Articles | Volume 18, issue 21
https://doi.org/10.5194/acp-18-15879-2018
https://doi.org/10.5194/acp-18-15879-2018
Research article
 | 
06 Nov 2018
Research article |  | 06 Nov 2018

An automatic observation-based aerosol typing method for EARLINET

Nikolaos Papagiannopoulos, Lucia Mona, Aldo Amodeo, Giuseppe D'Amico, Pilar Gumà Claramunt, Gelsomina Pappalardo, Lucas Alados-Arboledas, Juan Luís Guerrero-Rascado, Vassilis Amiridis, Panagiotis Kokkalis, Arnoud Apituley, Holger Baars, Anja Schwarz, Ulla Wandinger, Ioannis Binietoglou, Doina Nicolae, Daniele Bortoli, Adolfo Comerón, Alejandro Rodríguez-Gómez, Michaël Sicard, Alex Papayannis, and Matthias Wiegner

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Cited articles

Alados-Arboledas, L., Müller, D., Guerrero-Rascado, J. L., Navas-Guzmán, F., Pérez-Ramírez, D., and Olmo, F. J.: Optical and microphysical properties of fresh biomass burning aerosol retrieved by Raman lidar, and star- and sun-photometry, Geophys. Res. Lett., 38, L01807, https://doi.org/10.1029/2010GL045999, 2011. a, b
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Ansmann, A., Wagner, F., Althausen, D., Müller, D., Herber, A., and Wandinger, U.: European pollution outbreaks during ACE 2: Lofted aerosol plumes observed with Raman lidar at the Portuguese coast, J. Geophys. Res., 106, D18, https://doi.org/10.1029/2000JD000091, 2001. a
Ansmann, A., Bösenberg, J., Chaikovsky, A., Comeròn, A., Eckhardt, S., Eixmann, R., Freudenthaler, V., Ginoux, P., Komguem, L., Linné, H., Márquez, M. A. L., Matthias, V., Mattis, I., Mitev, V., Müller, D., Music, S., Nickovic, S., Pelon, J., Sauvage, L., Sobolewsky, P., Srivastava, M., Stohl, A., Torres, O., Vaughan, G., Wandinger, U., and Wiegner, M.: Long-range transport of Saharan dust to northern Europe: The 11–16 October 2001 outbreak observed with EARLINET, J. Geophys. Res., 108, D24, https://doi.org/10.1029/2003JD003757, 2003. a
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Short summary
A stand-alone automatic method for typing observations of the European Aerosol Research Lidar Network (EARLINET) is presented. The method compares the observations to model distributions that were constructed using EARLINET pre-classified data. The algorithm’s versatility and adaptability makes it suitable for network-wide typing studies.
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