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- ItemEARLINET 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, PasqualeThis 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.
- ItemAn EARLINET early warning system for atmospheric aerosol aviation hazards(Katlenburg-Lindau : EGU, 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, LuciaA 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).
- ItemAn 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, MatthiasWe 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.
- ItemExperimental techniques for the calibration of lidar depolarization channels in EARLINET(Katlenburg-Lindau : Copernicus, 2018) Belegante, Livio; Bravo-Aranda, Juan Antonio; Freudenthaler, Volker; Nicolae, Doina; Nemuc, Anca; Ene, Dragos; Alados-Arboledas, Lucas; Amodeo, Aldo; Pappalardo, Gelsomina; D'Amico, Giuseppe; Amato, Francesco; Engelmann, Ronny; Baars, Holger; Wandinger, Ulla; Papayannis, Alexandros; Kokkalis, Panos; Pereira, Sérgio N.Particle depolarization ratio retrieved from lidar measurements are commonly used for aerosol-typing studies, microphysical inversion, or mass concentration retrievals. The particle depolarization ratio is one of the primary parameters that can differentiate several major aerosol components but only if the measurements are accurate enough. The accuracy related to the retrieval of particle depolarization ratios is the driving factor for assessing and improving the uncertainties of the depolarization products. This paper presents different depolarization calibration procedures used to improve the quality of the depolarization data. The results illustrate a significant improvement of the depolarization lidar products for all the selected lidar stations that have implemented depolarization calibration procedures. The calibrated volume and particle depolarization profiles at 532-nm show values that fall within a range that is generally accepted in the literature.
- ItemMicrophysical 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, LucasStrong 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.