ALBERT

Description: 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) project and it is still continuing within ACTRIS (Aerosol, Clouds and Trace gases Research InfraStructure Network) project. The main idea was to develop a chain which allows all EARLINET stations to retrieve in a full 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 by two modules: a pre-processor module that 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 the input parameters needed to perform the lidar analysis are stored in a database to get them in an efficient way and also to keep track of all the changes that may occur on any EARLINET lidar system over the time. The two calculus modules and the data are coordinated and synchronized by a further module (deamon) which makes fully automatic the whole analysis process. The end-user can interact with the SCC using a user-friendly web interface. All the SCC modules are developed using open source and free available software packages. The final products retrieved by the SCC fulfill all constraints fixed in the framework of the EARLINET quality assurance programs on both instrumental and algorithm levels. Moreover the man power needed to provide aerosol optical products is greatly reduced improving the near-real time availability of lidar data. The high quality of the SCC products is demonstrated by the good agreement between the SCC analysis and the corresponding independent manual retrievals. Finally, a real example of the applicability of the SCC in providing high quality aerosol optical products in case of intense observation period is provided.

Description: Systematic measurements of dust concentration profiles at 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 dataset 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 to 6 km range, where most of 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.

Description: In this paper, we report the first systematic comparison of 12-year modeled dust extinction profiles vs. Raman lidar measurements. We use the BSC-DREAM8b model, one of the most widely used dust regional models in the Mediterranean, and Potenza EARLINET lidar profiles for Saharan dust cases, the largest one-site database of dust extinction profiles. A total of 310 dust cases were compared for the May 2000–July 2012 period. The model reconstructs the measured layers well: profiles are correlated within 5% of significance for 60% of the cases and the dust layer center of mass as measured by lidar and modeled by BSC-DREAM8b differ on average 0.3 ± 1.0 km. Events with a dust optical depth lower than 0.1 account for 70% of uncorrelated profiles. Although there is good agreement in terms of profile shape and the order of magnitude of extinction values, the model overestimates the occurrence of dust layer top above 10 km. Comparison with extinction profiles measured by the Raman lidar shows that BSC-DREAM8b typically underestimates the dust extinction coefficient, in particular below 3 km. Lowest model–observation differences (below 17%) correspond to a lidar ratio at 532 nm and Ångström exponent at 355/532 nm of 60 ± 13 and 0.1 ± 0.6 sr, respectively. These are in agreement with values typically observed and modeled for pure desert dust. However, the highest differences (higher than 85%) are typically related to greater Ångström values (0.5 ± 0.6), denoting smaller particles. All these aspects indicate that the level of agreement decreases with an increase in mixing/modification processes.

Description: This paper presents a new application of assimilating lidar signals to aerosol forecasting. It aims at investigating the impact of a ground-based lidar network on analysis and short-term forecasts of aerosols through a case study in the Mediterranean. To do so, we employ a data assimilation (DA) algorithm based on the optimal interpolation method developed in the chemistry transport model (CTM) {Polair3D of the air quality modelling platform POLYPHEMUS. We assimilate hourly-averaged normalised range corrected lidar signals (PR2) retrieved from a 72 h period of intensive and continuous measurements performed in July 2012 by ground-based lidar systems of the European Aerosol Research Lidar Network (EARLINET) integrated into the Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS) and an additional system in Corsica deployed in the framework of the pre-ChArMEx (Chemistry-Aerosol Mediterranean Experiment)/TRAQA (TRAnsport à longue distance et Qualité de l'Air) campaign. This lidar campaign was dedicated to demonstrating the potential operationality of a research network like EARLINET and the potential usefulness of assimilation of lidar signals to aerosol forecasts. Particles with an aerodynamic diameter lower than 2.5 μm (PM2.5) and those with an aerodynamic diameter higher than 2.5 μm but lower than 10 μm (PM2.5–10) are analysed separately using the lidar observations at each DA step. First, we study the spatial and temporal influences of the assimilation of lidar signals on aerosol forecasting. We conduct sensitivity studies on algorithmic parameters, e.g. the horizontal correlation length (Lh) used in the background error covariance matrix (50 km, 100 km or 200 km), the altitudes at which DA is performed (0.75–3.5 km, 1.0–3.5 km or 1.5–3.5 km a.g.l.) and the assimilation period length (12 h or 24 h). We find that DA with Lh = 100 km and assimilation from 1.0 to 3.5 km a.g.l. during a 12 h assimilation period length leads to the best scores for PM10 and PM2.5 during the forecast period with reference to available measurements from surface networks. Secondly, the aerosol simulation results without and with lidar DA using the optimal parameters (Lh

Description: We present LIVAS, a 3-dimentional multi-wavelength global aerosol and cloud optical climatology, optimized to be used for future space-based lidar end-to-end simulations of realistic atmospheric scenarios as well as retrieval algorithm testing activities. LIVAS database provides averaged profiles of aerosol optical properties for the potential space-borne laser operating wavelengths of 355, 532, 1064, 1570 and 2050 nm and of cloud optical properties at the wavelength of 532 nm. The global climatology is based on CALIPSO observations at 532 and 1064 nm and on aerosol-type-dependent spectral conversion factors for backscatter and extinction, derived from EARLINET ground-based measurements for the UV and scattering calculations for the IR wavelengths, using a combination of input data from AERONET, suitable aerosol models and recent literature. The required spectral conversion factors are calculated for each of the CALIPSO aerosol types and are applied to CALIPSO extinction and backscatter data correspondingly to the aerosol type retrieved by the CALIPSO aerosol classification scheme. A cloud climatology based on CALIPSO measurements at 532 nm is also provided, neglecting wavelength conversion due to approximately neutral scattering behavior of clouds along the spectral range of LIVAS. Averages of particle linear depolarization ratio profiles at 532 nm are provided as well. Finally, vertical distributions for a set of selected scenes of specific atmospheric phenomena (e.g., dust outbreaks, volcanic eruptions, wild fires, polar stratospheric clouds) are analyzed and spectrally converted so as to be used as case studies for space-borne lidar performance assessments. The final global climatology includes 4-year (1 January 2008–31 December 2011) time-averaged CALIPSO data on a uniform grid of 1×1 degree with the original high vertical resolution of CALIPSO in order to ensure realistic simulations of the atmospheric variability in lidar end-to-end simulations.

Description: In this paper, we report the first systematic comparison between dust extinction profiles forecasted by a model and measured by a Raman lidar. We use the BSC-DREAM8b model, one of the most widely used dust regional models in the Mediterranean, and Potenza EARLINET lidar profiles for Saharan dust cases, the largest one-site database of dust extinction profiles. A total of 310 dust cases were compared for the May 2000–July 2012 period. The model well reconstructs the measured layering: profiles are correlated within 5% of significance for 60% of the cases and the dust layer center of mass as measured by lidar and modeled by BSC-DREAM8b differ on average 0.3 ± 1.0 km. Cases with a dust optical depth lower than 0.1 account for 70% of uncorrelated profiles. Although the good agreement in terms of profile shape and extinction value order of magnitude, the comparison with extinction profiles measured by the Raman lidar shows that BSC-DREAM8b typically underestimate the dust extinction coefficient in particular below 3.5 km and for low concentrations and overestimates the occurrence of dust layer top height above 15 km.

Description: The analysis of aerosol microphysical properties profiles at different European stations is made in the framework of the ChArMEx/EMEP 2012 field campaign (9–11 July 2012). During and in support to this campaign, five lidar ground-based stations (Athens, Barcelona, Bucharest, Évora and Granada) performed 72 h of continuous lidar and collocated and coincident sun-photometer measurements. Therefore it was possible to retrieve volume concentration profiles with the Lidar Radiometer Inversion Code (LIRIC). Results indicated the presence of a mineral dust plume affecting the Western Mediterranean region (mainly Granada station) whereas a different aerosol plume was observed over the Balkans area. LIRIC profiles showed a predominance of coarse spheroid particles above Granada, as expected for mineral dust, and an aerosol plume composed mainly of fine and coarse spherical particles above Athens and Bucharest. Due to the exceptional characteristics of the ChArMEx database, the analysis of the microphysical properties profiles temporal evolution was also possible. An in depth analysis was performed mainly at Granada station because of the availability of continuous lidar measurements and frequent AERONET inversion retrievals. The analysis at Granada was of special interest since the station was affected by mineral dust during the complete analyzed period. LIRIC was found to be a very useful tool for performing continuous monitoring of mineral dust, allowing for the analysis of the dynamics of the dust event in the vertical and temporal coordinates. Results obtained here illustrate the importance of having collocated and simultaneous advanced lidar and sun-photometer measurements in order to characterize the aerosol microphysical properties both in the vertical and temporal coordinates at a regional scale. In addition, this study revealed that the use of the depolarization information as input in LIRIC in the stations of Bucharest, Évora and Granada was crucial for the characterization of the aerosol types and their distribution in the vertical column, whereas in stations lacking of depolarization lidar channels ancillary information was needed. Results obtained were also used for the validation of different mineral dust models. In general, the models better forecast the vertical distribution of the mineral dust than the column integrated mass concentration, which was underestimated in most of the cases.

Description: The CALIPSO Level 3 (CL3) product, available since December 2011, is the most recent data set produced by the observations of the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument onboard the Cloud–Aerosol Lidar and Pathfinder Satellite Observations (CALIPSO) space platform. The European Aerosol Research Lidar Network (EARLINET), based mainly on multi-wavelength Raman lidar systems, is the most appropriate ground-based reference for CALIPSO calibration/validation studies on a continental scale. In this work, CALIPSO data are compared against EARLINET monthly averaged profiles obtained by measurements performed during CALIPSO overpasess. In order to mitigate uncertainties due to spatial and temporal differences, we reproduce a modified version of CL3 data starting from CALIPSO Level 2 (CL2) data. The spatial resolution is finer and nearly 2° × 2° (latitude × longitude) and only simultaneous measurements are used for ease of comparison. The CALIPSO monthly mean profiles following this approach are called CALIPSO Level 3*, CL3*. We find good agreement on the aerosol extinction coefficient, yet in most of the cases a small CALIPSO underestimation is observed with an average bias of 0.02 km−1 up to 4 km and 0.003 km−1 higher above. In contrast to CL3 standard product, CL3* data set offers the possibility to assess the CALIPSO performance also in terms of the particle backscatter coefficient keeping the same quality assurance criteria applied to extinction profiles. The mean relative difference in the comparison improved from 26.1 % for extinction to 13.7 % for backscatter, showing better performances of CALIPSO backscatter retrievals. Additionally, the aerosol typing comparison yielded a robust identification of Dust and Polluted Dust. Moreover, the CALIPSO aerosol-type-dependent lidar ratio selection is assessed by means of EARLINET observations, so as to investigate the performance of the extinction retrievals. The aerosol types of Dust, Polluted Dust, and Clean Continental showed noticeable discrepancy. Finally, the potential improvements of the lidar ratio assignment have been examined by adjusting it according to EARLINET derived values.

Description: 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.

Description: With the establishment of ceilometer networks by national weather services, a discussion commenced to which extent these simple backscatter lidars can be used for aerosol research. Though primarily designed for the detection of clouds it was shown that at least observations of the vertical structure of the boundary layer might be possible. However, an assessment of the potential of ceilometers for the quantitative retrieval of aerosol properties is still missing. In this paper we discuss different retrieval methods to derive the aerosol backscatter coefficient βp, with special focus on the calibration of the ceilometers. Different options based on forward and backward integration methods are compared with respect to their accuracy and applicability. It is shown that advanced lidar systems such as those being operated in the framework of the European Aerosol Research Lidar Network (EARLINET) are excellent tools for the calibration, and thus βp retrievals based on forward integration can readily be implemented and used for real-time applications. Furthermore, we discuss uncertainties introduced by incomplete overlap, the unknown lidar ratio, and water vapor absorption. The latter is relevant for the very large number of ceilometers operating in the spectral range around λ = 905–910 nm. The accuracy of the retrieved βp mainly depends on the accuracy of the calibration and the long-term stability of the ceilometer. Under favorable conditions, a relative error of βp on the order of 10% seems feasible. In the case of water vapor absorption, corrections assuming a realistic water vapor distribution and laser spectrum are indispensable; otherwise errors on the order of 20% could occur. From case studies it is shown that ceilometers can be used for the reliable detection of elevated aerosol layers below 5 km, and can contribute to the validation of chemistry transport models, e.g., the height of the boundary layer. However, the exploitation of ceilometer measurements is still in its infancy, so more studies are urgently needed to consolidate the present state of knowledge, which is based on a limited number of case studies.