EARLINET Single Calculus Chain – overview on methodology and strategy

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

EARLINET: Towards an advanced sustainable European aerosol lidar network

The European Aerosol Research Lidar Network, EARLINET, was founded in 2000 as a research project for establishing a quantitative, comprehensive, and statistically significant database for the horizontal, vertical, and temporal distribution of aerosols on a continental scale. Since then EARLINET has continued to provide the most extensive collection of ground-based data for the aerosol vertical distribution over Europe. This paper gives an overview of the network's main developments since 2000 and introduces the dedicated EARLINET special issue, which reports on the present innovative and comprehensive technical solutions and scientific results related to the use of advanced lidar remote sensing techniques for the study of aerosol properties as developed within the network in the last 13 years. Since 2000, EARLINET has developed greatly in terms of number of stations and spatial distribution: from 17 stations in 10 countries in 2000 to 27 stations in 16 countries in 2013. EARLINET has developed greatly also in terms of technological advances with the spread of advanced multiwavelength Raman lidar stations in Europe. The developments for the quality assurance strategy, the optimization of instruments and data processing, and the dissemination of data have contributed to a significant improvement of the network towards a more sustainable observing system, with an increase in the observing capability and a reduction of operational costs. Consequently, EARLINET data have already been extensively used for many climatological studies, long-range transport events, Saharan dust outbreaks, plumes from volcanic eruptions, and for model evaluation and satellite data validation and integration. Future plans are aimed at continuous measurements and near-real-time data delivery in close cooperation with other ground-based networks, such as in the ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) www.actris.net, and with the modeling and satellite community, linking the research community with the operational world, with the aim of establishing of the atmospheric part of the European component of the integrated global observing system

Four-dimensional distribution of the 2010 Eyjafjallajökull volcanic cloud over Europe observed by EARLINET

© Author(s) 2013. This work is distributed under the Creative Commons Attribution 3.0 License.The eruption of the Icelandic volcano Eyjafjallaj ökull 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 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 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.Peer reviewe

\u201cGive, but Give until It Hurts\u201d: The Modulatory Role of Trait Emotional Intelligence on the Motivation to Help

Two studies investigated the effect of trait Emotional Intelligence (trait EI) on people\u2019s moti- vation to help. In Study 1, we developed a new computer-based paradigm that tested partic- ipants\u2019 motivation to help by measuring their performance on a task in which they could gain a hypothetical amount of money to help children in need. Crucially, we manipulated partici- pants\u2019 perceived efficacy by informing them that they had been either able to save the chil- dren (positive feedback) or unable to save the children (negative feedback). We measured trait EI using the Trait Emotional Intelligence Questionnaire\u2013Short Form (TEIQue-SF) and assessed participants\u2019 affective reactions during the experiment using the PANAS-X. Results showed that high and low trait EI participants performed differently after the presen- tation of feedback on their ineffectiveness in helping others in need. Both groups showed increasing negative affective states during the experiment when the feedback was negative; however, high trait EI participants better managed their affective reactions, modulating the impact of their emotions on performance and maintaining a high level of motivation to help. In Study 2, we used a similar computerized task and tested a control situation to explore the effect of trait EI on participants\u2019 behavior when facing failure or success in a scenario unre- lated to helping others in need. No effect of feedback emerged on participants\u2019 emotional states in the second study. Taken together our results show that trait EI influences the impact of success and failure on behavior only in affect-rich situation like those in which people are asked to help others in need

EARLINET observations of the 14-22-May long-range dust transport event during SAMUM 2006: Validation of results from dust transport modelling

We observed a long-range transport event of mineral dust from North Africa to South Europe during the Saharan Mineral Dust Experiment (SAMUM) 2006. Geometrical and optical properties of that dust plume were determined with Sun photometer of the Aerosol Robotic Network (AERONET) and Raman lidar near the North African source region, and with Sun photometers of AERONET and lidars of the European Aerosol Research Lidar Network (EARLINET) in the far field in Europe. Extinction-to-backscatter ratios of the dust plume over Morocco and Southern Europe do not differ. Ångstr¨om exponents increase with distance from Morocco. We simulated the transport, and geometrical and optical properties of the dust plume with a dust transport model. The model results and the experimental data show similar times regarding the appearance of the dust plume over each EARLINET site. Dust optical depth from the model agrees in most cases to particle optical depth measured with the Sun photometers. The vertical distribution of the mineral dust could be satisfactorily reproduced, if we use as benchmark the extinction profiles measured with lidar. In some cases we find differences. We assume that insufficient vertical resolution of the dust plume in the model calculations is one reason for these deviations

Experimental techniques for the calibration of lidar depolarization channels in EARLINET

Particle depolarization ratio retrieved from lidar measurements are commonly used for aerosol-typing studies, microphysical inversion, or mass concentration retrievals. The particle depolarization ratio is one of the primary parameters that can differentiate several major aerosol components but only if the measurements are accurate enough. The accuracy related to the retrieval of particle depolarization ratios is the driving factor for assessing and improving the uncertainties of the depolarization products. This paper presents different depolarization calibration procedures used to improve the quality of the depolarization data. The results illustrate a significant improvement of the depolarization lidar products for all the selected lidar stations that have implemented depolarization calibration procedures. The calibrated volume and particle depolarization profiles at 532 nm show values that fall within a range that is generally accepted in the literature