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The Aerosol, Clouds and Trace Gases Research Infrastructure ACTRIS is currently being developed with support from more than 20 countries and more than 100 research-performing organizations in Europe. The pan-European distributed research infrastructure shall provide data and services related to short-lived atmospheric constituents to facilitate high-quality Earth system research in the long term (over at least 20 years). While some of the activities are already in place, ACTRIS functionality will be further ramped up until full operation in 2025. The observation of aerosol, clouds and reactive trace gases with in-situ and remote-sensing techniques in ACTRIS is supported by six Topical Centres, which are responsible for common standards and quality assurance. Free and open virtual access to ACTRIS data is provided by the Data Centre. International users will also have physical access to ACTRIS observatories, atmospheric simulation chambers and mobile platforms as well as remote or physical access to calibration services, digital services and training. Access provision is organized through a single-entry point by the Head Office. In this contribution, the general principles and structure of ACTRIS are introduced, and the observational component related to aerosol remote sensing, which builds on the heritage of the European Aerosol Research Lidar Network (EARLINET) and the European part of the Aerosol Robotic Network (AERONET-Europe), is explained in more detail.

The vulnerability of the (European) aviation system to the airborne hazards was evident during the Eyjafjallajökull volcanic eruption in 2010. For support of Air Traffic Control (ATC) many observations of the event were available from satellites, ground based instruments and airborne platforms, at pan-European scale. However, efficient use of the data for ATC proved difficult mainly due to sub-optimal aggregation and integrated assessment of the available information in near-real-time. The project EUNADICS-AV (European Natural Disaster Coordination and Information System for Aviation) aims to close this gap. The observational component of the project will make existing data products for airborne hazards more accessible, visible and used, and to foster tailored product development. Once assimilated into models and integrated in the EUNADICS-AV Data Portal these data can be the base to efficiently improve European airspace resilience to airborne hazards. Since 2010 new data products have become available specifically for for airborne hazard alerting and monitoring together with specific tailored products designed for replying to user needs and recommendations. This paper describes the EUNADICS-AV approach and will focus on the role of operational and research grade ground based lidars.

The biomass burning events are analyzed using the EARLINET-ACTRIS atmospheric profiling of aerosols using lidars. The period of 2008-2017 was chosen to analyze all the events assigned in the EARLINET database under Forest Fire category. A number of fourteen stations were considered. The data provided, ranged from complete data sets (backscatter, extinction and particle linear depolarization ratio) to single profiles (backscatter coefficient). A thorough quality control was performed. Smoke layers geometry was evaluated and the mean properties within each layer were computed. The Hysplit backward-trajectory technique and the FIRMS fire database were used to double check the source of each layer. Discussions were made under the following scenarios: fire events seen by two stations, long range transport from North America, and geographical clusters.

The paper presents the preliminary results of the lidar&radiometer measurement campaign (LRMC-2017), estimation of statistical relations between aerosol mode concentrations retrieved from CALIOP and ground-based lidar stations and case study of fire smoke events in the Eurasian regions using combined ground-based and space lidar and radiometer observations.

Aerosol reanalysis datasets are model-based, observationally constrained, continuous 3D aerosol fields with a relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects, and impacts on socioeconomic sectors, such as health. Here we compare and assess the recently published MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) high-resolution regional desert dust reanalysis over northern Africa, the Middle East, and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS (MODerate resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging SpectroRadiometer), and IASI (Infrared Atmospheric Sounding Interferometer) spaceborne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products are factors that bias the reanalysis assessment. We, therefore, also use ground-based DOD observations provided by 238 stations of the AERONET (AErosol RObotic NETwork) located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking these results into consideration, the MONARCH reanalysis assessment shows that total and coarse-DOD simulations are consistent with satellite- and ground-based data, qualitatively capturing the major dust sources in the area in addition to the dust transport patterns. Moreover, the MONARCH reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity that occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model's removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases are found over the Sahara desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (- 0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low, as the low relative bias in the Sahara desert (< 50 %) and over the adjacent maritime regions (< 100 %) certifies. Similarly, over areas with intense dust activity, the linear correlation coefficient between the MONARCH reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean, and the Arabian Sea and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions for which large numbers of observations are available, thus allowing for robust reanalysis assessment. [ABSTRACT FROM AUTHOR]

Aerosol typing is essential for understanding the impact of the different aerosol sources on climate, weather system and air quality. An aerosol classification method for EARLINET (European Aerosol Research Lidar Network) measurements is introduced which makes use the Mahalanobis distance classifier. The performance of the automatic classification is tested against manually classified EARLINET data. Results of the application of the method to an extensive aerosol dataset will be presented.

The Cloud-Aerosol Transport System (CATS) onboard the International Space Station (ISS), is a lidar system providing vertically resolved aerosol and cloud profiles since February 2015. In this study, the CATS aerosol product is validated against the aerosol profiles provided by the European Aerosol Research Lidar Network (EARLINET). This validation activity is based on collocated CATS-EARLINET measurements and the comparison of the particle backscatter coefficient at 1064nm.

The EARLINET database is facing a complete reshaping to meet the wide request for more intuitive products and to face the even wider request related to the new initiatives such as Copernicus, the European Earth observation programme. The new design has been carried out in continuity with the past, to take advantage from long-term database. In particular, the new structure will provide information suitable for synergy with other instruments, near real time (NRT) applications, validation and process studies and climate applications.

The Single Calculus Chain (SCC) is an automatic and flexible tool to analyze raw lidar data using EARLINET quality assured retrieval algorithms. It has been already demonstrated the SCC can retrieve reliable aerosol backscatter and extinction coefficient profiles for different lidar systems. In this paper we provide an overview of new SCC products like particle linear depolarization ratio, cloud masking, aerosol layering allowing relevant improvements in the atmospheric aerosol characterization.

Aerosol reanalysis datasets are model-based observationally constrained continuous 3D aerosol fields with relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects and impacts upon socio-economic sectors, such as health. Here we compare and assess the recently published MONARCH high resolution regional desert dust reanalysis over Northern Africa, the Middle East and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS, MISR and IASI space-borne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows for at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products, are factors that bias the reanalysis assessment. We, therefore, also used ground-based DOD observations provided by 238 stations of the AERONET network located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking into consideration these results, the MONARCH reanalysis assessment showed that total and coarse DOD simulations are consistent with satellite and ground-based data, capturing qualitatively the major dust sources in the area as well as the dust transport patterns. Moreover, the reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases were found over the Sahara Desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (-0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low as the low relative bias in the Sahara Desert (< 0.5) and over the adjacent maritime regions (< 1), certifies. Similarly, over areas with intense dust activity the linear correlation coefficient between the reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean and the Arabian Sea, and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions where large amounts of observations are available, allowing for robust model assessment. [ABSTRACT FROM AUTHOR]