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The CALIPSO Level 3 (CL3) product, available since December 2011, is the most recent data set produced by the observations of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument onboard the Cloud-Aerosol Lidar and Pathfinder Satellite Observations (CALIPSO) space platform. The European Aerosol Research Lidar Network (EARLINET), based mainly on multi-wavelength Raman lidar systems, is the most appropriate ground-based reference for CALIPSO calibration/validation studies on a continental scale. In this work, CALIPSO data are compared against EARLINET monthly averaged profiles obtained by measurements performed during CALIPSO overpasess. In order to mitigate uncertainties due to spatial and temporal differences, we reproduce a modified version of CL3 data starting from CALIPSO Level 2 (CL2) data. The spatial resolution is finer and nearly 2° × 2° (latitude × longitude) and only simultaneous measurements are used for ease of comparison. The CALIPSO monthly mean profiles following this approach are called CALIPSO Level 3*, CL3*. We find good agreement on the aerosol extinction coeffcient, yet in most of the cases a small CALIPSO underestimation is observed with an average bias of 0.02km-1 up to 4 km and 0.003km-1 higher above. In contrast to CL3 standard product, CL3* data set offers the possibility to assess the CALIPSO performance also in terms of the particle backscatter coeffcient keeping the same quality assurance criteria applied to extinction profiles. The mean relative difference in the comparison improved from 26.1% for extinction to 13.7% for backscatter, showing better performances of CALIPSO backscatter retrievals. Additionally, the aerosol typing comparison yielded a robust identification of Dust and Polluted Dust. Moreover, the CALIPSO aerosol-type-dependent lidar ratio selection is assessed by means of EARLINET observations, so as to investigate the performance of the extinction retrievals. The aerosol types of Dust, Polluted Dust, and Clean Continental showed noticeable discrepancy. Finally, the potential improvements of the lidar ratio assignment have been examined by adjusting it according to EARLINET derived values. [ABSTRACT FROM AUTHOR]

In this work we present an analysis of mineral dust optical and microphysical properties obtained from different retrieval techniques applied to active and passive remote sensing measurements, including a comparison with simultaneous in-situ aircraft measurements. Data were collected in a field campaign performed during a mineral dust outbreak a Granada, Spain, experimental site (37.16° N, 3.61°W, 680ma.s.l.) on the 27 June 2011. Column-integrated properties are provided by sun- and star-photometry which allows a continuous evaluation of the mineral dust optical properties during both day and night-time. Both the Linear Estimation and AERONET (Aerosol Robotic Network) inversion algorithms are applied for the retrieval of the column-integrated microphysical particle properties. In addition, vertically-resolved microphysical properties are obtained from a multi-wavelength Raman lidar system included in EARLINET (European Aerosol Research Lidar Network), by using both LIRIC (Lidar Radiometer Inversion Code) algorithm during daytime and an algorithm applied to the Raman measurements based on the regularization technique during night-time. LIRIC retrievals reveal several dust layers between 3 and 5 kma.s.l. with volume concentrations of the coarse spheroid mode up to 60 μm3 cm-3. The combined use of the regularization and LIRIC methods reveals the night-to-day evolution of the vertical structure of the mineral dust microphysical properties and offers complementary information to that from column-integrated variables retrieved from passive remote sensing. Additionally, lidar depolarization profiles and LIRIC retrieved volume concentration are compared with aircraft in-situ measurements. This study presents for the first time a comparison of both volume concentration and dust particle polarization ratios measured with in-situ and remote sensing techniques. Results for the depolarization measurements in the dust layer indicate reasonable agreement within the estimated uncertainties. The differences in the volume concentration profiles, although somewhat larger, are still within the expected uncertainties. [ABSTRACT FROM AUTHOR]

A new methodology based on combining active and passive remote sensing and simultaneous and collocated radiosounding data to study the aerosol hygroscopic growth effects on the particle optical and microphysical properties is presented. The identifica-tion of hygroscopic growth situations combines the analysis of multiespectral aerosol particle backscatter coefficient and particle linear depolarization ratio with thermodynamic profiling of the atmospheric column.We analysed the hygroscopic growth effects on aerosol properties, namely the aerosol particle backscatter coefficient and the volume concentration profiles, using data gathered at Granada EARLINET station. Two study cases, corresponding to different aerosol loads and different aerosol types, are used for illustrating the potential of this methodology. Values of the aerosol particle backscatter coefficient enhancement factors range from 2.10±0.06 to 3.90±0.03, being similar to those previously reported in the literature. Differences in the enhancement factor are directly linked to the composition of the atmospheric aerosol. The largest value of the aerosol particle backscatter coefficient enhancement factor corresponds to the presence of sulphate and marine particles that are more affected by hygroscopic growth. On the contrary, the lowest value of the enhancement factor corresponds to an aerosol mixture containing sulphates and slight traces of mineral dust. The Hänel parameterization is applied to these case studies, obtaining results within the range of values reported in previous studies, with values of the exponent of 0.56±0.01 (for anthropogenic particles slightly influenced by mineral dust) and 1.07±0.01 (for the situation dominated by anthropogenic particles), showing the convenience of this remote sensing approach for the study of hygroscopic effects of the atmospheric aerosol under ambient unperturbed conditions. For the first time, the retrieval of the volume con centration profiles for these cases using the Lidar Radiometer Inversion Code (LIRIC) allows us to analyse the aerosol hygroscopic growth effects on aerosol volume concentration, observing a stronger increase of the fine mode volume concentration with increasing relative humidity. [ABSTRACT FROM AUTHOR]

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 analysis and short-term forecasts of aerosols through a case study in the Mediterranean. To do so, we employ a data assimilation (DA) algorithm based on the optimal interpolation method developed in the chemistry transport model (CTM) POLAIR3D of the air quality modelling platform POLYPHEMUS. We assimilate hourly-averaged normalised range corrected lidar signals (PR²) retrieved from a 72 h period of intensive and continuous measurements performed in July 2012 by ground-based lidar systems of the European Aerosol Research Lidar Network (EARLINET) integrated into the Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS) 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 (PM2.5) and those with an aerodynamic diameter higher than 2.5 µm but lower than 10 µm (PM2.5-10) 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 (Lh) 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 1.5-3.5km a.g.l.) and the assimilation period length (12 h or 24 h). We find that DA with Lh = 100 km and assimilation from 1.0 to 3.5km a.g.l. during a 12 h assimilation period length leads to the best scores for PM10 and PM2.5 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 (Lh =100 km, the assimilation altitude range from 1.0 to 3.5km a.g.l. and 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 (PM10 or PM2.5) from the French air quality network (BDQA) and the EMEP-Spain/Portugal network. The results show that the simulation with DA leads to better scores than the one without DA for PM2.5, PM10 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. [ABSTRACT FROM AUTHOR]

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Copyright of Óptica Pura y Aplicada is the property of Sociedad Espanola de Optica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)