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

Nabro volcano (13.37 • N, 41.70 • E) in Eritrea erupted on 13 June 2011 generating a layer of sulfate aerosols that persisted in the stratosphere for months. For the first time we report on ground-based lidar observations of the same event from every continent in the Northern Hemisphere, taking advantage of the synergy between global lidar networks such as EARLINET, MPLNET and NDACC with independent lidar groups and satellite CALIPSO to track the evolution of the stratospheric aerosol layer in various parts of the globe. The globally averaged aerosol optical depth (AOD) due to the stratospheric volcanic aerosol layers was of the order of 0.018±0.009 at 532 nm, ranging from 0.003 to 0.04. Compared to the total column AOD from the available collocated AERONET stations, the stratospheric contribution varied from 2% to 23% at 532 nm.

Abstract. 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 the analysis and short-term forecasts of aerosols through a case study in the Mediterranean basin. To do so, we employ a data assimilation (DA) algorithm based on the optimal interpolation method developed in the POLAIR3D chemistry transport model (CTM) of the POLYPHEMUS air quality modelling platform. We assimilate hourly averaged normalised range-corrected lidar signals (PR 2 ) retrieved from a 72 h period of intensive and continuous measurements gases Research InfraStructure (ACTRIS) network 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 (PM 2.5 ) and those with an aerodynamic diameter higher than 2.5 µm but lower than 10 µm (PM 10−2.5 ) 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 (L h ) 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 L h = 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 PM 10 and PM 2.5 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 (L h = 100 km, an assimilation altitude range from 1.0 to 3.5 km a.g.l. and a 12 h DA period) are evaluated using the level 2.0 (cloud-screened and quality-assured) aerosol optical depth (AOD) data from AERONET, and mass concentration measurements (PM 10 or PM 2.5 ) from the French air quality (BDQA) network and the EMEP-Spain/Portugal network. The results show that the simulation with DA leads to better scores than the one without DA for PM 2.5 , PM 10 and AOD. Additionally, the comparison of model results to evaluation data indicates that the temporal impact of assimilating lidar signals is longer than 36 h after the assimilation period.