Optimization of lidar data processing : a goal of the EARILINET-ASOS project

Amodeo, Aldo, Mattis, Ina, Boeckmann, Christine, D'Amico, Giuseppe, Mueller, D., Osterloh, Lukas, Chaikovsky, Anatoly, Pappalardo, Gelsomina, Ansmann, Albert, Apituley, Arnoud, Alados-Arboledas, Lucas, Balis, Dimitris, Comeron, Adolfo, Freudenthaler, Volker, Mitev, Valentin, Nicolae, Doina, Papayannis, Alexandros, Perrone, Maria Rita, Pietruezuk, Aleksander, Pujadas, Manuel, Putaud, Jean-Philippe, Ravetta, Francois, Rizi, Vincenzo, Simeonovs, Valentin, Spinelli, Nicola, Stebel, Kersten, Stoyanov, Dimitar, Trickl, Thomas and Wiegner, Matthias (2007) Optimization of lidar data processing : a goal of the EARILINET-ASOS project. SPIE.
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EARLINET-ASOS (European Aerosol Research Lidar Network - Advanced Sustainable Observation System) is a 5-year EC Project started in 2006. Based on the EARLINET infrastructure, it will provide appropriate tools to improve the quality and availability of the continuous observations. The EARLINET multi-year continental scale data set is an excellent instrument to assess the impact of aerosols on the European and global environment and to support future satellite missions. The project is addressed in optimizing instruments and algorithms existing within EARLINET-ASOS, exchanging expertise, with the main goal to build a database with high quality aerosol data. In particular, the optimization of the algorithms for the retrieval of the aerosol optical and microphysical. properties is a crucial activity. The main objective is to provide all partners with the possibility to use a common processing chain for the evaluation of their data, from raw signals to final products. Raw signals may come from different types of systems, and final products are profiles of optical properties, like backscatter and extinction, and, if the instrument properties permit, of microphysical properties. This will have a strong impact on the scientific community because data with homogeneous well characterized quality will be made available in nearly real time.

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