Search Results
EARLINET Single Calculus Chain – overview on methodology and strategy
2015, D'Amico, Giuseppe, Amodeo, A., Baars, H., Binietoglou, I., Freudenthaler, V., Mattis, I., Wandinger, U., Pappalardo, G.
In this paper we describe the EARLINET Single Calculus Chain (SCC), a tool for the automatic analysis of lidar measurements. The development of this tool started in the framework of EARLINET-ASOS (European Aerosol Research Lidar Network – Advanced Sustainable Observation System); it was extended within ACTRIS (Aerosol, Clouds and Trace gases Research InfraStructure Network), and it is continuing within ACTRIS-2. The main idea was to develop a data processing chain that allows all EARLINET stations to retrieve, in a fully automatic way, the aerosol backscatter and extinction profiles starting from the raw lidar data of the lidar systems they operate. The calculus subsystem of the SCC is composed of two modules: a pre-processor module which handles the raw lidar data and corrects them for instrumental effects and an optical processing module for the retrieval of aerosol optical products from the pre-processed data. All input parameters needed to perform the lidar analysis are stored in a database to keep track of all changes which may occur for any EARLINET lidar system over the time. The two calculus modules are coordinated and synchronized by an additional module (daemon) which makes the whole analysis process fully automatic. The end user can interact with the SCC via a user-friendly web interface. All SCC modules are developed using open-source and freely available software packages. The final products retrieved by the SCC fulfill all requirements of the EARLINET quality assurance programs on both instrumental and algorithm levels. Moreover, the manpower needed to provide aerosol optical products is greatly reduced and thus the near-real-time availability of lidar data is improved. The high-quality of the SCC products is proven by the good agreement between the SCC analysis, and the corresponding independent manual retrievals. Finally, the ability of the SCC to provide high-quality aerosol optical products is demonstrated for an EARLINET intense observation period.
Surface matters: Limitations of CALIPSO V3 aerosol typing in coastal regions
2014, Kanitz, T., Ansmann, A., Foth, A., Seifert, P., Wandinger, U., Engelmann, R., Baars, H., Althausen, D., Casiccia, C., Zamorano, F.
In the CALIPSO data analysis, surface type (land/ocean) is used to augment the aerosol characterization. However, this surface-dependent aerosol typing prohibits a correct classification of marine aerosol over land that is advected from ocean to land. This might result in a systematic overestimation of the particle extinction coefficient and of the aerosol optical thickness (AOT) of up to a factor of 3.5 over land in coastal areas. We present a long-term comparison of CALIPSO and ground-based lidar observations of the aerosol conditions in the coastal environment of southern South America (Punta Arenas, Chile, 53° S), performed in December 2009–April 2010. Punta Arenas is almost entirely influenced by marine particles throughout the year, indicated by a rather low AOT of 0.02–0.04. However, we found an unexpectedly high fraction of continental aerosol in the aerosol types inferred by means of CALIOP observations and, correspondingly, too high values of particle extinction. Similar features of the CALIOP data analysis are presented for four other coastal areas around the world. Since CALIOP data serve as important input for global climate models, the influence of this systematic error was estimated by means of simplified radiative-transfer calculations.
One year of Raman lidar observations of free-tropospheric aerosol layers over South Africa
2015, Giannakaki, E., Pfüller, A., Korhonen, K., Mielonen, T., Laakso, L., Vakkari, V., Baars, H., Engelmann, R., Beukes, J.P., Van Zyl, P.G., Josipovic, M., Tiitta, P., Chiloane, K., Piketh, S., Lihavainen, H., Lehtinen, K.E.J., Komppula, M.
Raman lidar data obtained over a 1 year period has been analysed in relation to aerosol layers in the free troposphere over the Highveld in South Africa. In total, 375 layers were observed above the boundary layer during the period 30 January 2010 to 31 January 2011. The seasonal behaviour of aerosol layer geometrical characteristics, as well as intensive and extensive optical properties were studied. The highest centre heights of free-tropospheric layers were observed during the South African spring (2520 ± 970 m a.g.l., also elsewhere). The geometrical layer depth was found to be maximum during spring, while it did not show any significant difference for the rest of the seasons. The variability of the analysed intensive and extensive optical properties was high during all seasons. Layers were observed at a mean centre height of 2100 ± 1000 m with an average lidar ratio of 67 ± 25 sr (mean value with 1 standard deviation) at 355 nm and a mean extinction-related Ångström exponent of 1.9 ± 0.8 between 355 and 532 nm during the period under study. Except for the intensive biomass burning period from August to October, the lidar ratios and Ångström exponents are within the range of previous observations for urban/industrial aerosols. During Southern Hemispheric spring, the biomass burning activity is clearly reflected in the optical properties of the observed free-tropospheric layers. Specifically, lidar ratios at 355 nm were 89 ± 21, 57 ± 20, 59 ± 22 and 65 ± 23 sr during spring (September–November), summer (December–February), autumn (March–May) and winter (June–August), respectively. The extinction-related Ångström exponents between 355 and 532 nm measured during spring, summer, autumn and winter were 1.8 ± 0.6, 2.4 ± 0.9, 1.8 ± 0.9 and 1.8 ± 0.6, respectively. The mean columnar aerosol optical depth (AOD) obtained from lidar measurements was found to be 0.46 ± 0.35 at 355 nm and 0.25 ± 0.2 at 532 nm. The contribution of free-tropospheric aerosols on the AOD had a wide range of values with a mean contribution of 46%.
A methodology for investigating dust model performance using synergistic EARLINET/AERONET dust concentration retrievals
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.
Technical Note: One year of Raman-lidar measurements in Gual Pahari EUCAARI site close to New Delhi in India – Seasonal characteristics of the aerosol vertical structure
2012, Komppula, M., Mielonen, T., Arola, A., Korhonen, K., Lihavainen, H., Hyvärinen, A.-P., Baars, H., Engelmann, R., Althausen, D., Ansmann, A., Müller, D., Panwar, T.S., Hooda, R.K., Sharma, V.P., Kerminen, V.-M., Lehtinen, K.E.J., Viisanen, Y.
One year of multi-wavelength (3 backscatter + 2 extinction + 1 depolarization) Raman lidar measurements at Gual Pahari, close to New Delhi, were analysed. The data was split into four seasons: spring (March–May), summer (June–August), autumn (September–November) and winter (December–February). The vertical profiles of backscatter, extinction, and lidar ratio and their variability during each season are presented. The measurements revealed that, on average, the aerosol layer was at its highest in spring (5.5 km). In summer, the vertically averaged (between 1–3 km) backscatter and extinction coefficients had the highest averages (3.3 Mm−1 sr−1 and 142 Mm−1 at 532 nm, respectively). Aerosol concentrations were slightly higher in summer compared to other seasons, and particles were larger in size. The autumn showed the highest lidar ratio and high extinction-related Ångström exponents (AEext), indicating the presence of smaller probably absorbing particles. The winter had the lowest backscatter and extinction coefficients, but AEext was the highest, suggesting still a large amount of small particles.