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Since 2018, the Aeolus satellite of the European Space Agency (ESA) has acquired wind HLOS (horizontal line-of-sight) profiles throughout the troposphere and up to the lower stratosphere, filling a critical gap in the Global Observing System (GOS). Aeolus, carrying ALADIN (Atmospheric LAser Doppler INstrument), the first UV HSRL (High Spectral Resolution Lidar) Doppler lidar ever placed in space, provides also vertically resolved optical properties of particulates (aerosols and clouds). The present study focuses on the assessment of Aeolus L2A particulate backscatter coefficient (baseline 2A11), retrieved by the Standard Correct Algorithm (SCA), in the eastern Mediterranean, a region hosting a variety of aerosol species. Ground-based retrievals acquired by lidar instruments operating in Athens (central Greece), Thessaloniki (northern Greece) and Antikythera (southwestern Greece) serve as reference. All lidar stations provide routine measurements to the PANACEA (PANhellenic infrastructure for Atmospheric Composition and climatE chAnge) network. A set of ancillary data, including sun-photometric observations (AERONET), reanalysis products (CAMS and MERRA-2), satellite observations (MSG-SEVIRI and MODIS Aqua) and backward-trajectories modelling (FLEXPART), is utilized towards an optimum characterization of the probed atmospheric conditions under the absence of a classification scheme in Aeolus SCA profiles. First, emphasis is given on the assessment of Aeolus SCA backscatter coefficient under specific aerosol scenarios over Antikythera island. Due to the misdetection of the cross-polar component of the backscattered lidar signal, Aeolus underestimates the aerosol backscatter coefficient by up to 33 % when non-spherical mineral particles are recorded (10 July 2019). A good performance is revealed on 3 July 2019, when horizontally homogeneous loads of fine spherical particles are confined below 4 km. For other two cases (8 July 2020 and 5 August 2020), due to noise issues, the SCA performance degrades in terms of depicting the stratification of aerosol layers composed of particles of different origin. According to the statistical assessment analysis of 43 identified cases, a poor-to-moderate performance is revealed for the unfiltered (aerosols plus clouds) SCA profiles, which improves substantially when cloud-contaminated profiles are excluded from the collocated sample. This improvement is evident at both Aeolus vertical scales (regular scales have 24 bins and mid-bin scales have 23 bins), and it is justified by the drastic reduction in the bias (from 0.45 to 0.27 Mm−1 sr−1 for SCA and from 0.69 to 0.37 Mm−1 sr−1 for SCA mid-bin) and root mean square error (from 2.00 to 1.65 Mm−1 sr−1 for SCA and from 1.88 to 1.00 Mm−1 sr−1 for SCA mid-bin) scores. In the vertical, the SCA performance degrades at the lowermost bins due to either the contamination from surface signals or the increased noise levels for the aerosol retrievals. Among the three PANACEA stations, the best agreement is found at the remote site of Antikythera with respect to the urban sites of Athens and Thessaloniki. Finally, all key Cal/Val (calibration and validation) aspects necessary for future relevant studies, the recommendations for a possible Aeolus follow-on mission and an overview of the ongoing related activities are thoroughly discussed.

In this study we focus on the retrieval of aerosol and trace gas vertical profiles from multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations for the first time over Thessaloniki, Greece. We use two independent inversion algorithms for the profile retrievals: the Mexican MAX-DOAS Fit (MMF) and the Mainz Profile Algorithm (MAPA). The former is based on the optimal estimation method (OEM), while the latter follows a parameterization approach. We evaluate the performance of MMF and MAPA, and we validate their retrieved products with ancillary data measured by other co-located reference instruments. The trace gas differential slant column densities (dSCDs), simulated by the forward models, are in good agreement, except for HCHO, where larger scatter is observed due to the increased spectral noise of the measurements in the UV. We find an excellent agreement between the tropospheric column densities of NO2 retrieved by MMF and MAPA (slope=1.009, Pearson's correlation coefficient R=0.982) and a good correlation for the case of HCHO (R=0.927). For aerosols, we find better agreement for the aerosol optical depths (AODs) in the visible (i.e., at 477 nm) compared to the UV (at 360 nm), and we show that the agreement strongly depends on the O4 scaling factor that is used in the analysis. The agreement for NO2 and HCHO near-surface concentrations is similar to the comparison of the integrated columns with slightly decreased correlation coefficients. The seasonal mean vertical profiles that are retrieved by MMF and MAPA are intercompared, and the seasonal variation in all species along with possible sources is discussed. The AODs retrieved by the MAX-DOAS are validated by comparing them with AOD values measured by a CIMEL sun photometer and a Brewer spectrophotometer. Four different flagging schemes were applied to the data in order to evaluate their performance. Qualitatively, a generally good agreement is observed for both wavelengths, but we find a systematic bias from the CIMEL sun photometer and Brewer spectrophotometer measurements, due to the limited sensitivity of the MAX-DOAS in retrieving information at higher altitudes, especially in the UV. An in-depth validation of the aerosol vertical profiles retrieved by the MAX-DOAS is not possible since only in very few cases is the true aerosol profile known during the period of study. However, we examine four cases, where the MAX-DOAS provided a generally good estimation of the shape of the profiles retrieved by a co-located multi-wavelength lidar system. The NO2 near-surface concentrations are validated against in situ observations, and the comparison of both MMF and MAPA revealed good agreement with correlation coefficients of R=0.78 and R=0.73, respectively. Finally, the effect of the O4 scaling factor is investigated by intercomparing the integrated columns retrieved by the two algorithms and also by comparing the AODs derived by MAPA for different values of the scaling factor with AODs measured by the CIMEL sun photometer and the Brewer spectrophotometer.

Measurements of geometrical and optical properties of cirrus clouds, performed with a multi-wavelength Polly XT Raman lidar during the period 2008 to 2016, are analysed. The measurements were performed with the same instrument, during sequential periods, in three places at different latitudes, Gwal Pahari (28.43 ∘ N, 77.15 ∘ E; 243 m a.s.l.) in India, Elandsfontein (26.25 ∘ S, 29.43 ∘ E; 1745 m a.s.l.) in South Africa and Kuopio (62.74 ∘ N, 27.54 ∘ E; 190 m a.s.l.) in Finland. The lidar dataset was processed by an automatic cirrus cloud masking algorithm, developed in the frame of this work. In the following, we present a statistical analysis of the lidar-retrieved geometrical characteristics (cloud boundaries, geometrical thickness) and optical properties of cirrus clouds (cloud optical depth, lidar ratio, ice crystal depolarisation ratio) measured over the three areas that correspond to subtropical and subarctic regions as well as their seasonal variability. The effect of multiple scattering from ice particles to the derived optical products is also considered and corrected in this study. Our results show that cirrus layers, which have a noticeable monthly variability, were observed between 6.5 and 13 km, with temperatures ranging from −72 to −27 ∘ C. The observed differences on cirrus clouds' geometrical and optical properties over the three regions are discussed in terms of latitudinal and temperature dependence. The latitudinal dependence of the geometrical properties is consistent with satellite observations, following the pattern observed with CloudSat, with decreasing values towards the poles. The geometrical boundaries have their highest values in the subtropical regions, and overall, our results seem to demonstrate that subarctic cirrus clouds are colder, lower and optically thinner than subtropical cirrus clouds. The dependence of cirrus cloud geometrical thickness and optical properties on mid-cirrus temperatures shows a quite similar tendency for the three sites but less variability for the subarctic dataset. Cirrus clouds are geometrically and optically thicker at temperatures between −45 and −35 ∘ C, and a second peak is observed at lower temperatures ∼ - 70 ∘ C for the subarctic site. Lidar ratio values also exhibit a pattern, showing higher values moving toward the poles, with higher mean values observed over the subarctic site. The dependency of the mid-cirrus temperatures on the lidar ratio values and the particle depolarisation values is further examined. Our study shows that the highest values of the cirrus lidar ratio correspond to higher values of cirrus depolarisation and warmer cirrus. The kind of information presented here can be rather useful in the cirrus parameterisations required as input to radiative transfer models and can be a complementary tool for satellite products that cannot provide cloud vertical structure. In addition, ground-based statistics of the cirrus properties could be useful in the validation and improvement of the corresponding derived products from satellite retrievals.

This study aims to present and analyze the time series of the snow parameters focusing on representative geographical areas of the Eastern Mediterranean (i.e., Greece and Italy) and to examine their seasonal variability, in terms of region and geography. The satellite retrievals were firstly validated against in-situ retrievals for 67 common days, with a mean bias equal to −0.018 cm, with a near-Gaussian distribution, showing the good performance of the satellite snow detection. The satellite-based analysis resulted in increasing trends of snow water equivalent, attributed to the enhanced values between 2000 and 2009; however, decreasing trends are found starting from 2010 until now of −1.79 × 10−17 and −2.31 × 10−18 over the two representative areas of Greece (e.g., Thessaloniki and Kozani). A similar pattern is found for the snow water equivalent in the Italian study area, with a decreasing trend of −4.45 × 10−18. The presented results contribute to a better understanding of the spatial snow distribution and the snow coverage seasonality that could be crucial for the long-term groundwater management, by combining snow data trends from in-situ data and satellite statistics.

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.

In this study we focus on the retrieval of aerosol and trace gas vertical profiles from Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations for the first time over Thessaloniki, Greece. We use two independent inversion algorithms for the profile retrievals: The Mexican MAX-DOAS Fit (MMF) and the Mainz Profile Algorithm (MAPA). The former is based on the Optimal Estimation Method (OEM), while the latter follows a parameterization approach. We evaluate the performance of MMF and MAPA and we validate their retrieved products with ancillary data measured by other co-located reference instruments. We find an excellent agreement between the tropospheric column densities of NO2 retrieved by MMF and MAPA (Slope = 1.009, Pearson's correlation coefficient R = 0.982) and a good correlation for the case of HCHO (R = 0.927). For aerosols, we find better agreement for the aerosol optical depths (AODs) in the visible (i.e., at 477 nm), compared to the UV (360 nm) and we show that the agreement strongly depends on the O4 scaling factor that is used in the analysis. The trace gas differential slant column densities (dSCDs), simulated by the forward models, are also in good agreement, except for HCHO, where larger scatter is observed due to the increased spectral noise of the measurements in the UV. The agreement for NO2 and HCHO surface concentrations is similar to the comparison of the integrated columns with slightly decreased correlation coefficients. The AODs retrieved by the MAX-DOAS are validated by comparing them with AOD values measured by a CIMEL sun-photometer and a Brewer spectrophotometer. Four different flagging schemes were applied to the data in order to evaluate their performance. Qualitatively, a generally good agreement is observed for both wavelengths, but we find a systematic bias from the CIMEL and Brewer measurements, due to the limited sensitivity of the MAX-DOAS in retrieving information at higher altitudes, especially in the UV. An in-depth validation of the aerosol vertical profiles retrieved by the MAX-DOAS is not possible since only in very few cases the true aerosol profile is known during the period of study. However, we examine four cases, where the MAX-DOAS provided a generally good estimation of the shape of the profiles retrieved by a co-located multi-wavelength lidar system. The NO2 surface concentrations are validated against in situ observations and the comparison of both MMF and MAPA revealed good agreement with correlation coefficients of R = 0.78 and R = 0.73, respectively. Finally, the effect of the O4 scaling factor is investigated by intercomparing the integrated columns retrieved by the two algorithms and also by comparing the AODs derived by MAPA for different values of the scaling factor with AODs measured by the CIMEL and the Brewer.

Aerosols that are efficient ice-nucleating particles (INPs) are crucial for the formation of cloud ice via heterogeneous nucleation in the atmosphere. The distribution of INPs on a large spatial scale and as a function of height determines their impact on clouds and climate. However, in situ measurements of INPs provide sparse coverage over space and time. A promising approach to address this gap is to retrieve INP concentration profiles by combining particle concentration profiles derived by lidar measurements with INP efficiency parameterizations for different freezing mechanisms (immersion freezing, deposition nucleation). Here, we assess the feasibility of this new method for both ground-based and spaceborne lidar measurements, using in situ observations collected with unmanned aerial vehicles (UAVs) and subsequently analyzed with the FRIDGE (FRankfurt Ice nucleation Deposition freezinG Experiment) INP counter from an experimental campaign at Cyprus in April 2016. Analyzing five case studies we calculated the cloud-relevant particle number concentrations using lidar measurements (n250,drywith an uncertainty of 20 % to 40 % andSdrywith an uncertainty of 30 % to 50 %), and we assessed the suitability of the different INP parameterizations with respect to the temperature range and the type of particles considered. Specifically, our analysis suggests that our calculations using the parameterization ofUllrich et al.(2017)(applicable for the temperature range−50to−33 ∘C) agree within 1order of magnitude with the in situ observations ofnINP; thus, the parameterization ofUllrich et al.(2017)can efficiently address the deposition nucleation pathway in dust-dominated environments. Additionally, our calculations using the combination of the parameterizations ofDeMott et al.(2015,2010)(applicable for the temperature range−35 to−9 ∘C) agree within 2orders of magnitude with the in situ observations of INP concentrations (nINP) and can thus efficiently address the immersion/condensation pathway of dust and nondust particles. The same conclusion is derived from the compilation of the parameterizations ofDeMott et al.(2015)for dust andUllrich et al.(2017)for soot. Furthermore, we applied this methodology to estimate the INP concentration profiles before and after a cloud formation, indicating the seeding role of the particles and their subsequent impact on cloud formation and characteristics. More synergistic datasets are expected to become available in the future from EARLINET (European Aerosol Research Lidar Network) and in the frame of the European ACTRIS-RI (Aerosols, Clouds, and Trace gases Research Infrastructure). Our analysis shows that the developed techniques, when applied on CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar observations, are in agreement with the in situ measurements. This study gives us confidence for the production of global 3-D products of cloud-relevant particle number concentrations (n250,dry,SdryandnINP) using the CALIPSO 13-year dataset. This could provide valuable insight into the global height-resolved distribution of INP concentrations related to mineral dust, as well as possibly other aerosol types.

Measurements of cirrus clouds geometrical and optical properties, performed with a multi-wavelength PollyXT Raman Lidar, during the period 2008 to 2016 are analysed. The measurements were performed with the same instrument, during sequential periods, in three places at different latitudes, Gual Pahari (28.43° N, 77.15° E, 243 m a.s.l) in India, Elandsfontein (26.25° S, 29.43° E, 1745 m a.s.l) in South Africa and Kuopio (62.74° N, 27.54° E, 190 m a.s.l) in Finland. The lidar dataset has been processed by an automatic cirrus cloud detection algorithm. In the following, we present a statistical analysis of the lidar derived geometrical characteristics (cloud boundaries, geometrical thickness) and optical properties of cirrus clouds (cloud optical depth, lidar ratio, ice crystal depolarization ratio) measured in different latitudes that correspond to subtropical and subarctic regions as well as their seasonal variability. The effect of multiple-scattering from ice particles to the derived optical products is also considered and corrected in this study. Our results show that, over the subtropical stations, cirrus layers, which have a noticeable monthly variability, were observed between 7 to 13 km, with mid-cloud temperatures ranging from −60 °C to −21 °C and a mean thickness of 1295 ± 489 m and 1383 ± 735 m for Gual Pahari and Elandsfontein respectively. The corresponding overall mean cirrus optical depth at 355 nm is calculated to be 0.59 ± 0.39 and 0.40 ± 0.33, with lidar ratio values at 355 nm of 26 ± 12 sr and 25 ± 6 sr, respectively. A more extended dataset was acquired for the subarctic area of Kuopio Finland, between 2012 and 2016. The estimated average geometrical thickness of the cirrus clouds over Kuopio is 1200 ± 585 m and the temperature values vary from −71 °C to −21 °C, while the mean cirrus optical depth at 355 nm is 0.25 ± 0.2, with an estimated mean lidar ratio of 33 ± 7 sr, similar to the idar ratio values observed over middle latitude stations. The kind of information presented here can be rather useful in the cirrus parameterizations required as input to radiative transfer models, and can be a complementary tool to satellite products that cannot provide cloud vertical structure. In addition, a ground-based statistics of the cirrus properties could be useful in the validation and improvement of the corresponding derived products from satellite retrievals.

We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the Cloud-Aerosol Transport System (CATS) onboard the International Space Station (ISS). The study employs correlative CATS and EARLINET backscatter measurements within 50 km distance between the ground station and the ISS overpass and as close in time as possible, typically within 90 min, from February 2015 to September 2016. The results demonstrate the good agreement of CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig-Germany, Évora-Portugal and Dushanbe-Tajikistan are analysed here to demonstrate the performance of CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions CATS is in good agreement with EARLINET, independently of daytime/nighttime conditions. CATS low negative biases, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds, may lead to systematic deviations and slight underestimations of the total Aerosol Optical Depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, may lead to non-representative, unrealistic and cloud contaminated aerosol profiles. The distributions of backscatter coefficient biases show the relatively good agreement between the CATS and EARLINET measurements, although on average underestimations are observed, 22.3 % during daytime and 6.1 % during nighttime.

A long-term analysis and climatology of aerosol backscatter and extinction coefficients profiles using a five-year study period lidar dataset derived from a multiwavelenth Raman lidar at Thessaloniki station is presented. All measurements have been processed with the latest version of the Single Calculus Chain (SCCv5.1.6) fully automated algorithm, which has been developed to provide a common lidar processing tool, within EARLINET (European Aerosol Research Lidar NETwork) stations. The optical products delivered by the SCC tool have already been compared with the optical products derived from the operational algorithm of Thessaloniki (THessaloniki Aerosol LIdar Algorithm-THALIA) and discussed in terms of inhomogeneities. In this contribution, we analyze these products for climatological purposes, in order to investigate the aerosol columnar properties over Thessaloniki lidar station, drawing conclusions about the issues to be considered when switching from the current operational algorithm to the SCCv5. The SCCv5 algorithm is evaluated for the AOD both for 355 and 532 nm. The agreement with THALIA algorithm seems promising with correlations of 0.89 and 0.84, respectively, and absolute deviations within the range of the EARLINET quality requirements. Time series of the AOD at 355 nm denote a decrease of 0.017 per year in the free troposphere, a trend that is also shown in the AOD values derived from the operational algorithm (0.014). A decrease of 0.01 per year in the lower troposphere is also noted from the SCC, whereas the corresponding AOD values derived from the operational algorithm denote a decrease of 0.017.

Aerosols that are efficient ice nucleating particles (INPs) are crucial for the formation of cloud ice via heterogeneous nucleation in the atmosphere. The distribution of INPs on a large spatial scale and as a function of height determines their impact on clouds and climate. However, in-situ measurements of INPs provide sparse coverage over space and time. A promising approach to address this gap is to retrieve INP concentration profiles by combining particle concentration profiles derived by lidar measurements with INP efficiency parametrization for different freezing mechanisms (immersion freezing, deposition nucleation). Here, we assess the feasibility of this new method for both ground-based and space-borne lidar measurements, using airborne in-situ observations from an experimental campaign at Cyprus in April 2016. Analyzing five case studies we calculated the particle number concentrations using lidar measurements (with an uncertainty of 20 to 100 %) and we assessed the suitability of the different INP parameterizations with respect to the temperature range and the type of particles considered. Specifically, our analysis suggests that the parametrization of Ullrich et al. (2017) (applicable for the temperature range −50 °C to −33 °C) agree within 1 order of magnitude with the in-situ observations of nINP and can efficiently address the deposition nucleation pathway in dust-dominated environments. Additionally, the combination of the parameterizations of DeMott et al. (2015) and DeMott et al. (2010) (applicable 15 for the temperature range −35 °C to −9 °C) agree within 2 orders of magnitude with the in-situ observations of nINP and can efficiently address the immersion/condensation pathway of dust and continental/anthropogenic particles. The same conclusion is derived from the compilation of the parameterizations of DeMott et al. (2015) for dust and Ullrich et al. (2017) for soot. Furthermore, we applied this methodology to estimate the INP concentration profiles before and after a cloud formation, indicating the seeding role of the particles and their subsequent impact on cloud formation and characteristics. More synergistic data-sets are expected to become available in the future from EARLINET (European Aerosol Research Lidar NETwork) and in the frame of the European ACTRIS-RI (Aerosols, Clouds and Trace gases Research Infrastructure). Our analysis shown that the developed techniques, when applied on CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) space-born lidar observations, are in very good agreement with the in-situ measurements. This study give us confidence for the production of global 3D products of n250,dry, Sdry and nINP using the CALIPSO 13-yrs dataset. This could provide valuable insight into global height-resolved distribution of INP concentrations related to mineral dust, and possibly other aerosol types.

A cirrus cloud dataset from a groundbased lidar in a sub-arctic station is analyzed in terms of the particle depolarization ratio. The depolarization values -δ- showed a broad distribution, ranging between 0.25 and 0.7, with a mean value of 0.38 ± 0.07. This variability is examined in correlation with temperature dependencies and the cirrus optical depth. Depolarization values greater than 0.45 are observed from temperatures between -60oC and -40oC, where horizontally oriented planar ice crystals are to be expected. Two case studies are also, discussed and analyzed in terms of depolarization height dependence.

The purpose of this research is to investigate the ability of GOME-2 instrument on board on the MetOpA and MetOpB platforms, to deliver accurate geometrical features of lofted aerosol layers over the area of Thessaloniki. For this purpose, we use ground-based lidar data from the Thessaloniki lidar station that belongs to EARLINET network. Results of the validation between absorbing aerosol height (ΑΑΗ) fromΑΑΗ) from) from GOME-2 sensor and THELISYS lidar dataset products will be presented.

Results of a multi-year comparison of the aerosol optical depth, derived by two operational algorithms based on lidar measurements with a Raman/elastic backscatter lidar in Thessaloniki, Greece and ground-based sun photometer observations are presented. Measurements from the European Aerosol Research Lidar Network (EARLINET) database processed with the operational algorithm of Aristotle University of Thessaloniki (AUTH) for the period 2001-2007, have been reprocessed with the Single Calculus Chain (SCC) algorithm. The SCC algorithm was developed within the EARLINET to provide high quality, standardized aerosol optical products in near real time. The objective of this study is to verify for the case of Thessaloniki, the long-term consistency of the aerosol load estimates between the operational and the SCC derived data, in order to adopt the SCC for operational processing. The observed differences would introduce inhomogeneities in the time series when switching to SCC, so a full reprocessing is required. An investigation of the parameters affecting the comparisons is presented, considering the differences in the algorithms.

The long term analysis of 15 years of lidar data derived from a Raman lidar at Thessaloniki is presented here. All measurements have been processed with the latest version 4 of the EARLINET Single Calculus Chain algorithm and are compared with the results from the current operational retrieval algorithm. In this paper we investigate the consistency between the EARLINET database and SCC for the case of Thessaloniki and we identify the issues to be considered when switching from current operations to SCC.