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We present newly developed software for the data analysis and quality assurance of lidar systems operated in the ACTRIS (Aerosol Clouds and Trace Gases Research Infrastructure) research infrastructure. The software development is coordinated by the Meteorological Institute of Munich (MIM), which operates as one of the central facilities of the Center of Aerosol Remote Sensing (CARS) of ACTRIS. In the frame of ACTRIS, a large number of national facilities (NF) are operating lidar systems for aerosol remote sensing. In order to ensure homogeneously high data quality, CARS is developing appropriate common software tools to assist data processing, system intercomparison, and routine quality assurance of lidar data. Here, we present two such software tools, developed and tested using the long experience of the EARLINET (European Aerosol Research Lidar Network) community.The ARC (Algorithm for Rayleigh Calculations) has been designed to calculate the cross-section and depolarization ratio of molecular back-scattering. The effect of Rotational Raman (RR) scattering is included line-by-line in ARC considering especially the partial blocking of the RR spectrum due to transmission through narrow-band interference filters. The algorithm supports calculation in variable meteorological conditions for an atmosphere that consists of up to five major gas components (N2, O2, CO2, Ar, H2O). Such a tool is needed in order to properly take into account the effect of air temperature in the molecular depolarization ratio measured by the NF lidar systems. It is also crucial for designing lidars that rely on RR scattering such as temperature and RR aerosol lidars and can even be applied for the algorithmic correction of unwanted effects introduced by the interference filter in such systems.The second software package developed by CARS-MIM is ATLAS (AuTomated Lidar Analysis Software). It has been designed for the operational analysis of the quality assurance tests that should be regularly performed and submitted to CARS by the NF for the ACTRIS labeling process. ATLAS currently supports the analysis of all main CARS test procedures, that is, the Rayleigh fit, the Telecover, and the Polarization Calibration. It can also be used to directly compare signals from two lidar systems; It has already been applied in the first intercomparison campaign of CARS reference systems, organized in September 2022 in Magurele, Romania. The software takes raw lidar data as input so the user can detect otherwise-hidden issues in the preprocessing steps. At the time of writing, ATLAS is compatible with all ACTRIS lidar systems. Future updates will include automated syncing of the system metadata from the handbook of instruments of the network, currently hosted by the Single Calculus Chain (SCC), and a graphical user interface that will facilitate its adoption by the NF users. Both software packages are written in python and are open-source projects.

Understanding the macrophysical and microphysical processes within a convective environment is highly important to strengthen the resilience and adaptation to severe weather. The ACCuReSy project targets a topic a topic under debate within the international scientific community but less tackled in Romania: the aerosol-cloud interactions. By using state-of-the-art remote sensing instruments from new exploratory platforms placed within relevant two locations chosen by their relevance for the environmental factors that meet the conditions for observing convective development either thermal and dynamical, the project aims to perform advanced research on the atmospheric environment before, during and shortly after the convective events and to investigate the aerosol-cloud interactions with special attention on the factors that contribute to the hail formation. Here we present briefly the work performed during the first phase of the project and the future steps in achieving our goals.Key words: aerosol-clouds interactions, cloud macro- and microphysics, convective clouds, severe weatherAcknowledgment: This work is funded by a grant of the Ministry of Research, Innovation and Digitization, CCCDI - UEFISCDI, project number PN-III-P2-2.1-PED-2021-1938, ctr. No. 713PED, and partially supported by the Romanian National Core Program Contract No.11N/03.01 2023 and by the Romanian Ministry of Research, Innovation and Digitalization, through Program 1- Development of the national research-development system, Subprogram 1.2 - Institutional performance - Projects to finance the excellent RDI, Contract no. 18PFE/30.12.2021

The methodology of analysing the biomass burning events recorded in the database of the European Aerosol Research Lidar Network in the framework of the Aerosol, Clouds and Trace Gases Research Infrastructure is presented. The period of 2008–2017 was chosen to analyse all of the events stored in the database under the Forest Fire category for a total of 14 stations available. The data provided ranged from complete datasets (particle backscatter, extinction and linear depolarization ratio profiles) to single profiles (particle backscatter coefficient profile). Smoke layers geometry was evaluated and the mean optical properties within each layer were computed. The back-trajectory technique was used to double-check the source of all pollution layers. The biomass burning layers were identified by taking into account the presence of the fires along the back trajectory. The biomass burning events are analysed by the means of the intensive parameters. The analysis was structured in three directions: (I) common biomass burning source (fire) recorded by at least two stations, (II) long-range transport from North America, and (III) analysis over four geographical regions (south-eastern Europe, north-eastern Europe, central Europe, and south-western Europe). Based on back-trajectory calculations and fire locations, the lidar measurements can be labelled either as measurements of a “single fire” or “mixed fires” (case I), measurements of North American fires, or measurements of mixed North American and local fires (case II). The histogram of the fire locations reveals the smoke sources for each region. For each region, statistics on intensive parameters are performed. The source origin of the intensive parameters is categorized based on the continental origin of the air mass (European, African, Asian, North American, or a combination of them). The methodology presented here is meant to provide a perspective to explore a large number of lidar data and deliver novel approaches to analyse the intensive parameters based on the assigned biomass burning sources. A thorough consideration of all potential fire sources reveals that most of the time the lidar measurements characterize the smoke from a mixture of fires. A comprehensive discussion of all the results (based on the intensive parameters and the source locations) will be given in a companion paper submitted to the ACP EARLINET special issue.

In this erratum Eqs. (10) and (11) are corrected. Note that the routines created to perform the calculations were correct and thus, all the calculations in the paper [Appl. Opt. 51, 2135 (2012)APOPAI0003-693510.1364/AO.51.002135] were correct.

Biomass burning episodes measured at 14 stations of the European Aerosol Research Lidar Network (EARLINET) over 2008–2017 were analysed using the methodology described in "Biomass burning events measured by lidars in EARLINET – Part 1: Data analysis methodology" (Adam et al., 2020, this issue). The smoke layers were identified in lidar optical properties profiles. A number of 795 layers for which we measured at least one intensive parameter was analysed. These layers were geographically distributed as follows: 399 layers observed in South-East Europe, 119 layers observed in South-West Europe, 243 layers observed in North-East Europe, and 34 layers observed in Central Europe. The mean layer intensive parameters are discussed following two research directions: (I) the long-range transport of smoke particles from North America, and (II) the smoke properties (fresh versus aged), separating the smoke events into four continental source regions (European, North American, African, Asian or a mixture of two), based on back trajectory analysis. The smoke detected in Central Europe (Cabauw, Leipzig, and Hohenpeißenberg) was mostly transported from North America (87 % of fires). In North-East Europe (Belsk, Minsk, Warsaw) smoke advected mostly from Eastern Europe (Ukraine and Russia), but there was a significant contribution (31 %) from North America. In South-West Europe (Barcelona, Evora, Granada) smoke originated mainly from the Iberian Peninsula and North Africa (while 9 % were originating in North America). In the South-East Europe (Athens, Bucharest, Potenza, Sofia, Thessaloniki) the origin of the smoke was mostly local (only 3 % represented North America smoke). The following features, correlated with the increased smoke travel time (corresponding to aging) were found: the colour ratio of the lidar ratio (i.e., the ratio of the lidar ratio at 532 nm to the lidar ratio at 355 nm) and the colour ratio of the backscatter Ångström exponent (i.e., the ratio of the backscatter-related Angstrom exponent for the pair 532 nm – 1064 nm to the one for the pair 355 nm – 532 nm) increase, while the extinction Ångström exponent and the colour ratio of the particle depolarization ratio (i.e., the ratio of the particle linear depolarization ratio at 532 nm to the particle depolarization ratio at 355 nm) decrease. The smoke originating from all continental regions can be characterized on average as aged smoke, with a very few exceptions. In general, the long range transported smoke shows higher lidar ratio and lower depolarization ratio compared to the local smoke.

Biomass burning events are analysed using the European Aerosol Research Lidar Network database for atmospheric profiling of aerosols by lidars. Atmospheric profiles containing forest fires layers were identified in data collected by fourteen stations during 2008–2017. The data ranged from complete data sets (particle backscatter coefficient, extinction coefficient and linear depolarization ratio) to single profiles (particle backscatter coefficient). The data analysis methodology was described in Part I (Biomass burning events measured by lidars in EARLINET. Part I. Data analysis methodology, under discussions to ACP, the EARLINET special issue). The results are analysed by means of intensive parameters in three directions: (I) common biomass burning source (fire) recorded by at least two stations, (II) long range transport of smoke particles from North America (here, we divided the events into pure North America and mixed-North America and local) smoke groups, and (III) analysis of smoke particles over four geographical regions (SE Europe, NE Europe, Central Europe and SW Europe). Five events were found for case (I), while 24 events were determined for case (II). A statistical analysis over the four geographical regions considered revealed that smoke originated from different regions. The smoke detected in the Central Europe region (Cabauw, Leipzig, and Hohenpeißenberg) was mostly brought over from North America (87 % of the fires), by long range transport. The smoke in the South West region (Barcelona, Evora, and Granada) came mostly from the Iberian Peninsula and North Africa, the long-range transport from North America accounting for only 9 % here. The smoke in the North Europe region (Belsk, Minsk, and Warsaw) originated mostly in East Europe (Ukraine and Russia), and had a 31 % contribution from smoke by long-range transport from North America. For the South East region (Athens, Bucharest, Potenza, Sofia, Thessaloniki) the origin of the smoke was mostly located in SE Europe (only 3 % from North America). Specific features for the lidar-derived intensive parameters based on smoke continental origin were determined for each region. Based on the whole dataset, the following signatures were observed: (i) the colour ratio of the lidar ratio and the backscatter Ångström exponent increase with travel time, while the extinction Ångström exponent and the colour ratio of the particle depolarization ratio decrease; (ii) an increase of the colour ratio of the particle depolarization ratio corresponds to both a decrease of the colour ratio of the lidar ratios and an increase of the extinction Ångström exponent; (iii) the measured smoke originating from all continental regions is characterized in average as aged smoke, except for a few cases; (iv) in general, the local smoke shows a smaller lidar ratio while the long range transported smoke shows a higher lidar ratio; and (v) the depolarization is smaller for long range transported smoke. A complete characterization of the smoke particles type (either fresh or aged) is presented for each of the four geographical regions versus different continental source regions.

On 15–16 October 2017, ex-hurricane Ophelia passed to the west of the British Isles, bringing dust from the Sahara and smoke from Portuguese forest fires that was observable to the naked eye and reported in the UK's national press. We report here detailed observations of this event using the UK operational lidar and sun-photometer network, established for the early detection of aviation hazards, including volcanic ash. We also use ECMWF ERA5 wind field data and MODIS imagery to examine the aerosol transport. The observations, taken continuously over a period of 30 h, show a complex picture, dominated by several different aerosol layers at different times and clearly correlated with the passage of different air masses associated with the intense cyclonic system. A similar evolution was observed at several sites, with a time delay between them explained by their different location with respect to the storm and associated meteorological features. The event commenced with a shallow dust layer at 1–2 km in altitude and culminated in a deep and complex structure that lasted ∼12 h at each site over the UK, correlated with the storm's warm sector. For most of the time, the aerosol detected was dominated by mineral dust mixtures, as highlighted by depolarisation measurements, but an intense biomass burning aerosol (BBA) layer was observed towards the end of the event, lasting around 3 h at each site. The aerosol optical depth at 355 nm (AOD355) during the whole event ranged from 0.2 to 2.9, with the larger AOD correlated to the intense BBA layer. Such a large AOD is unprecedented in the UK according to AERONET records for the last 20 years. The Raman lidars permitted the measurement of the aerosol extinction coefficient at 355 nm, the particle linear depolarisation ratio (PLDR), and the lidar ratio (LR) and made the separation of the dust (depolarising) aerosol from other aerosol types possible. A specific extinction has also been computed to provide an estimate of the atmospheric concentration of both aerosol types separately, which peaked at 420±200 µg m−3 for the dust and 558±232 µg m−3 for the biomass burning aerosols. Back trajectories computed using the Numerical Atmospheric-dispersion Modelling Environment (NAME) were used to identify the sources and strengthen the conclusions drawn from the observations. The UK network represents a significant expansion of the observing capability in northern Europe, with instruments evenly distributed across Great Britain, from Camborne in Cornwall to Lerwick in the Shetland Islands, and this study represents the first attempt to demonstrate its capability and validate the methods in use. Its ultimate purpose will be the detection and quantification of volcanic plumes, but the present study clearly demonstrates the advanced capabilities of the network.

The methodology of analysing the biomass burning events recorded in the database of the European Aerosol Research Lidar Network in the frame of Aerosol Cloud and Trace Gases Research Infrastructure is presented. The period of 2008–2017 was chosen to analyse all of the events stored in the database under Forest Fire category for a number of 14 stations available. The data provided ranged from complete data sets (particle backscatter, extinction and linear depolarization ratio profiles) to single profiles (particle backscatter coefficient profile). Smoke layers geometry was evaluated and the mean optical properties within each layer were computed. The backtrajectories technique was used to double check the source of all pollution layers. The biomass burning layers were identified taking into account the presence of the fires along the backtrajectory. The biomass burning events are analysed by the means of the intensive parameters. The analysis was structured in three directions: I) common biomass burning source (fire) recorded by at least two stations, II) long-range transport from N. America, III) analysis over four geographical regions (SE Europe, NE Europe, Central Europe and SW Europe). Based on backtrajectories calculations and fires’ location, the lidar measurements can be labelled either as measurements of ‘single fire’ or ‘mixed fires’ (case I), measurements of N America fires or measurements of mixed N America and local fires (case II). The histogram of the fires’ location reveals the smoke sources for each region. For each region, statistics on intensive parameters is performed. The sources’ origin of the intensive parameters is categorized based on the continental origin of the air-mass (European, African, Asian, N American or a combination of them). The methodology presented here is meant to provide a perspective to explore large amount of lidar data and deliver novel approaches to analyse the intensive parameters based on the assigned biomass burning sources. A thorough consideration of all potential fires’ sources reveals that most of the time the lidar measurements characterise the smoke from a mixture of fires. A comprehensive discussion over all results (based on the intensive parameters and the sources’ location), will be given in a companion paper submitted to ACP EARLINET special issue.

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.

An automatic alert system is implemented in order to detect atmospheric pollution layers and establish the degree of pollution load. When such layers are heavily loaded, automatic alerts are sent towards designed scientists in order to further analyze the event and inform the relevant stakeholders. The alert system is based on continuous measurements taken by a ceilometer supplemented by a photometer. Backtrajectory model is used to establish the pollution source.

On 15–16 October 2017, ex-hurricane Ophelia passed to the West of the British Isles, bringing dust from the Sahara and smoke from Portuguese forest fires that was observable to the naked eye and reported in the national press. We report here detailed observations of this event using the UK operational lidar and sun-photometer network, established for the early detection of aviation hazards. The observations, taken continuously over a period of 30 hours, show a complex picture, dominated by several aerosol layers at different times, and clearly correlated with the passage of different air-masses associated with the intense cyclonic system. A similar evolution was observed at several sites, with a time delay between them explained by their different location with respect to the storm. The event commenced with a hallow dust layer at 1–2 km in altitude, and culminated in a deep and complex structure that lasted 12 hours at each site, correlated with the storm’s warm sector. For most of the time, the aerosol detected as mineral dust, as highlighted by depolarisation measurements, but an intense smoke layer was observed towards the end of the event, lasting around 3 hours at each site. The aerosol optical depth AOD) during the whole event ranged from 0.2 to 2.9, with the larger AOD correlated to the intense smoke plume. Such a large AOD is unprecedented in the United Kingdom according to AERONET records or the last 20 years. The Raman lidars permitted the measurement of the aerosol extinction coefficient at 355 nm, the particle depolarisation ratio (PDR) and the lidar ratio (LR), and made possible the separation of the dust (depolarising) aerosol from other aerosol types. A specific extinction has also been computed to provide an estimate of the atmospheric concentration of both aerosols separately, which peaked at 500 ± 100 μg m−3 for the dust and 600 ± 100 μg m−3 for the smoke. Back-trajectories computed using the Numerical Atmospheric dispersion Modelling Environment (NAME) were used to identify the sources and strengthen the conclusions drawn from the observations. The UK network represents a significant expansion of the observing capability in Northern Europe, with instruments evenly distributed across Great Britain, from Camborne in Cornwall to Lerwick in the Shetland Islands, and this study represents the first attempt to demonstrate its capability and validate the methods in use. Its ultimate purpose will be the detection and quantification of volcanic plumes, but the present study clearly demonstrates the advanced capabilities of the network.

Water vapor mixing ratio retrieval using the Howard University Raman lidar is presented with emphasis on three aspects: (i) comparison of the lidar with collocated radiosondes and Raman lidar, (ii) investigation of the relationship between atmospheric state variables and the relative performance of the lidar and sonde (in particular, their poor agreement), and (iii) comparison with satellite-based measurements. The measurements were acquired during the Water Vapor Validation Experiment Sondes/Satellites 2006 campaign. Ensemble averaging of water vapor mixing ratio data from 10 nighttime comparisons with Vaisala RS92 radiosondes shows, on average, an agreement within ±10%, up to ∼8 km. A similar analysis of lidar-to-lidar data of over 700 profiles revealed an agreement to within 20% over the first 7 km (10% below 4 km). A grid analysis, defined in the temperature–relative humidity space, was developed to characterize the lidar–radiosonde agreement and quantitatively localizes regions of strong and weak correlations as a function of altitude, temperature, or relative humidity. Three main regions of weak correlation emerge: (i) regions of low relative humidity and low temperature, (ii) regions of moderate relative humidity at low temperatures, and (iii) regions of low relative humidity at moderate temperatures. Comparison of Atmospheric Infrared Sounder and Tropospheric Emission Sounder satellite retrievals of moisture with those of Howard University Raman lidar showed a general agreement in the trend, but the satellites miss details in atmospheric structure because of their low resolution. A relative difference of about ±20% is usually found between lidar and satellite measurements for the coincidences available.

The temperature dependence of molecular backscatter coefficients must be taken into account when narrowband interference filters are used in lidar measurements. Thus, the spectral backscatter differential cross section of the molecules involved in the backscattering of the radiation has to be calculated or measured and the interference filter transmission efficiency must be known. The present paper is intended to describe in an easily reproducible manner the procedure involved in calculating the temperature-dependent functions introduced in the lidar equations, including the computation of the differential cross sections for air, nitrogen, and water vapor. The temperature-dependent functions are computed for the Howard University Raman lidar (HURL). The interference filter efficiencies are given by the manufacturer. Error estimates in water vapor mixing ratio and aerosol backscatter ratio involved when temperature-dependent functions are omitted are given for measurements taken with HURL. For the data analyzed, it is found that errors in estimating the water vapor mixing ratio are up to ∼6% while in estimating the aerosol backscattering ratio the errors are up to ∼1.3% in the planetary boundary layer and ∼2.2% in cirrus clouds. Theoretical computations are performed to determine temperature-dependent functions for nitrogen, water vapor, and their ratio, using simulated Gaussian-shaped filters. The goal is to find the optimum combination of different filters that will determine the ratio profiles of the temperature-dependent functions that are either the closest to unity or the least variable. The analyses reveal that quite constant profiles can be obtained for several combinations of the filters.

The eruption of Eyjafjallajokull in 2010 has triggered the rapid development of volcanic ash remote sensing activities at the Met Office. Volcanic ash qualitative and quantitative mapping have been achieved using lidar on board the Facility for Airborne Atmospheric Measurements (FAAM) research aircraft, and using improved satellite retrieval algorithms. After the eruption, a new aircraft facility, the Met Office Civil Contingencies Aircraft (MOCCA), has been set up to enable a rapid response, and a network of ground-based remote sensing sites with lidars and sunphotometers is currently being developed. Thanks to these efforts, the United Kingdom (UK) will be much better equipped to deal with such a crisis, should it happen in the future.

In this paper we calculate the Signal-to-Noise ( SNR ) ratio of a 3-channel commercial (Raymetics) volcanic ash detection system, (LR111-D300), already operating under Met Office organization. The methodology for the accurate estimation is presented for day and nighttime conditions. The results show that SNR values are higher than 10 for ranges up to 13 km for both nighttime and daytime conditions. This is a quite good result compared with other values presented in bibliography and proves that such system is able to detect volcanic ash over a range of 20 km.

The present research envisages the estimation of the overlap correction function for an airborne nadir-mounted lidar using multi-angle measurements. We have scanned a series of offnadir angles and after data processing we have been able to determine the instrument’s overlap function down to 95m from the lidar. This function can be used for the correction of lidar profiles and hence reduce the near-range uncertainty of lidar measurements. To our knowledge, the estimation of the overlap function using multi-angle method for a nadir pointing lidar is a premiere.

An improved measurement methodology and a data-processing technique for multiangle data obtained with an elastic scanning lidar in clear atmospheres are introduced. Azimuthal and slope scans are combined to reduce the atmospheric heterogeneity. Vertical profiles of optical depth and intercept (proportional to the logarithm of the backscatter coefficient) are determined. The purpose of this approach is to identify and remove data points that distort the regression analysis results in order to improve the accuracy of the retrieved optical depth and of the intercept. In addition, the influence of systematic distortions has been investigated. Furthermore, profiles of the optical depth, intercept, and the range-squared-corrected signals have been used to determine the lidar overlap function as a function of range. Simulation and experimental results of this data-processing technique are presented.

Highly time-resolved measurements of PM2.5, its major constituents, particle size distributions (9 nm to 20 μ m), CO, NO/NO2, and O3, and meteorological parameters were made from February through November 2002, at the Baltimore Supersite at Ponca St. using commercial and prototype semi-continuous instruments. The average PM2.5 mass concentration during the study period was 16.9 μ g/m3 and a total of 29 PM2.5 pollution episodes, each in which 24-h averaged PM2.5 mass concentrations exceeded 30.0 μ g/m3 for one or more days, were observed. Herein, 6 of the worst episodes are discussed. During these events, PM2.5 excursions were often largely due to elevations in the concentration of one or two of the major species. In addition, numerous short-term excursions were observed and were generally attributable to local sources. Those in OC, EC, nitrate, CO, and NOx levels were often observed in the morning traffic hours, particularly before breakdown of nocturnal inversions. Moreover, fresh accumulation aerosols f...

The Met Office completed the deployment of ten lidars (UV Raman and depolarization), each accompanied by a sunphotometer (polarized model), to provide quantitative monitoring of volcanic ash over UK for VAAC London. The lidars provide range corrected signal and volume depolarization ratio in near-real time. The sunphotometers deliver aerosol optical depth, Ångstrom exponent and degree of linear polarization. Case study analyses of Saharan dust events (as a proxy for volcanic ash) are presented.

The eruption of the Icelandic volcano Eyjafjallajökull in April–May 2010 represents a "natural experiment" to study the impact of volcanic emissions on a continental scale. For the first time, quantitative data about the presence, altitude, and layering of the volcanic cloud, in conjunction with optical information, are available for most parts of Europe derived from the observations by the European Aerosol Research Lidar NETwork (EARLINET). Based on multi-wavelength Raman lidar systems, EARLINET is the only instrument worldwide that is able to provide dense time series of high-quality optical data to be used for aerosol typing and for the retrieval of particle microphysical properties as a function of altitude. In this work we show the four-dimensional (4-D) distribution of the Eyjafjallajökull volcanic cloud in the troposphere over Europe as observed by EARLINET during the entire volcanic event (15 April–26 May 2010). All optical properties directly measured (backscatter, extinction, and particle linear depolarization ratio) are stored in the EARLINET database available at http://www.earlinet.org. A specific relational database providing the volcanic mask over Europe, realized ad hoc for this specific event, has been developed and is available on request at http://www.earlinet.org. During the first days after the eruption, volcanic particles were detected over Central Europe within a wide range of altitudes, from the upper troposphere down to the local planetary boundary layer (PBL). After 19 April 2010, volcanic particles were detected over southern and south-eastern Europe. During the first half of May (5–15 May), material emitted by the Eyjafjallajökull volcano was detected over Spain and Portugal and then over the Mediterranean and the Balkans. The last observations of the event were recorded until 25 May in Central Europe and in the Eastern Mediterranean area. The 4-D distribution of volcanic aerosol layering and optical properties on European scale reported here provides an unprecedented data set for evaluating satellite data and aerosol dispersion models for this kind of volcanic events., The financial support for EARLINET by the European Union under grant RICA 025991 in the Sixth Framework Programme is gratefully acknowledged. Since 2011 EARLINET has been integrated in the ACTRIS Research Infrastructure Project supported by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 262254. The authors acknowledge the ESA financial support under the ESRIN contract 21769/08/I-OL and 22202/09/I-EC. Additional financial support has been received from the Andalusia Regional Government through project P10-RNM-6299 and from the Spanish Ministry of Science and Technology through projects CGL2010-18782, and CSD2007-00067.

Gibberella circinata (anamorphic stage Fusarium circinatum) is the causal agent of pine pitch canker. The disease almost exclusively affects Pinus species, but was also described to occur on Douglas-fir (Pseudotsuga menziesii). This disease is a serious threat to the pine forests, due to extensive tree mortality, reduced growth and timber quality. Multiple branch infection may cause severe crown dieback and eventually lead to the death of the tree. This aggressive fungus may also cryptically infect the Pinus seeds and may cause damping-off in seedlings. The fungus is officially reported in the USA, Mexico, Haiti, South Africa, Japan, Chile (Anonymous 2005) and it has recently been reported in the EPPO region. In Spain and France G. circinata is under eradication and in Italy the pest organism has been eradicated. The pathogen is subject to EC emergency measures and there are requirements for MS to conduct surveys. In nurseries there had been findings in Spain, Portugal and France; it has been found in forests, parks and gardens in Spain. The first aim of this project is to ring test available and widely used detection methods and to provide validation and performance data for each of them. The validation data provided by this project will be useful to help the reference laboratories and mandated diagnostic laboratories to choose and implement efficient pine seed testing regarding this pathogen. The second aim is to provide an agreement about the sample sizes of pine seeds for testing. All the pine seed samples used for this project will be artificially contaminated with known quantities of the target pathogen. Preliminary tests should ensure the homogeneity of the different samples produced for the different levels of infestations and the different sample sizes. Preliminary investigation will be needed to explore the ISPM N°31 standard (International Plant Protection Convention 2008), and to determine which range of sample size should be assessed during this collaborative research project., Scientific report of the Euphresco funded project 'Ring testing of diagnostic protocols for identification and detection of Gibberella circinata in pine seed'

This study compares the aerosol backscatter and extinction coefficients retrieved from vertical elastic and Raman channels with those derived from measurements with multiangle elastic channels. Retrievals from simulated vertical signals at 355 nm, 387 nm, 532 nm, and 607 nm are compared with those from multiangle measurements (at 15 elevation angles) at 355 nm and 532 nm. The atmosphere is considered horizontally homogeneously stratified. For the backscatter coefficient, the Raman backscatter solution and the multiangle solution are considered. For the extinction coefficient, retrievals from the Raman channel and multiangle measurements are compared. The comparison shows that in the presence of horizontal homogeneity, multiangle measurements provide more reliable results, especially for the aerosol extinction coefficient. The uncertainty in the measured signals is considered in an alternative approach to quantify the relative error of the retrieved profiles with respect to the models (linear regression between retrieval and model).

This study focuses on the aerosol hygroscopic properties as determined from ground-based measurements and Mie theory. Usually, aerosol ground-based measurements are taken in dry conditions to ensure data consistency within networks. The dependence of the various aerosol optical characteristics (e.g. aerosol absorption, scattering, backscattering or extinction coefficients) on relative humidity has therefore to be established in order to determine their values in the atmosphere, where relative humidity can reach high values. We calculated mean monthly diurnal values of the aerosol hygroscopic growth factor at 90% relative humidity GF(90) based on measurements performed at EMEP-GAW station of Ispra with a Hygroscopicity Tandem Differential Mobility Analyzer over eight months in 2008 and 2009. Particle hygroscopicity increases with particle dry diameter ranging from 35 to 165 nm for all seasons. We observed a clear seasonal variation in GF(90) for particles larger than 75 nm, and a diurnal cycle in spring and winter for all sizes. For 165 nm particles, GF(90) averages 1.32 ± 0.06. The effect of the particle hygroscopic growth on the aerosol optical properties (scattering, extinction, absorption and backscatter coefficients, asymmetry parameter and backscatter faction) was computed using the Mie theory, based on data obtained from a series of instruments running at our station. We found median enhancement factors (defined as ratios between the values of optical variables at 90% and 0% relative humidity) equal to 1.1, 2.1, 1.7, and 1.8, for the aerosol absorption, scattering, backscattering, and extinction coefficients, respectively. All except the absorption enhancement factor show a strong correlation with the hygroscopic growth factor. The enhancement factors observed at our site are among the lowest observed across the world for the aerosol scattering coefficient, and among the highest for the aerosol backscatter fraction.

This study focuses on the aerosol hygroscopic properties as determined from ground-based measurements and Mie’s theory. Usually, aerosol ground-based measurements are taken in dry conditions in order to have a consistency within networks. The dependence of the various aerosol optical characteristics (e.g. aerosol absorption, scattering, backscattering or extinction coefficients) on relative humidity has therefore to be established in order to determine their values in the atmosphere, where relative humidity (RH) can reach high values. We calculated mean monthly diurnal values of the aerosol hygroscopic growth factor at 90% GF(90) based on measurements performed at EMEP-GAW station of Ispra with a Hygroscopicity Tandem Differential Mobility Analyzer over eight months in 2008 and 2009. Particle hygroscopicity increases with particle dry diameter ranging from 35 to 165 nm for all season. We observed a clear seasonal variation in GF(90) for particles larger than 75 nm, and a diurnal cycle in spring and winter for all sizes. For 165 nm particles, GF(90) averages 1.32 ± 0.06. The effect of the particle hygroscopic growth on the aerosol optical properties (scattering, extinction, absorption and backscatter coefficients, asymmetry parameter and backscatter faction) was computed using the Mie theory, based on data obtained from a series of instruments run at our station. We found median enhancement factors (defined as ratios between the values of optical variables at 90 and 0% RH) equal to 1.1, 2.1, 1.7, and 1.8, for the aerosol absorption, scattering, backscattering, and extinction coefficients, respectively. All except the absorption enhancement factors show a strong correlation with the hygroscopic growth factor. The enhancement factors observed at our site are among the lowest observed across the world for the aerosol scattering coefficient, and among the highest for the aerosol backscatter fraction., JRC.H.2-Air and Climate

Classical and quantum formulations are used to estimate Rayleigh scattering within lidar signals. Within the classical approach, three scenarios are used to characterize atmospheric molecular composition: 2-component atmosphere (N2 and O2), 4-component atmosphere (N2, O2, Ar, and CO2), and 5-component atmosphere (N2, O2, Ar, CO2, and water vapor). First, analysis focuses on Rayleigh scattering, showing the relative difference between the three scenarios within classical approach. The relative difference in molecular scattering between 2(4)-component atmosphere and 5-component atmosphere is below ~1%. The second analysis focuses on the lidar retrieval of aerosol backscatter and extinction coefficients showing the effect of different molecular formulations. A relative difference of ±3% was found between the molecular formulation of 2-component atmosphere and the molecular formulation of 5-component atmosphere. Consideration of the Raman rotational lines blocked by the interference filter is important for the elastic channels, but of little significance in the N2 Raman channel. For lidar retrieval of aerosol profiles, the 5-component approximation is the best when the water vapor profile is known, but 2-component is still adequate and quite accurate when water vapor is only poorly known., JRC.H.2-Air and Climate

At the Howard University Atmospheric Observatory in Beltsville, MD, a Raman Lidar system was developed to provide both daytime and nighttime measurements of water vapor, aerosols, and cirrus clouds with 1 min temporal and 7.5 m spatial resolution in the lower troposphere. Signals at three wavelengths associated with Rayleigh/Mie scattering for aerosols and cirrus clouds at 354.7 nm, Raman scattering for nitrogen at 386.7 nm, and water vapor at 407.5 nm are analyzed. The transmitter is a triple harmonic Nd: YAG solid state laser. The receiver is a 40 cm Cassegrain telescope. Our detector system consists of a multi‐channel wavelength separator unit and data acquisition system. We are developing a numerical model to provide a realistic representation of the system behavior. The variants of the lidar equation in the model use system parameters and are solved to determine the return signals for our lidar system. In this paper, we report on two of the five case studies being investigated: clear sky and cirrus cloud covered molecular atmosphere. The first simulations are based on a standard atmosphere, which assumes an unpolluted (aerosol‐free) dry air atmosphere. The second set of simulations is based on a cloudy atmosphere, where cirrus clouds are added to the conditions in case study I. Lidar signals are simulated over the altitude range covered by our measurements (up to 14 km). Results will show comparisons between the simulated and actual measurements when varying lidar and atmospheric optical parameters in the model.

[1] Comparisons of Tropospheric Emission Spectrometer (TES) water vapor retrievals with in situ measurements are presented. Global comparisons of TES water vapor retrievals with nighttime National Centers for Environmental Prediction RS90/RS92 radiosondes show a small (

During the eruption of Eyjafjallajokull in 2010, the Met Office ceilometers (Laser Cloud Based Recorders - LCBR) provided reasonable information about volcanic ash plumes over the United Kingdom [1]. This capability triggered the development of an operational system to provide quick looks of the range corrected signals (RCS ) in near-real-time (NRT). Moreover, the Met Office acquired eleven Jenoptik ceilometers to supplement the operational ceilometer network. The combined network became operational in 2012 and currently comprises a total of 43 ceilometers reporting backscatter profiles in NRT. In 2013, Civil Aviation Authority (CAA) and the Department for transport (DfT) sponsored the acquisition of 9 fixed lidars and one mobile unit (each accompanied by a sunphotometer), to further improve the quantitative monitoring of volcanic ash. The current status of both ceilometer and lidar/sun-photometer networks is discussed and further developments are proposed.

The purpose of this study is to estimate the errors due to several systematic distortions which occur in the procedure of computing water vapor mixing ratio (WVMR) and aerosol scattering ratio (ASR). For WVMR, the systematic distortions are encountered during the following processes: gluing, omission of temperature dependent molecular backscatter coefficient (temperature dependent lidar equation), incomplete overlap correction, and calibration while for ASR during the gluing and omission of temperature dependent molecular backscatter coefficient. The data analyzed are taken with Howard University Raman Lidar (HURL) during WAVES 2006 field campaign. The HURL system operates at the third harmonic of a Nd:YAG laser and acquires data within three channels (354.7 nm, 386.7 nm and 407.5 nm). The study shows the relative errors in computing WVMR and ASR when considering different combinations of the systematic distortions (15 cases for WVMR and 3 cases for ASR) with respect to the case as considered true. The analyses were performed over a time series of WVMR and ASR of about 6 hours and over the altitude range up to 5 km. The range of the relative errors is between ~ 1 % and ~ 18 % for WVMR and between ~ 1 % and ~ 8 % for ASR.

An experimental method for determining the presence and the level of systematic distortions in lidar data is considered. The method has been developed on the basis of two years of field experiments with the Fire Sciences Laboratory elastic scanning lidar. The influence of multiplicative and additive distortion components is considered using numerical experiments and is illustrated with experimental data. The examination method is most applicable for short wavelengths at which the atmospheric molecular component in clear atmospheres is large enough to stabilize the Kano-Hamilton multiangle solution, based on the assumption of horizontal atmospheric homogeneity.

Layers of aerosol at heights between 2 and 11 km were observed with Raman lidars in the UK between 23 and 31 May 2016. A network of such lidars, supported by ceilometer observations, is used to map the extent of the aerosol and its optical properties. Spaceborne lidar profiles show that the aerosol originated from forest fires over Western Canada around 17 May, and indeed the aerosol properties – weak depolarisation and a lidar ratio at 355 nm in the range 35–65 sr – were consistent with long-range transport of forest fire smoke. The event was unusual in its persistence – the smoke plume was drawn into an atmospheric block that kept it above North-west Europe for nine days. Lidar observations show how the smoke layers became optically thinner during this period, but the lidar ratio and aerosol depolarisation showed little change.

[1] High spatial and temporal resolution elastic backscatter lidar data from Baltimore are analyzed with a near-end approach to estimate vertical profiles of the aerosol extinction coefficient. The near-end approach makes use of the (1) aerosol scattering coefficient measured at the surface with a nephelometer (0.530 μm), (2) surface level particle size distribution, and (3) refractive index calculated using Mie theory to estimate the aerosol extinction coefficient boundary condition for the lidar equation. There was a broad range of atmospheric turbidity due to a strong haze event, which occurred because of smoke transport from Canadian forest fires, and led to a wide range of observed atmospheric properties. The index of refraction for aerosols estimated during the entire study period is 1.5–0.47 i, which is typical for soot. The measured surface level aerosol scattering coefficient ranged from σp = 0.002 to σp = 0.541 km−1, and the computed aerosol extinction coefficient spanned values κp = 0.01 to κp = 1.05 km−1. The derived mass concentration and the mass scattering ranges were 3.96–194 μg m−3 and 0.05–3.260 m2g−1, respectively. The aerosol optical properties were dominated by light absorption by soot.