2017, Tsekeri, Alexandra, Lopatin, Anton, Amiridis, Vassilis, Marinou, Eleni, Igloffstein, Julia, Siomos, Nikolaos, Solomos, Stavros, Kokkalis, Panagiotis, Engelmann, Ronny, Baars, Holger, Gratsea, Myrto, Raptis, Panagiotis I., Binietoglou, Ioannis, Mihalopoulos, Nikolaos, Kalivitis, Nikolaos, Kouvarakis, Giorgos, Bartsotas, Nikolaos, Kallos, George, Basart, Sara, Schuettemeyer, Dirk, Wandinger, Ulla, Ansmann, Albert, Chaikovsky, Anatoli P., Dubovik, Oleg

The Generalized Aerosol Retrieval from Radiometer and Lidar Combined data algorithm (GARRLiC) and the LIdar-Radiometer Inversion Code (LIRIC) provide the opportunity to study the aerosol vertical distribution by combining ground-based lidar and sun-photometric measurements. Here, we utilize the capabilities of both algorithms for the characterization of Saharan dust and marine particles, along with their mixtures, in the south-eastern Mediterranean during the CHARacterization of Aerosol mixtures of Dust and Marine origin Experiment (CHARADMExp). Three case studies are presented, focusing on dust-dominated, marinedominated and dust-marine mixing conditions. GARRLiC and LIRIC achieve a satisfactory characterization for the dust-dominated case in terms of particle microphysical properties and concentration profiles. The marine-dominated and the mixture cases are more challenging for both algorithms, although GARRLiC manages to provide more detailed microphysical retrievals compared to AERONET, while LIRIC effectively discriminates dust and marine particles in its concentration profile retrievals. The results are also compared with modelled dust and marine concentration profiles and surface in situ measurements.

2017, Baars, Holger, Seifert, Patric, Engelmann, Ronny, Wandinger, Ulla

Absolute calibrated signals at 532 and 1064 nm and the depolarization ratio from a multiwavelength lidar are used to categorize primary aerosol but also clouds in high temporal and spatial resolution. Automatically derived particle backscatter coefficient profiles in low temporal resolution (30 min) are applied to calibrate the lidar signals. From these calibrated lidar signals, new atmospheric parameters in temporally high resolution (quasi-particle-backscatter coefficients) are derived. By using thresholds obtained from multiyear, multisite EARLINET (European Aerosol Research Lidar Network) measurements, four aerosol classes (small; large, spherical; large, non-spherical; mixed, partly nonspherical) and several cloud classes (liquid, ice) are defined. Thus, particles are classified by their physical features (shape and size) instead of by source. The methodology is applied to 2 months of continuous observations (24 h a day, 7 days a week) with the multiwavelength-Raman-polarization lidar PollyXT during the High-Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) in spring 2013. Cloudnet equipment was operated continuously directly next to the lidar and is used for comparison. By discussing three 24 h case studies, it is shown that the aerosol discrimination is very feasible and informative and gives a good complement to the Cloudnet target categorization. Performing the categorization for the 2-month data set of the entire HOPE campaign, almost 1 million pixel (5 min×30 m) could be analysed with the newly developed tool. We find that the majority of the aerosol trapped in the planetary boundary layer (PBL) was composed of small particles as expected for a heavily populated and industrialized area. Large, spherical aerosol was observed mostly at the top of the PBL and close to the identified cloud bases, indicating the importance of hygroscopic growth of the particles at high relative humidity. Interestingly, it is found that on several days non-spherical particles were dispersed from the ground into the atmosphere.

2017, Filioglou, Maria, Nikandrova, Anna, Niemelä, Sami, Baars, Holger, Mielonen, Tero, Leskinen, Ari, Brus, David, Romakkaniemi, Sami, Giannakaki, Elina, Komppula, Mika

We present tropospheric water vapor profiles measured with a Raman lidar during three field campaigns held in Finland. Co-located radio soundings are available throughout the period for the calibration of the lidar signals. We investigate the possibility of calibrating the lidar water vapor profiles in the absence of co-existing on-site soundings using water vapor profiles from the combined Advanced InfraRed Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU) satellite product; the Aire Limitée Adaptation dynamique Développement INternational and High Resolution Limited Area Model (ALADIN/HIRLAM) numerical weather prediction (NWP) system, and the nearest radio sounding station located 100 km away from the lidar site (only for the permanent location of the lidar). The uncertainties of the calibration factor derived from the soundings, the satellite and the model data are < 2.8, 7.4 and 3.9 %, respectively. We also include water vapor mixing ratio intercomparisons between the radio soundings and the various instruments/model for the period of the campaigns. A good agreement is observed for all comparisons with relative errors that do not exceed 50 % up to 8 km altitude in most cases. A 4-year seasonal analysis of vertical water vapor is also presented for the Kuopio site in Finland. During winter months, the air in Kuopio is dry (1.15±0.40 †kg-1); during summer it is wet (5.54±1.02 †kg-1); and at other times, the air is in an intermediate state. These are averaged values over the lowest 2 km in the atmosphere. Above that height a quick decrease in water vapor mixing ratios is observed, except during summer months where favorable atmospheric conditions enable higher mixing ratio values at higher altitudes. Lastly, the seasonal change in disagreement between the lidar and the model has been studied. The analysis showed that, on average, the model underestimates water vapor mixing ratios at high altitudes during spring and summer.