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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.
Lidar-Radiometer Inversion Code (LIRIC) for the retrieval of vertical aerosol properties from combined lidar/radiometer data: Development and distribution in EARLINET
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.
Profiling of aerosol microphysical properties at several EARLINET/AERONET sites during the July 2012 ChArMEx/EMEP campaign
2016, Granados-Muñoz, María José, Navas-Guzmán, Francisco, Guerrero-Rascado, Juan Luis, Bravo-Aranda, Juan Antonio, Pereira, Sergio Nepomuceno, Basart, Sara, Baldasano, José María, Belegante, Livio, Chaikovsky, Anatoli, Comerón, Adolfo, D'Amico, Giuseppe, Dubovik, Oleg, Ilic, Luka, Kokkalis, Panos, Muñoz-Porcar, Constantino, Nickovic, Slobodan, Nicolae, Doina, Facchini, Maria Cristina, Olmo, Francisco José, Papayannis, Alexander, Pappalardo, Gelsomina, Rodríguez, Alejandro, Schepanski, Kerstin, Sicard, Michaël, Vukovic, Ana, Wandinger, Ulla, Dulac, François, Alados-Arboledas, Lucas
The simultaneous analysis of aerosol microphysical properties profiles at different European stations is made in the framework of the ChArMEx/EMEP 2012 field campaign (9–11 July 2012). During and in support of this campaign, five lidar ground-based stations (Athens, Barcelona, Bucharest, Évora, and Granada) performed 72 h of continuous lidar measurements and collocated and coincident sun-photometer measurements. Therefore it was possible to retrieve volume concentration profiles with the Lidar Radiometer Inversion Code (LIRIC). Results indicated the presence of a mineral dust plume affecting the western Mediterranean region (mainly the Granada station), whereas a different aerosol plume was observed over the Balkans area. LIRIC profiles showed a predominance of coarse spheroid particles above Granada, as expected for mineral dust, and an aerosol plume composed mainly of fine and coarse spherical particles above Athens and Bucharest. Due to the exceptional characteristics of the ChArMEx database, the analysis of the microphysical properties profiles' temporal evolution was also possible. An in-depth analysis was performed mainly at the Granada station because of the availability of continuous lidar measurements and frequent AERONET inversion retrievals. The analysis at Granada was of special interest since the station was affected by mineral dust during the complete analyzed period. LIRIC was found to be a very useful tool for performing continuous monitoring of mineral dust, allowing for the analysis of the dynamics of the dust event in the vertical and temporal coordinates. Results obtained here illustrate the importance of having collocated and simultaneous advanced lidar and sun-photometer measurements in order to characterize the aerosol microphysical properties in both the vertical and temporal coordinates at a regional scale. In addition, this study revealed that the use of the depolarization information as input in LIRIC in the stations of Bucharest, Évora, and Granada was crucial for the characterization of the aerosol types and their distribution in the vertical column, whereas in stations lacking depolarization lidar channels, ancillary information was needed. Results obtained were also used for the validation of different mineral dust models. In general, the models better forecast the vertical distribution of the mineral dust than the column-integrated mass concentration, which was underestimated in most of the cases.