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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 water cycle strongly influence life on Earth and precipitation especially modifies the atmospheric column thermodynamics through the evaporation process and serving as a proxy for latent heat modulation. For this reason, a correct light precipitation parameterization at global scale, it is of fundamental importance, bedsides improving our understanding of the hydrological cycle, to reduce the associated uncertainty of the global climate models to correctly forecast future scenarios. In this context we developed a full automatic algorithm based on morphological filters that, once operational, will make available a new rain product for the NASA Micropulse Lidar Network (MPLNET) and the European Aerosol Research Lidar Network (EARLINET) in the frame of WMO GALION Project

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 INTERACT-II (INTERcomparison of Aerosol and Cloud Tracking) campaign, performed at the CNR-IMAA Atmospheric Observatory (760 m a.s.l., 40.60° N, 15.72° E), aims to evaluate the performances of commercial automatic lidars and ceilometers for atmospheric aerosol profiling, through the comparison with Potenza EARLINET (European Aerosol Research Lidar NETwork) lidars. The results of the campaign and the overall lesson learnt within INTERACT-I and INTERACT-II ACTRIS campaigns 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 Aerosols, Clouds and Trace gases Research Infrastructure (ACTRIS) is a distributed infrastructure dedicated to high-quality observation of aerosols, clouds, trace gases and exploration of their interactions. It will deliver precision data, services and procedures regarding the 4D variability of clouds, short-lived atmospheric species and the physical, optical and chemical properties of aerosols to improve the current capacity to analyse, understand and predict past, current and future evolution of the atmospheric environment.

The purpose of this study is to investigate the ability of the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) to derive accurate geometrical features of lofted aerosol layers on a continental scale. Comparisons with ground-based correlative measurements constitute a key component in the validation of passive satellite aerosol products. For this purpose, we use ground-based observations from quality controlled lidar stations reporting to the European Aerosol Research Lidar Network (EARLINET). An optimal methodology for validation purposes has been developed and applied using the EARLINET optical profiles and TROPOMI aerosol products, aiming at the in-depth evaluation of the TROPOMI Aerosol Layer Height (ALH), product over the Mediterranean Basin for the period 2018 to 2021, over the Mediterranean Basin. Seven EARLINET stations across the Mediterranean were chosen, taking into consideration their proximity to the sea, which provided 34 coincident aerosol cases for the satellite retrievals. In the following, we present the first validation results for the TROPOMI/S5P ALH using the optimized EARLINET lidar products employing the automated validation chain designed for this purpose. The quantitative validation at pixels over the selected EARLINET stations illustrates that TROPOMI ALH is consistent with EARLINET, with a high correlation coefficient R=0.9 (R=0.59) and a mean bias of -1.02±0.96 km (-1.46±1.57 km) over ocean and ocean/land pixels respectively. Overall, it appears that aerosol layer altitudes retrieved from TROPOMI are systematically lower than altitudes from the lidar retrievals. This work confirms that the TROPOMI ALH product is within the required threshold accuracy and precision requirements of 1 km. Furthermore, we describe and analyse three case studies in detail, one dust and two smoke episodes, in order to illustrate the strengths and limitations of TROPOMI ALH product and demonstrate the presented validation methodology. [ABSTRACT FROM AUTHOR]

This paper presents the newly established Lidar Calibration Centre, a distributed infrastructure in Europe, whose goal is to offer services for complete characterization and calibration of lidars and ceilometers. Mobile reference lidars, laboratories for testing and characterization of optics and electronics, facilities for inspection and debugging of instruments, as well as for training in good practices are open to users from the scientific community, operational services and private sector. The Lidar Calibration Centre offers support for trans-national access through the EC HORIZON2020 project ACTRIS-2.

CALIPSO (Cloud-Aerosol Lidar and Pathfinder Satellite Observations) Level 3 (CL3) data were compared against EARLINET (European Aerosol Research Lidar Network) monthly averages obtained by profiles during satellite overpasses. Data from EARLINET stations of Évora, Granada, Leipzig, Naples and Potenza, equipped with advanced multi-wavelength Raman lidars were used for this study. Owing to spatial and temporal differences, we reproduced the CL3 filtering rubric onto the CALIPSO Level 2 data. The CALIPSO monthly mean profiles following this approach are called CALIPSO Level 3*, CL3*. This offers the possibility to achieve direct comparable datasets. In respect to CL3 data, the agreement typically improved, in particular above the areas directly affected by the anthropogenic activities within the planetary boundary layer. However in most of the cases a subtle CALIPSO underestimation was observed with an average bias of 0.03 km-1. We investigated the backscatter coefficient applying the same screening criteria, where the mean relative difference in respect to the extinction comparison improved from 15.2% to 11.4%. Lastly, the typing capabilities of CALIPSO were assessed outlining the importance of the correct aerosol type (and associated lidar ratio value) assessment to the CALIPSO aerosol properties retrieval.

A methodology for the study of cloud droplet activation based on the measurements performed with ground-based multi-wavelength Raman lidars and ancillary remote sensors collected at CNR-IMAA observatory, Potenza, South Italy, is presented. The study is focused on the observation of thin warm clouds. Thin clouds are often also optically thin: this allows the cloud top detection and the full profiling of cloud layers using ground-based Raman lidar. Moreover, broken clouds are inspected to take advantage of their discontinuous structure in order to study the variability of optical properties and water vapor content in the transition from cloudy regions to cloudless regions close to the cloud boundaries. A statistical study of this variability leads to identify threshold values for the optical properties, enabling the discrimination between clouds and cloudless regions. These values can be used to evaluate and improve parameterizations of droplet activation within numerical models. A statistical study of the co-located Doppler radar moments allows to retrieve droplet size and vertical velocities close to the cloud base. First evidences of a correlation between droplet vertical velocities measured at the cloud base and the aerosol effective radius observed in the cloud-free regions of the broken clouds are found.

An intercomparison of the algorithms used to retrieve aerosol extinction and backscatter starting from Raman lidar signals has been performed by 11 groups of lidar scientists involved in the European Aerosol Research Lidar Network (EARLINET). This intercomparison is part of an extended quality assurance program performed on aerosol lidars in the EARLINET. Lidar instruments and aerosol backscatter algorithms were tested separately. The Raman lidar algorithms were tested by use of synthetic lidar data, simulated at 355, 532, 386, and 607 nm, with realistic experimental and atmospheric conditions taken into account. The intercomparison demonstrates that the data-handling procedures used by all the lidar groups provide satisfactory results. Extinction profiles show mean deviations from the correct solution within 10% in the planetary boundary layer (PBL), and backscatter profiles, retrieved by use of algorithms based on the combined Raman elastic-backscatter lidar technique, show mean deviations from solutions within 20% up to 2 km. The intercomparison was also carried out for the lidar ratio and produced profiles that show a mean deviation from the solution within 20% in the PBL. The mean value of this parameter was also calculated within a lofted aerosol layer at higher altitudes that is representative of typical layers related to special events such as Saharan dust outbreaks, forest fires, and volcanic eruptions. Here deviations were within 15%. OCIS codes: 010.3640, 280.1100, 290.1090, 290.5860, 290.2200.

An intercomparison of aerosol backscatter lidar algorithms was performed in 2001 within the framework of the European Aerosol Research Lidar Network to Establish an Aerosol Climatology (EARLINET). The objective of this research was to test the correctness of the algorithms and the influence of the lidar ratio used by the various lidar teams involved in the EARLINET for calculation of backscatter-coefficient profiles from the lidar signals. The exercise consisted of processing synthetic lidar signals of various degrees of difficulty. One of these profiles contained height-dependent lidar ratios to test the vertical influence of those profiles on the various retrieval algorithms. Furthermore, a realistic incomplete overlap of laser beam and receiver field of view was introduced to remind the teams to take great care in the nearest range to the lidar. The intercomparison was performed in three stages with increasing knowledge on the input parameters. First, only the lidar signals were distributed; this is the most realistic stage. Afterward the lidar ratio profiles and the reference values at calibration height were

Climate trends estimated using historical radiosounding time series may be significantly affected by the choice of the regression method to use, as well as by a subsampling of the dataset often adopted in specific applications. These are contributions to the uncertainty of trend estimations, which have been quantified in literature, although on specific pairs of regression methods, and in the not very recent past characterized by smaller trends in temperature than those observed over the last two decades. This paper investigates the sensitivity of trend estimations to four linear regression methods (parametric and nonparametric) and to the artificial subsampling of the same dataset using historical radiosounding time series from 1978 onwards, available in the version 2 of the Integrated Global Radiosonde Archive (IGRA). Results show that long‐term decadal trends may have not negligible uncertainties related to the choice of the regression method, the percentage of data available, the amount of missing data and the number of stations selected in the dataset. The choice of the regression methods increases uncertainties in the decadal trends ranging from −0.10 to −0.01 K⋅da–1 for temperature in the lower stratosphere at 100 hPa and from 0.2 to 0.8% da–1 for relative humidity (RH) in the middle troposphere at 300 hPa. Differences can also increase up to 0.4 K⋅da–1 at 300 hPa when the amount of missing data exceeds 50% of the original dataset for temperature, while for RH, significant differences are observed in the lower troposphere at 925 hPa for almost all datasets. Finally, subsampling effects on trend estimation are quantified by artificially reducing the size of the IGRA dataset: Results show that subsampling effects on trend estimations when at least 60 stations, up to 76% of data available, are considered for temperature and at least 40 stations for RH. [ABSTRACT FROM AUTHOR]

The Atmospheric Boundary Layer (ABL) represents the lowermost part of the atmosphere directly in contact with the Earth surface. The estimation of its depth is of crucial importance in meteorology and for anthropogenic pollution studies. The ABL Height (ABLH) measurements are usually far from being adequate, both spatially and temporally. Thus, different remote sensing sources can be of great help in growing both the spatial and temporal ABLH measurement capabilities. To this aim, aerosol backscatter profiles are widely used as proxy to retrieve the ABLH. Hence, the scientific community is making remarkable efforts in developing automatic ABLH retrieval algorithms applied to lidar observations. In this paper, we propose a ABLH estimation algorithm based on image processing techniques applied to the composite image of the total attenuated backscatter coefficient. A pre-processing step is applied to the composite total backscatter image based on morphological filters to properly set-up and adjust the image to detect edges. As final step, the detected edges are post-processed through both mathematical morphology and an object-based analysis. The performance of the proposed approach is assessed on real data acquired by two different lidar systems, deployed in Potenza (Italy) and Evora (Portugal), belonging to the EARLINET network. The proposed approach has shown higher performance than the benchmark consisting of some state-of-the-art ABLH estimation methods. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the potential of GOME-2 instruments on board the MetOpA, MetOpB and MetOpC platforms, to deliver accurate geometrical features of lofted aerosol layers. For this purpose, we use archived ground-based lidar data from lidar stations available fromEuropean Aerosol Research Lidar Network (EARLINET) database. The data are post-processed with the wavelet covariance transform (WCT) method in order to extract geometrical features such as the Planetary Boundary Layer, PBL, height and the cloud boundaries. To obtain a significant number of collocated and coincident GOME-2 - EARLINET cases for the period between January 2007 and September 2019, fourteenlidar stations, distributed over different European latitudes, contributed to this validation. For the 172 carefully screened collocations, the mean bias was found to be -0.18 ± 1.68 km, with a near Gaussian distribution. On a station-basis, and with a couple of exceptions where very few collocations were found, their mean biases fall in the ± 1 km range with an associated standard deviation between 0.5 and 1.5 km. Considering the differences, mainly due to the temporal collocation and the difference between the satellite pixel size and the point view of the ground-based observations, these results are quite promising and demonstrating that stable and extended aerosol layers as captured by the satellite sensors, are verified by the ground-based data. We further present an in-depth analysis of a strong and long-lasting Saharan dust intrusion over the Iberian Peninsula. We show that for, this well-developed and spatially well-spread aerosol layer, most GOME-2 retrievals fall within 1 km of the exactly temporally collocated lidar observation for the entire range of 0 to 150 km radii. This finding further testifies to the capabilities of the MetOp-born instruments to sense the atmospheric aerosol layer height. [ABSTRACT FROM AUTHOR]