3 results
Search Results
Now showing 1 - 3 of 3
- ItemGARRLiC and LIRIC: Strengths and limitations for the characterization of dust and marine particles along with their mixtures(Katlenburg-Lindau : Copernicus, 2017) Tsekeri, Alexandra; Lopatin, Anton; Amiridis, Vassilis; Marinou, Eleni; Igloffstein, Julia; Siomos, Nikolaos; Solomos, Stavros; Kokkalis, Panagiotis; Engelmann, Ronny; Baars, Holger; Gratsea, Myrto; Raptis, Panagiotis I.; Binietoglou, Ioannis; Mihalopoulos, Nikolaos; Kalivitis, Nikolaos; Kouvarakis, Giorgos; Bartsotas, Nikolaos; Kallos, George; Basart, Sara; Schuettemeyer, Dirk; Wandinger, Ulla; Ansmann, Albert; Chaikovsky, Anatoli P.; Dubovik, OlegThe Generalized Aerosol Retrieval from Radiometer and Lidar Combined data algorithm (GARRLiC) and the LIdar-Radiometer Inversion Code (LIRIC) provide the opportunity to study the aerosol vertical distribution by combining ground-based lidar and sun-photometric measurements. Here, we utilize the capabilities of both algorithms for the characterization of Saharan dust and marine particles, along with their mixtures, in the south-eastern Mediterranean during the CHARacterization of Aerosol mixtures of Dust and Marine origin Experiment (CHARADMExp). Three case studies are presented, focusing on dust-dominated, marinedominated and dust-marine mixing conditions. GARRLiC and LIRIC achieve a satisfactory characterization for the dust-dominated case in terms of particle microphysical properties and concentration profiles. The marine-dominated and the mixture cases are more challenging for both algorithms, although GARRLiC manages to provide more detailed microphysical retrievals compared to AERONET, while LIRIC effectively discriminates dust and marine particles in its concentration profile retrievals. The results are also compared with modelled dust and marine concentration profiles and surface in situ measurements.
- ItemLidar-Radiometer Inversion Code (LIRIC) for the retrieval of vertical aerosol properties from combined lidar/radiometer data: Development and distribution in EARLINET(München : European Geopyhsical Union, 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, XuanThis 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.
- ItemA methodology for investigating dust model performance using synergistic EARLINET/AERONET dust concentration retrievals(München : European Geopyhsical Union, 2015) Binietoglou, I.; Basart, S.; Alados-Arboledas, L.; Amiridis, V.; Argyrouli, A.; Baars, H.; Baldasano, J.M.; Balis, D.; Belegante, L.; Bravo-Aranda, J.A.; Burlizzi, P.; Carrasco, V.; Chaikovsky, A.; Comerón, A.; D'Amico, G.; Filioglou, M.; Granados-Muñoz, M.J.; Haefele, A.; Hervo, M.; Iarlori, M.; Kokkalis, P.; Lange, D.; Mamouri, R.E.; Mattis, I.; Molero, F.; Montoux, N.; Muñoz, A.; Muñoz Porcar, C.; Navas-Guzmán, F.; Nicolae, D.; Nisantzi, A.; Papagiannopoulos, N.; Papayannis, A.; Pereira, S.; Preißler, J.; Pujadas, M.; Rizi, V.; Rocadenbosch, F.; Sellegri, K.; Simeonov, V.; Tsaknakis, G.; Wagner, F.; Pappalardo, G.Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAMABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1–6 km range, where most dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of -40 to -20 μg m−3 at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies.