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- ItemEARLINET 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, GelsominaIn 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.
- 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, MarÃa 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.
- ItemAssessment 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, MarÃa 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, MartialLidar 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.
- ItemEARLINET 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, MarcoIn 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.
- 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; RodrÃguez-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 LuÃs; Amiridis, Vassilis; Kokkalis, Panagiotis; Apituley, Arnoud; Baars, Holger; Schwarz, Anja; Wandinger, Ulla; Binietoglou, Ioannis; Nicolae, Doina; Bortoli, Daniele; Comerón, Adolfo; RodrÃguez-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.