucas; Guerrero-Rascado, Juan Luís; Amiridis, Vassilis; Kokkalis, Panagiotis; Apituley, Arnoud; Baars, Holger; Schwarz, Anja; Wandinger, Ulla; Binietoglou, Ioannis; Nicolae, Doina; Bortoli, Daniele; Comerón, Adolfo; Rodríguez-Gómez, Alejandro; Sicard, Michaël; Papayannis, Alex; Wiegner, Matthias
    We present an automatic aerosol classification method based solely on the European Aerosol Research Lidar Network (EARLINET) intensive optical parameters with the aim of building a network-wide classification tool that could provide near-real-time aerosol typing information. The presented method depends on a supervised learning technique and makes use of the Mahalanobis distance function that relates each unclassified measurement to a predefined aerosol type. As a first step (training phase), a reference dataset is set up consisting of already classified EARLINET data. Using this dataset, we defined 8 aerosol classes: clean continental, polluted continental, dust, mixed dust, polluted dust, mixed marine, smoke, and volcanic ash. The effect of the number of aerosol classes has been explored, as well as the optimal set of intensive parameters to separate different aerosol types. Furthermore, the algorithm is trained with literature particle linear depolarization ratio values. As a second step (testing phase), we apply the method to an already classified EARLINET dataset and analyze the results of the comparison to this classified dataset. The predictive accuracy of the automatic classification varies between 59% (minimum) and 90% (maximum) from 8 to 4 aerosol classes, respectively, when evaluated against pre-classified EARLINET lidar. This indicates the potential use of the automatic classification to all network lidar data. Furthermore, the training of the algorithm with particle linear depolarization values found in the literature further improves the accuracy with values for all the aerosol classes around 80%. Additionally, the algorithm has proven to be highly versatile as it adapts to changes in the size of the training dataset and the number of aerosol classes and classifying parameters. Finally, the low computational time and demand for resources make the algorithm extremely suitable for the implementation within the single calculus chain (SCC), the EARLINET centralized processing suite.
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    Long-term profiling of aerosol light extinction, particle mass, cloud condensation nuclei, and ice-nucleating particle concentration over Dushanbe, Tajikistan, in Central Asia
    (Katlenburg-Lindau : EGU, 2020) Hofer, Julian; Ansmann, Albert; Althausen, Dietrich; Engelmann, Ronny; Baars, Holger; Abdullaev, Sabur F.; Makhmudov, Abduvosit N.
    For the first time, continuous, vertically resolved long-term aerosol measurements were conducted with a state-of-the-art multiwavelength lidar over a Central Asian site. Such observations are urgently required in efforts to predict future climate and environmental conditions and to support spaceborne remote sensing (ground truth activities). The lidar observations were performed in the framework of the Central Asian Dust Experiment (CADEX) at Dushanbe, Tajikistan, from March 2015 to August 2016. An AERONET (AErosol RObotic NETwork) sun photometer was operated at the lidar field site. During the 18-month campaign, mixtures of continental aerosol pollution and mineral dust were frequently detected from ground to cirrus height level. Regional sources of dust and pollution as well as long-range transport of mineral dust mainly from Middle Eastern and the Saharan deserts determine the aerosol conditions over Tajikistan. In this study, we summarize our findings and present seasonally resolved statistics regarding aerosol layering (main aerosol layer depth, lofted layer occurrence); optical properties (aerosol and dust optical thicknesses at 500–532 nm, vertically resolved light-extinction coefficient at 532 nm); profiles of dust and non-dust mass concentrations and dust fraction; and profiles of particle parameters relevant for liquid water, mixed-phase cloud, and cirrus formation such as cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations. The main aerosol layer over Dushanbe typically reaches 4–5 km height in spring to autumn. Frequently lofted dust-containing aerosol layers were observed at heights from 5 to 10 km, indicating a sensitive potential of dust to influence cloud ice formation. Typical dust mass fractions were of the order of 60 %–80 %. A considerable fraction is thus anthropogenic pollution and biomass burning smoke. The highest aerosol pollution levels (in the relatively shallow winter boundary layer) occur during the winter months. The seasonal mean 500 nm AOT (aerosol optical thickness) ranges from 0.15 in winter to 0.36 in summer during the CADEX period (March 2015 to August 2016); DOTs (dust optical thicknesses) were usually below 0.2; seasonally mean particle extinction coefficients were of the order of 100–500 Mm−1 in the main aerosol layer during the summer half year and about 100–150 Mm−1 in winter but were mainly caused by anthropogenic haze. Accordingly, the highest dust mass concentrations occurred in the summer season (200–600 µg m−3) and the lowest during the winter months (20–50 µg m−3) in the main aerosol layer. In winter, the aerosol pollution mass concentrations were 20–50 µg m−3, while during the summer half year (spring to autumn), the mass concentration caused by urban haze and biomass burning smoke decreases to 10–20 µg m−3 in the lower troposphere. The CCN concentration levels are always controlled by aerosol pollution. The INP concentrations were found to be high enough in the middle and upper troposphere to significantly influence ice formation in mixed-phase and ice clouds during spring and summer seasons.
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    Profiling water vapor mixing ratios in Finland by means of a Raman lidar, a satellite and a model
    (Katlenburg-Lindau : Copernicus, 2017) Filioglou, Maria; Nikandrova, Anna; Niemelä, Sami; Baars, Holger; Mielonen, Tero; Leskinen, Ari; Brus, David; Romakkaniemi, Sami; Giannakaki, Elina; Komppula, Mika
    We present tropospheric water vapor profiles measured with a Raman lidar during three field campaigns held in Finland. Co-located radio soundings are available throughout the period for the calibration of the lidar signals. We investigate the possibility of calibrating the lidar water vapor profiles in the absence of co-existing on-site soundings using water vapor profiles from the combined Advanced InfraRed Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU) satellite product; the Aire Limitée Adaptation dynamique Développement INternational and High Resolution Limited Area Model (ALADIN/HIRLAM) numerical weather prediction (NWP) system, and the nearest radio sounding station located 100 km away from the lidar site (only for the permanent location of the lidar). The uncertainties of the calibration factor derived from the soundings, the satellite and the model data are < 2.8, 7.4 and 3.9 %, respectively. We also include water vapor mixing ratio intercomparisons between the radio soundings and the various instruments/model for the period of the campaigns. A good agreement is observed for all comparisons with relative errors that do not exceed 50 % up to 8 km altitude in most cases. A 4-year seasonal analysis of vertical water vapor is also presented for the Kuopio site in Finland. During winter months, the air in Kuopio is dry (1.15±0.40 †kg-1); during summer it is wet (5.54±1.02 †kg-1); and at other times, the air is in an intermediate state. These are averaged values over the lowest 2 km in the atmosphere. Above that height a quick decrease in water vapor mixing ratios is observed, except during summer months where favorable atmospheric conditions enable higher mixing ratio values at higher altitudes. Lastly, the seasonal change in disagreement between the lidar and the model has been studied. The analysis showed that, on average, the model underestimates water vapor mixing ratios at high altitudes during spring and summer.
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    Triple-wavelength lidar observations of the linear depolarization ratio of dried marine particles
    (Les Ulis : EDP Sciences, 2018) Haarig, Moritz; Ansmann, Albert; Baars, Holger; Engelmann, Ronny; Althausen, Dietrich; Bohlmann, Stephanie; Gasteiger, Josef; Farrell, David; Nicolae, D.; Makoto, A.; Vassilis, A.; Balis, D.; Behrendt, A.; Comeron, A.; Gibert, F.; Landulfo, E.; McCormick, M.P.; Senff, C.; Veselovskii, I.; Wandinger, U.
    For aerosol typing with lidar, sea salt particles are usually assumed to be spherical with a consequently low depolarization ratio. Evidence of dried marine particles at the top of the humid marine aerosol layer with a depolarization ratio up to 0.1 has been found at predominately maritime locations on Barbados and in the Southern Atlantic. The depolarization ratio for these probably cubic sea salt particles has been measured at three wavelengths (355, 532 and 1064 nm) simultaneously for the first time and compared to model simulations.
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    Extreme levels of Canadian wildfire smoke in the stratosphere over central Europe on 21-22 August 2017
    (Katlenburg-Lindau : EGU, 2018) Ansmann, Albert; Baars, Holger; Chudnovsky, Alexandra; Mattis, Ina; Veselovskii, Igor; Haarig, Moritz; Seifert, Patric; Engelmann, Ronny; Wandinger, Ulla
    Light extinction coefficients of 500 Mm1, about 20 times higher than after the Pinatubo volcanic eruptions in 1991, were observed by European Aerosol Research Lidar Network (EARLINET) lidars in the stratosphere over central Europe on 21-22 August 2017. Pronounced smoke layers with a 1-2 km vertical extent were found 2-5 km above the local tropopause. Optically dense layers of Canadian wildfire smoke reached central Europe 10 days after their injection into the upper troposphere and lower stratosphere which was caused by rather strong pyrocumulonimbus activity over western Canada. The smoke-related aerosol optical thickness (AOT) identified by lidar was close to 1.0 at 532 nm over Leipzig during the noon hours on 22 August 2017. Smoke particles were found throughout the free troposphere (AOT of 0.3) and in the pronounced 2 km thick stratospheric smoke layer at an altitude of 14-16 km (AOT of 0.6). The lidar observations indicated peak mass concentrations of 70-100 μgm-3 in the stratosphere. In addition to the lidar profiles, we analyzed Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power (FRP) over Canada, and the distribution of MODIS AOT and Ozone Monitoring Instrument (OMI) aerosol index across the North Atlantic. These instruments showed a similar pattern and a clear link between the western Canadian fires and the aerosol load over Europe. In this paper, we also present Aerosol Robotic Network (AERONET) sun photometer observations, compare photometer and lidar-derived AOT, and discuss an obvious bias (the smoke AOT is too low) in the photometer observations. Finally, we compare the strength of this recordbreaking smoke event (in terms of the particle extinction coefficient and AOT) with major and moderate volcanic events observed over the northern midlatitudes.
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    Target categorization of aerosol and clouds by continuous multiwavelength-polarization lidar measurements
    (Katlenburg-Lindau : Copernicus, 2017) Baars, Holger; Seifert, Patric; Engelmann, Ronny; Wandinger, Ulla
    Absolute calibrated signals at 532 and 1064 nm and the depolarization ratio from a multiwavelength lidar are used to categorize primary aerosol but also clouds in high temporal and spatial resolution. Automatically derived particle backscatter coefficient profiles in low temporal resolution (30 min) are applied to calibrate the lidar signals. From these calibrated lidar signals, new atmospheric parameters in temporally high resolution (quasi-particle-backscatter coefficients) are derived. By using thresholds obtained from multiyear, multisite EARLINET (European Aerosol Research Lidar Network) measurements, four aerosol classes (small; large, spherical; large, non-spherical; mixed, partly nonspherical) and several cloud classes (liquid, ice) are defined. Thus, particles are classified by their physical features (shape and size) instead of by source. The methodology is applied to 2 months of continuous observations (24 h a day, 7 days a week) with the multiwavelength-Raman-polarization lidar PollyXT during the High-Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) in spring 2013. Cloudnet equipment was operated continuously directly next to the lidar and is used for comparison. By discussing three 24 h case studies, it is shown that the aerosol discrimination is very feasible and informative and gives a good complement to the Cloudnet target categorization. Performing the categorization for the 2-month data set of the entire HOPE campaign, almost 1 million pixel (5 min×30 m) could be analysed with the newly developed tool. We find that the majority of the aerosol trapped in the planetary boundary layer (PBL) was composed of small particles as expected for a heavily populated and industrialized area. Large, spherical aerosol was observed mostly at the top of the PBL and close to the identified cloud bases, indicating the importance of hygroscopic growth of the particles at high relative humidity. Interestingly, it is found that on several days non-spherical particles were dispersed from the ground into the atmosphere.