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- ItemEARLINET Single Calculus Chain – technical – Part 1: Pre-processing of raw lidar data(München : European Geopyhsical Union, 2016) D'Amico, Giuseppe; Amodeo, Aldo; Mattis, Ina; Freudenthaler, Volker; Pappalardo, GelsominaIn this paper we describe an automatic tool for the pre-processing of aerosol lidar data called ELPP (EARLINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of ELPP, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns.
- ItemAssessment of lidar depolarization uncertainty by means of a polarimetric lidar simulator(München : European Geopyhsical Union, 2016) Bravo-Aranda, Juan Antonio; Belegante, Livio; Freudenthaler, Volker; Alados-Arboledas, Lucas; Nicolae, Doina; Granados-Muñoz, María José; Guerrero-Rascado, Juan Luis; Amodeo, Aldo; D'Amico, Giusseppe; Engelmann, Ronny; Pappalardo, Gelsomina; Kokkalis, Panos; Mamouri, Rodanthy; Papayannis, Alex; Navas-Guzmán, Francisco; Olmo, Francisco José; Wandinger, Ulla; Amato, Francesco; Haeffelin, MartialLidar depolarization measurements distinguish between spherical and non-spherical aerosol particles based on the change of the polarization state between the emitted and received signal. The particle shape information in combination with other aerosol optical properties allows the characterization of different aerosol types and the retrieval of aerosol particle microphysical properties. Regarding the microphysical inversions, the lidar depolarization technique is becoming a key method since particle shape information can be used by algorithms based on spheres and spheroids, optimizing the retrieval procedure. Thus, the identification of the depolarization error sources and the quantification of their effects are crucial. This work presents a new tool to assess the systematic error of the volume linear depolarization ratio (δ), combining the Stokes–Müller formalism and the complete sampling of the error space using the lidar model presented in Freudenthaler (2016a). This tool is applied to a synthetic lidar system and to several EARLINET lidars with depolarization capabilities at 355 or 532 nm. The lidar systems show relative errors of δ larger than 100 % for δ values around molecular linear depolarization ratios (∼ 0.004 and up to ∼ 10 % for δ = 0.45). However, one system shows only relative errors of 25 and 0.22 % for δ = 0.004 and δ = 0.45, respectively, and gives an example of how a proper identification and reduction of the main error sources can drastically reduce the systematic errors of δ. In this regard, we provide some indications of how to reduce the systematic errors.
- 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.
- ItemEARLINET Single Calculus Chain – technical – Part 2: Calculation of optical products(München : European Geopyhsical Union, 2016) Mattis, Ina; D'Amico, Giuseppe; Baars, Holger; Amodeo, Aldo; Madonna, Fabio; Iarlori, MarcoIn this paper we present the automated software tool ELDA (EARLINET Lidar Data Analyzer) for the retrieval of profiles of optical particle properties from lidar signals. This tool is one of the calculus modules of the EARLINET Single Calculus Chain (SCC) which allows for the analysis of the data of many different lidar systems of EARLINET in an automated, unsupervised way. ELDA delivers profiles of particle extinction coefficients from Raman signals as well as profiles of particle backscatter coefficients from combinations of Raman and elastic signals or from elastic signals only. Those analyses start from pre-processed signals which have already been corrected for background, range dependency and hardware specific effects. An expert group reviewed all algorithms and solutions for critical calculus subsystems which are used within EARLINET with respect to their applicability for automated retrievals. Those methods have been implemented in ELDA. Since the software was designed in a modular way, it is possible to add new or alternative methods in future. Most of the implemented algorithms are well known and well documented, but some methods have especially been developed for ELDA, e.g., automated vertical smoothing and temporal averaging or the handling of effective vertical resolution in the case of lidar ratio retrievals, or the merging of near-range and far-range products. The accuracy of the retrieved profiles was tested following the procedure of the EARLINET-ASOS algorithm inter-comparison exercise which is based on the analysis of synthetic signals. Mean deviations, mean relative deviations, and normalized root-mean-square deviations were calculated for all possible products and three height layers. In all cases, the deviations were clearly below the maximum allowed values according to the EARLINET quality requirements. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns.
- ItemSeparation of the optical and mass features of particle components in different aerosol mixtures by using POLIPHON retrievals in synergy with continuous polarized Micro-Pulse Lidar (P-MPL) measurements(Katlenburg-Lindau : Copernicus, 2018) Córdoba-Jabonero, Carmen; Sicard, Michaël; Ansmann, Albert; del Águila, Ana; Baars, HolgerThe application of the POLIPHON (POlarization-LIdar PHOtometer Networking) method is presented for the first time in synergy with continuous 24/7 polarized Micro-Pulse Lidar (P-MPL) measurements to derive the vertical separation of two or three particle components in different aerosol mixtures, and the retrieval of their particular optical properties. The procedure of extinction-to-mass conversion, together with an analysis of the mass extinction efficiency (MEE) parameter, is described, and the relative mass contribution of each aerosol component is also derived in a further step. The general POLIPHON algorithm is based on the specific particle linear depolarization ratio given for different types of aerosols and can be run in either 1-step (POL-1) or 2 steps (POL-2) versions with dependence on either the 2- or 3-component separation. In order to illustrate this procedure, aerosol mixing cases observed over Barcelona (NE Spain) are selected: a dust event on 5 July 2016, smoke plumes detected on 23 May 2016 and a pollination episode observed on 23 March 2016. In particular, the 3-component separation is just applied for the dust case: a combined POL-1 with POL-2 procedure (POL-1/2) is used, and additionally the fine-dust contribution to the total fine mode (fine dust plus non-dust aerosols) is estimated. The high dust impact before 12:00 UTC yields a mean mass loading of 0.6±0.1 g m'2 due to the prevalence of Saharan coarse-dust particles. After that time, the mean mass loading is reduced by two-thirds, showing a rather weak dust incidence. In the smoke case, the arrival of fine biomass-burning particles is detected at altitudes as high as 7 km. The smoke particles, probably mixed with less depolarizing non-smoke aerosols, are observed in air masses, having their origin from either North American fires or the Arctic area, as reported by HYSPLIT back-trajectory analysis. The particle linear depolarization ratio for smoke shows values in the 0.10-0.15 range and even higher at given times, and the daily mean smoke mass loading is 0.017±0.008 g m'2, around 3 % of that found for the dust event. Pollen particles are detected up to 1.5 km in height from 10:00 UTC during an intense pollination event with a particle linear depolarization ratio ranging between 0.10 and 0.15. The maximal mass loading of Platanus pollen particles is 0.011±0.003 g m'2, representing around 2 % of the dust loading during the higher dust incidence. Regarding the MEE derived for each aerosol component, their values are in agreement with others referenced in the literature for the specific aerosol types examined in this work: 0.5±0.1 and 1.7±0.2 m2 g'1 are found for coarse and fine dust particles, 4.5±1.4 m2 g'1 is derived for smoke and 2.4±0.5 m2 g'1 for non-smoke aerosols with Arctic origin, and a MEE of 2.4±0.8 m2 g'1 is obtained for pollen particles, though it can reach higher or lower values depending on predominantly smaller or larger pollen grain sizes. Results reveal the high potential of the P-MPL system, a simple polarization-sensitive elastic backscatter lidar working in a 24/7 operation mode, to retrieve the relative optical and mass contributions of each aerosol component throughout the day, reflecting the daily variability of their properties. In fact, this procedure can be simply implemented in other P-MPLs that also operate within the worldwide Micro-Pulse Lidar Network (MPLNET), thus extending the aerosol discrimination at a global scale. Moreover, the method has the advantage of also being relatively easily applicable to space-borne lidars with an equivalent configuration such as the ongoing Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) on board NASA CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) and the forthcoming Atmospheric Lidar (ATLID) on board the ESA EarthCARE mission.
- ItemNew particle formation in the Svalbard region 2006-2015(Katlenburg-Lindau : EGU, 2017) Heintzenberg, Jost; Tunved, Peter; Galí, Martí; Leck, CarolineEvents of new particle formation (NPF) were analyzed in a 10-year data set of hourly particle size distributions recorded on Mt. Zeppelin, Spitsbergen, Svalbard. Three different types of NPF events were identified through objective search algorithms. The first and simplest algorithm utilizes short-term increases in particle concentrations below 25 nm (PCT (percentiles) events). The second one builds on the growth of the sub-50 nm diameter median (DGR (diameter growth) events) and is most closely related to the classical "banana type" of event. The third and most complex, multiple-size approach to identifying NPF events builds on a hypothesis suggesting the concurrent production of polymer gel particles at several sizes below ca. 60 nm (MEV (multisize growth) events). As a first and general conclusion, we can state that NPF events are a summer phenomenon and not related to Arctic haze, which is a late winter to early spring feature. The occurrence of NPF events appears to be somewhat sensitive to the available data on precipitation. The seasonal distribution of solar flux suggests some photochemical control that may affect marine biological processes generating particle precursors and/or atmospheric photochemical processes that generate condensable vapors from precursor gases. Notably, the seasonal distribution of the biogenic methanesulfonate (MSA) follows that of the solar flux although it peaks before the maxima in NPF occurrence. A host of ancillary data and findings point to varying and rather complex marine biological source processes. The potential source regions for all types of new particle formation appear to be restricted to the marginal-ice and open-water areas between northeastern Greenland and eastern Svalbard. Depending on conditions, yet to be clarified new particle formation may become visible as short bursts of particles around 20 nm (PCT events), longer events involving condensation growth (DGR events), or extended events with elevated concentrations of particles at several sizes below 100 nm (MEV events). The seasonal distribution of NPF events peaks later than that of MSA and DGR, and in particular than that of MEV events, which reach into late summer and early fall with open, warm, and biologically active waters around Svalbard. Consequently, a simple model to describe the seasonal distribution of the total number of NPF events can be based on solar flux and sea surface temperature, representing environmental conditions for marine biological activity and condensation sink, controlling the balance between new particle nucleation and their condensational growth. Based on the sparse knowledge about the seasonal cycle of gel-forming marine microorganisms and their controlling factors, we hypothesize that the seasonal distribution of DGR and, more so, MEV events reflect the seasonal cycle of the gel-forming phytoplankton.
- ItemCombining cloud radar and radar wind profiler for a value added estimate of vertical air motion and particle terminal velocity within clouds(Göttingen : Copernicus GmbH, 2018) Radenz, M.; Bühl, J.; Lehmann, V.; Görsdorf, U.; Leinweber, R.Vertical-stare observations from a 482MHz radar wind profiler and a 35GHz cloud radar are combined on the level of individual Doppler spectra to measure vertical air motions in clear air, clouds and precipitation. For this purpose, a separation algorithm is proposed to remove the influence of falling particles from the wind profiler Doppler spectra and to calculate the terminal fall velocity of hydrometeors. The remaining error of both vertical air motion and terminal fall velocity is estimated to be better than 0.1ms-1 using numerical simulations. This combination of instruments allows direct measurements of in-cloud vertical air velocity and particle terminal fall velocity by means of ground-based remote sensing. The possibility of providing a profile every 10s with a height resolution of < 100m allows further insight into the process scale of in-cloud dynamics. The results of the separation algorithm are illustrated by two case studies, the first covering a deep frontal cloud and the second featuring a shallow mixed-phase cloud.
- ItemAlgorithms and uncertainties for the determination of multispectral irradiance components and aerosol optical depth from a shipborne rotating shadowband radiometer(Katlenburg-Lindau : Copernicus, 2017) Witthuhn, Jonas; Deneke, Hartwig; Macke, Andreas; Bernhard, GermarThe 19-channel rotating shadowband radiometer GUVis-3511 built by Biospherical Instruments provides automated shipborne measurements of the direct, diffuse and global spectral irradiance components without a requirement for platform stabilization. Several direct sun products, including spectral direct beam transmittance, aerosol optical depth, Ångström exponent and precipitable water, can be derived from these observations. The individual steps of the data analysis are described, and the different sources of uncertainty are discussed. The total uncertainty of the observed direct beam transmittances is estimated to be about 4% for most channels within a 95% confidence interval for shipborne operation. The calibration is identified as the dominating contribution to the total uncertainty. A comparison of direct beam transmittance with those obtained from a Cimel sunphotometer at a land site and a manually operated Microtops II sunphotometer on a ship is presented. Measurements deviate by less than 3 and 4% on land and on ship, respectively, for most channels and in agreement with our previous uncertainty estimate. These numbers demonstrate that the instrument is well suited for shipborne operation, and the applied methods for motion correction work accurately. Based on spectral direct beam transmittance, aerosol optical depth can be retrieved with an uncertainty of 0.02 for all channels within a 95% confidence interval. The different methods to account for Rayleigh scattering and gas absorption in our scheme and in the Aerosol Robotic Network processing for Cimel sunphotometers lead to minor deviations. Relying on the cross calibration of the 940 nm water vapor channel with the Cimel sunphotometer, the column amount of precipitable water can be estimated with an uncertainty of ±0.034 cm.
- ItemAn automatic observation-based aerosol typing method for EARLINET(Katlenburg-Lindau : EGU, 2018) Papagiannopoulos, Nikolaos; Mona, Lucia; Amodeo, Aldo; D'Amico, Giuseppe; Gumà Claramunt, Pilar; Pappalardo, Gelsomina; Alados-Arboledas, Lucas; Guerrero-Rascado, Juan Luís; Amiridis, Vassilis; Kokkalis, Panagiotis; Apituley, Arnoud; Baars, Holger; Schwarz, Anja; Wandinger, Ulla; Binietoglou, Ioannis; Nicolae, Doina; Bortoli, Daniele; Comerón, Adolfo; Rodríguez-Gómez, Alejandro; Sicard, Michaël; Papayannis, Alex; Wiegner, MatthiasWe present an automatic aerosol classification method based solely on the European Aerosol Research Lidar Network (EARLINET) intensive optical parameters with the aim of building a network-wide classification tool that could provide near-real-time aerosol typing information. The presented method depends on a supervised learning technique and makes use of the Mahalanobis distance function that relates each unclassified measurement to a predefined aerosol type. As a first step (training phase), a reference dataset is set up consisting of already classified EARLINET data. Using this dataset, we defined 8 aerosol classes: clean continental, polluted continental, dust, mixed dust, polluted dust, mixed marine, smoke, and volcanic ash. The effect of the number of aerosol classes has been explored, as well as the optimal set of intensive parameters to separate different aerosol types. Furthermore, the algorithm is trained with literature particle linear depolarization ratio values. As a second step (testing phase), we apply the method to an already classified EARLINET dataset and analyze the results of the comparison to this classified dataset. The predictive accuracy of the automatic classification varies between 59% (minimum) and 90% (maximum) from 8 to 4 aerosol classes, respectively, when evaluated against pre-classified EARLINET lidar. This indicates the potential use of the automatic classification to all network lidar data. Furthermore, the training of the algorithm with particle linear depolarization values found in the literature further improves the accuracy with values for all the aerosol classes around 80%. Additionally, the algorithm has proven to be highly versatile as it adapts to changes in the size of the training dataset and the number of aerosol classes and classifying parameters. Finally, the low computational time and demand for resources make the algorithm extremely suitable for the implementation within the single calculus chain (SCC), the EARLINET centralized processing suite.