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Arctic haze over Central Europe

2017, Heintzenberg, Jost, Tuch, Thomas, Wehner, Birgit, Wiedensohler, Alfred, Wex, Heike, Ansmann, Albert, Mattis, Ina, Müller, Detlef, Wendisch, Manfred, Eckhardt, Sabine, Stohl, Andreas

An extraordinary aerosol situation over Leipzig, Germany in April 2002 was investigated with a comprehensive set of ground-based volumetric and columnar aerosol data, combined with aerosol profiles from lidar, meteorological data from radiosondes and air mass trajectory calculations. Air masses were identified to stem from the Arctic, partly influenced by the greater Moscow region. An evaluation of ground-based measurements of aerosol size distributions during these periods showed that the number concentrations below about 70 nm in diameter were below respective long-term average data, while number, surface and volume concentrations of the particles larger than about 70 nm in diameter were higher than the long-term averages. The lidar aerosol profiles showed that the imported aerosol particles were present up to about 3 km altitude. The particle optical depth was up to 0.45 at 550 nm wavelength. With a one-dimensional spectral radiative transfer model top of the atmosphere (TOA) radiative forcing of the aerosol layer was estimated for a period with detailed vertical information. Solar aerosol radiative forcing values between −23 and −38 W m−2 were calculated, which are comparable to values that have been reported in heavily polluted continental plumes outside the respective source regions. The present report adds weight to previous findings of aerosol import to Europe, pointing to the need for attributing the three-dimensional aerosol burden to natural and anthropogenic sources as well as to aerosol imports from adjacent or distant source regions. In the present case, the transport situation is further complicated by forward trajectories, indicating that some of the observed Arctic haze may have originated in Central Europe. This aerosolwas transported to the European Arctic before being re-imported in the modified and augmented form to its initial source region.

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The automated multiwavelength Raman polarization and water-vapor lidar PollyXT: The neXT generation

2016, Engelmann, Ronny, Kanitz, Thomas, Baars, Holger, Heese, Birgit, Althausen, Dietrich, Skupin, Annett, Wandinger, Ulla, Komppula, Mika, Stachlewska, Iwona S., Amiridis, Vassilis, Marinou, Eleni, Mattis, Ina, Linné, Holger, Ansmann, Albert

The atmospheric science community demands autonomous and quality-assured vertically resolved measurements of aerosol and cloud properties. For this purpose, a portable lidar called Polly was developed at TROPOS in 2003. The lidar system was continuously improved with gained experience from the EARLINET community, involvement in worldwide field campaigns, and international institute collaborations within the last 10 years. Here we present recent changes of the setup of the portable multiwavelength Raman and polarization lidar PollyXT and discuss the improved capabilities of the system by means of a case study. The latest system developments include an additional near-range receiver unit for Raman measurements of the backscatter and extinction coefficient down to 120 m above ground, a water-vapor channel, and channels for simultaneous measurements of the particle linear depolarization ratio at 355 and 532 nm. Quality improvements were achieved by systematically following the EARLINET guidelines and the international PollyNET quality assurance developments. A modified ship radar ensures measurements in agreement with air-traffic safety regulations and allows for 24∕7 monitoring of the atmospheric state with PollyXT.

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EARLINET Single Calculus Chain – technical – Part 2: Calculation of optical products

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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Extreme levels of Canadian wildfire smoke in the stratosphere over central Europe on 21-22 August 2017

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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PollyNET - an emerging network of automated raman-polarizarion lidars for continuous aerosolprofiling

2018, Baars, Holger, Althausen, Dietrich, Engelmann, Ronny, Heese, Birgit, Ansmann, Albert, Wandinger, Ulla, Hofer, Julian, Skupin, Annett, Komppula, Mika, Giannakaki, Eleni, Filioglou, Maria, Bortoli, Daniele, Silva, Ana Maria, Pereira, Sergio, Stachlewska, Iwona S., Kumala, Wojciech, Szczepanik, Dominika, Amiridis, Vassilis, Marinou, Eleni, Kottas, Michail, Mattis, Ina, Müller, Gerhard, 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.

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.

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EARLINET Single Calculus Chain – technical – Part 1: Pre-processing of raw lidar data

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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EARLINET evaluation of the CATS Level 2 aerosol backscatter coefficient product

2019, Proestakis, Emmanouil, Amiridis, Vassilis, Marinou, Eleni, Binietoglou, Ioannis, Ansmann, Albert, Wandinger, Ulla, Hofer, Julian, Yorks, John, Nowottnick, Edward, Makhmudov, Abduvosit, Papayannis, Alexandros, Pietruczuk, Aleksander, Gialitaki, Anna, Apituley, Arnoud, Szkop, Artur, Muñoz Porcar, Constantino, Bortoli, Daniele, Dionisi, Davide, Althausen, Dietrich, Mamali, Dimitra, Balis, Dimitris, Nicolae, Doina, Tetoni, Eleni, Liberti, Gian Luigi, Baars, Holger, Mattis, Ina, Stachlewska, Iwona Sylwia, Voudouri, Kalliopi Artemis, Mona, Lucia, Mylonaki, Maria, Perrone, Maria Rita, Costa, Maria João, Sicard, Michael, Papagiannopoulos, Nikolaos, Siomos, Nikolaos, Burlizzi, Pasquale, Pauly, Rebecca, Engelmann, Ronny, Abdullaev, Sabur, Pappalardo, Gelsomina

We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the Cloud-Aerosol Transport System (CATS) aboard the International Space Station (ISS; Rodier et al., 2015). The study employs correlative CATS and EARLINET backscatter measurements within a 50km distance between the ground station and the ISS overpass and as close in time as possible, typically with the starting time or stopping time of the EARLINET performed measurement time window within 90min of the ISS overpass, for the period from February 2015 to September 2016. The results demonstrate the good agreement of the CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig, Germany; Évora, Portugal; and Dushanbe, Tajikistan, are analyzed here to demonstrate the performance of the CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions, CATS is in good agreement with EARLINET, independent of daytime and nighttime conditions. CATS low negative biases are observed, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds; these are biases which may lead to systematic deviations and slight underestimations of the total aerosol optical depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, occasionally leads to non-representative, unrealistic, and cloud-contaminated aerosol profiles. Regarding solar illumination conditions, low negative biases in CATS backscatter coefficient profiles, of the order of 6.1%, indicate the good nighttime performance of CATS. During daytime, a reduced signal-to-noise ratio by solar background illumination prevents retrievals of weakly scattering atmospheric layers that would otherwise be detectable during nighttime, leading to higher negative biases, of the order of 22.3%. © Author(s) 2019.

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Earlinet single calculus chain: New products overview

2018, D’Amico, Giuseppe, Mattis, Ina, Binietoglou, Ioannis, Baars, Holger, Mona, Lucia, Amato, Francesco, Kokkalis, Panos, Rodríguez-Gómez, Alejandro, Soupiona, Ourania, Kalliopi-Artemis, Voudouri, 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.

The Single Calculus Chain (SCC) is an automatic and flexible tool to analyze raw lidar data using EARLINET quality assured retrieval algorithms. It has been already demonstrated the SCC can retrieve reliable aerosol backscatter and extinction coefficient profiles for different lidar systems. In this paper we provide an overview of new SCC products like particle linear depolarization ratio, cloud masking, aerosol layering allowing relevant improvements in the atmospheric aerosol characterization.

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EARLINET instrument intercomparison campaigns: Overview on strategy and results

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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An EARLINET early warning system for atmospheric aerosol aviation hazards

2020, Papagiannopoulos, Nikolaos, D’Amico, Giuseppe, Gialitaki, Anna, Ajtai, Nicolae, Alados-Arboledas, Lucas, Amodeo, Aldo, Amiridis, Vassilis, Baars, Holger, Balis, Dimitris, Binietoglou, Ioannis, Comerón, Adolfo, Dionisi, Davide, Falconieri, Alfredo, Fréville, Patrick, Kampouri, Anna, Mattis, Ina, Mijić, Zoran, Molero, Francisco, Papayannis, Alex, Pappalardo, Gelsomina, Rodríguez-Gómez, Alejandro, Solomos, Stavros, Mona, Lucia

A stand-alone lidar-based method for detecting airborne hazards for aviation in near real time (NRT) is presented. A polarization lidar allows for the identification of irregular-shaped particles such as volcanic dust and desert dust. The Single Calculus Chain (SCC) of the European Aerosol Research Lidar Network (EARLINET) delivers high-resolution preprocessed data: the calibrated total attenuated backscatter and the calibrated volume linear depolarization ratio time series. From these calibrated lidar signals, the particle backscatter coefficient and the particle depolarization ratio can be derived in temporally high resolution and thus provide the basis of the NRT early warning system (EWS). In particular, an iterative method for the retrieval of the particle backscatter is implemented. This improved capability was designed as a pilot that will produce alerts for imminent threats for aviation. The method is applied to data during two diverse aerosol scenarios: first, a record breaking desert dust intrusion in March 2018 over Finokalia, Greece, and, second, an intrusion of volcanic particles originating from Mount Etna, Italy, in June 2019 over Antikythera, Greece. Additionally, a devoted observational period including several EARLINET lidar systems demonstrates the network's preparedness to offer insight into natural hazards that affect the aviation sector. © 2020 Author(s).