As the MODIS era concludes, new missions like 3MI/EPS-SG and PACE/NASA are now delivering extensive multi-angular, multi-viewing polarimetric data on aerosols. This shift necessitates an evolution in chemistry-transport models (CTMs). Specifically, the successful assimilation of sophisticated aerosol optical properties into the European Centre for Medium-Range Weather Forecasts (ECMWF) CAMS model depends on precise microphysical definitions. This study addresses the existing microphysical inconsistencies that currently prevent the seamless assimilation of remote sensing observations into CTMs.We compare two generations of the CAMS model using observations from 2008. The first is the Cy42R1 Reanalysis, which incorporates MODIS Aerosol Optical Depth (AOD) at 550 nm through assimilation. The second is the Cy49R2 Forecast, an unconstrained forward simulation. Our analysis uses aerosol properties retrieved from both POLDER measurements and AERONET ground-based data, employing the GRASP algorithm. To ensure a consistent and fair comparison with CAMS assumptions, we adopt a chemical component approach. This involves decomposing the total aerosol loading into its specific components—Black Carbon (BC), Organic Matter (OM), Dust (DU), Sulphate (SU), and Sea Salt (SS)—and fixing their refractive indices and size parameters during the retrieval process.The CAMS model consistently underestimates AOD compared to both POLDER/GRASP and AERONET, a negative bias present in both its reanalysis and forecast products. Analysis of the Ångström Exponent indicates that the model frequently miscategorizes fine and coarse mode particles. This confusion results in a significant negative bias in CAMS's coarse mode AOD. Additionally, the Single Scattering Albedo (SSA) in CAMS lacks the spectral and spatial variability evident in the POLDER/GRASP retrievals. Further analysis reveals that optical discrepancies in the model's performance are rooted in chemical component-specific errors. The model significantly underrepresents the total column volume concentrations of fine-mode aerosols, especially BC and OM. Furthermore, modeled volume concentrations of SU and SS are negligibly low compared to observational data. For DU, a distinct shift in model strategy is apparent: the older Cy42R1 version underestimates DU volume concentration, while the newer Cy49R2 overestimates it, indicating a transition towards modeling coarser particle emissions. Validation against AERONET data confirms that POLDER/GRASP retrievals offer a reliable benchmark for these comparative assessments.Current CTMs and retrieval algorithms evidently operate under differing microphysical assumptions. This strongly implies underlying inaccuracies in the assumed aerosol size distributions and refractive indices within these models. The improved DU representation in Cy49R2 is a step forward, but the persistent underestimation of other components limits the model's application for radiative forcing calculations. The subsequent essential step involves harmonization. It is necessary that ECMWF update CAMS aerosol microphysics to incorporate effective radii, size distribution, and refractive indices consistent with state-of-the-art polarimetric retrievals. Establishing a unified definition for aerosol components will enable the next generation of CAMS reanalysis to effectively assimilate data from 3MI and PACE, consequently mitigating uncertainties in global aerosol forcing.

During the unusually long wildfire season in 2023, the multi-wavelength Mie-Raman-polarization-fluorescence lidar recorded a long time series of transported biomass burning aerosols. With these observations, we obtained a comprehensive dataset about the optical and microphysical properties of BBAs. In this study, we present a method for estimating BBA volume/mass concentrations from lidar observation. The derived profiles of volume and mass concentration show good consistency with airborne measurements and model simulations, respectively.

This project develops a relational database and interactive web system to organize and share aerosol and cloud optical and microphysical data from the Tables of Aerosol and Cloud Optics (TACO) that is part of the MIRA working group. The TACO project is an extension of historical efforts (e.g., Shettle and Fenn, 1979; d’Almeida et al., 1991; Koepke et al., 1997; Hess et al., 1998) on providing libraries of aerosol and cloud characteristics for applications in global chemical transport modeling and remote sensing. The optical and microphysical properties of aerosols and clouds are classified according to their origin, type, geographic region, wavelengths set etc. The combination of these characteristics, along with anticipated evolution, the open access and interactive principles of TACO, suggests that the data set structure becomes increasingly complex. We therefore suggest using specialized computer science techniques for the TACO data organization and management. To this end, we employ the relational database that consists in the data structuring in multiple tables with indexation relating the entities and their values in unique or multiple connections. The project will enable uploading the TACO data into the format of relational database and creation of a web interface for an efficient and interactive communication with the community. The presentation is expected to gather valuable feedback from modelers, in-situ and remote sensing experts on the data needs, exchange formats and potential applications.

The TRANSAMA campaign (Transit to AMARYLLIS-AMAGAS oceanographic cruise), conducted aboard the research vessel Marion Dufresne II assessed instrument performance and investigated aerosol properties during its transit from La Reunion Island to Barbados (April-May 2023). A set of remote sensing instruments, including two CE318-T Sun-sky-lunar photometers and a CE370 single-wavelength elastic lidar, was deployed under the MAP-IO (Marion Dufresne Atmospheric Program-Indian Ocean) framework. Performance assessments of the deployed instrumentation support the development of coupled lidar-photometer systems for shipborne atmospheric observations, while acknowledging current detection limits. Synergistic observations provided vertically resolved aerosol properties, such as extinction coefficients, alongside atmospheric structure, highlighting the marine boundary layer (MBL) top at 800 +/- 300 m. While the photometer observations revealed clean atmospheric conditions over the South Atlantic (AOD440=0.08 +/- 0.04), thin aerosol layers above the MBL were identified as long-range transported residual biomass-burning-urban aerosols from Southern Africa with effective LR of 33 +/- 12 sr. Cloud layers covering a large range of altitudes (up to 16 km) were observed in 53 % of the lidar profiles, with a higher frequency at lower altitudes, where aerosol layers were more frequently detected. These findings emphasize the impact of continental aerosols on remote oceanic regions and demonstrate the capabilities of synergistic lidar-photometer measurements for advancing our understanding of aerosol variability, cloud formation, and climate processes over the oceans.

This study presents the development of an automated aerosol typing model utilizing Mie-Raman-fluorescence lidar data collected by LILAS (Lille Lidar for Atmospheric Study), located on the ATOLL (ATmospheric Observations at LiLLe) platform in Lille, France. The proposed model, FLARE-GMM (Fluorescence Lidar-based Aerosol REcognition from Gaussian Mixture Model), employs a Gaussian mixture model trained on a dataset spanning from early 2021 to the end of 2023. FLARE-GMM is able to distinguish the predominant aerosol type in a given layer between dust, urban, and biomass burning aerosols by using the PLDR (particular linear depolarization ratio) and the fluorescence capacity, as well as relative humidity, all measured with LILAS. To ensure accurate model training, cases were manually selected to include only pure aerosol layers, as mixed aerosols are not accurately modeled by GMM. Following the training phase, the model's performance was evaluated by investigating extreme events in which the aerosol type is not ambiguous. This approach was also completed with the use of a test dataset, on which FLARE-GMM was compared to NATALI (Neural Network Aerosol Typing Algorithm Based on Lidar Data), another automatic aerosol typing model based on neural networks using lidar data. The results demonstrated that FLARE-GMM shows promise in accurately identifying aerosol types, indicating its potential for classifying aerosols in a variety of situations. Finally, FLARE-GMM was used to estimate the aerosol types present in Lille's atmosphere throughout the entire dataset from early 2021 to the end of 2023. A statistical analysis of these results was conducted, further underscoring the model's capability in automated aerosol classification.

Mineral dust is a key atmospheric aerosol agent that impacts the radiation budget and plays a significant role in cloud formation. However, studies on retrieving height-resolved microphysical properties of dust aerosols, which are crucial for understanding dust evolution, transport processes, and radiative effects, from lidar measurements are still insufficient. Here, we retrieve dust aerosol microphysical properties, including the volume size distribution (VSD), total volume concentration (Vt), effective radius (reff), complex refractive index (CRI), and single-scattering albedo (SSA), from spectral extinction (alpha), backscattering (beta), and depolarization (delta) lidar measurements. We evaluate the performance of three particle scattering models, namely the spherical, spheroidal, and irregular-hexahedral (IH) models, in terms of mimicking dust optical properties and deriving retrieval results when different measurement combinations are inverted. Both simulations and inversions of real lidar measurements confirm the superiority of the IH model and the significance of spectral depolarization measurements to improve the retrieval accuracy. An increase in discrepancy in depolarization ratio produced by the IH and spheroid models is observed for reff>0.5 mu m, resulting in larger retrieval difference between the two non-spherical models after the inclusion of 3 delta. Comparisons of the real case retrievals with Aerosol Robotic Network (AERONET) retrievals and previous in situ results indicate relatively smaller reff and larger SSA derived from the lidar retrievals. A discussion of the possible reasons is presented.

Abstract. This study presents lidar observations of long-range transported biomass burning aerosol (BBA) plumes from the exceptional 2023 Canadian wildfire season, recorded between May and September at the ATOLL observatory (France) and the GPI site (Russia). ATOLL operates a multi-wavelength Raman lidar with 3 polarization channels (355, 532 and 1064 nm) and a single fluorescence channel at 466 nm. GPI uses a fluorescence lidar with 5 broadband fluorescence channels excited by 355 nm. The dual-site dataset combines multi-wavelength elastic scattering and depolarization measurements with fluorescence observations, enabling a comprehensive characterization of BBA properties in the free troposphere (FT) and upper troposphere–lower stratosphere (UTLS). UTLS layers exhibit higher particle depolarization ratios, slightly lower lidar ratios, lower extinction- and backscatter-related Angström exponents, and a redshift in fluorescence spectral peaks. Cross-site comparisons show consistent fluorescence magnitudes and spectral shapes, highlighting the potential of coordinated multi-lidar fluorescence observations. Correlation analysis indicates that depolarization ratio, extinction-related Angström exponent, and fluorescence color ratio are moderately (r2 ≈ 0.61–0.68) correlated with layer altitude, however, this correlation is not sufficient to confirm a solid altitude dependence. It is likely that altitude is an intermediate variable linked to other controlling factors such as injection height of the plume, in-layer temperature and the plume origin. In addition, we observed BBAs showing no clear hygroscopic growth at RH of 90 %–100 % and statistically low RH values in the detected nearly 100 layers, suggesting aged BBAs, which were typically considered as hygroscopic, may have limited water uptake capability.

Aerosols are emitted into the atmosphere by natural and anthropogenic events. They scatter and absorb the incoming solar radiation playing a major role in heating and cooling the atmosphere. To determine the heating and cooling rates, remote sensing and global climate modelers use the optical and physical properties of these aerosols. Table of Aerosol Optics (TAO) database is a platform for the scientists to acquire the optical properties of several aerosol species and types for wavelengths ranging from 0.25 µm to 40 µm (673 values) including phase matrices for 203 angles and 36 relative humidity values. TAO will provide the users with choices on the source, shape, size distribution, wavelength range, etc. to accommodate the needs from various atmospheric science groups. We have generated the optical calculations such as the extinction, absorption, single scattering albedo, asymmetry parameter, phase functions etc. using Mie theory for spherical aerosol species like Black Carbon (BC), Organic Carbon (OC) etc. along with an OCBC mixture. OC varies in composition depending on the source of emission. For instance, wildfire emits highly absorbing OC such as Tarballs (type of BrC) along with low viscous OC whereas, anthropogenic emissions generate slightly absorbing OC such as Toluene derived aerosols. The number fraction of Tarballs range from 10% to 95% depending on transport distance and atmospheric aging. Anthropogenic aromatic compounds such as Toluene and Xylene constitute about 70% of the total OC. Organic aerosol being complex in composition, we have classified them based on their optical parameters such as single scattering albedo (SSA) and mass absorbing coefficient (MAC). In TAO we classified organic aerosols into three groups based on their MAC values as: Brown Carbon, Slightly Absorbing Aerosol, and Scattering Aerosol. This classification will improve the representation of organic aerosols in climate and weather models. Hence the TAO database has a potential to replace the database that was developed decades ago and are being widely used among the modeling communities. Using the measurements from latest study will improve the climate and weather data.

This effort is dedicated to construction of a relational database and an interactive web system that organizes and communicates aerosol optical and microphysical characteristics assembled in the Table of Aerosol Optics (TAO) community repository. The TAO project (https://science.larc.nasa.gov/mira-wg/topics/tao/) is an extension of historical efforts (e.g., Shettle and Fenn, 1979; d’Almeida et al., 1991; Koepke et al., 1997; Hess et al., 1998) on providing libraries of aerosol characteristics for applications in global chemical transport modeling and remote sensing. Aerosol characteristics such as size distribution, complex refractive index, shape, mixing state, extinction, absorption, single-scatter albedo, lidar ratio, etc. are provided for different aerosol types, wavelengths, be originated from laboratory measurements, in situ or remote sensing observations. Combination of aerosol characteristics, their origins, types, spectral domains, computational techniques used for single-scatter properties become quickly very complex and is expected to evolve in future. The open access and interactive principles of TAO implies increasing complexity of its database structure that requires involvement of dedicated computer science technics for its organization and management. The relational database conception, for instance, is widely used in many domains that require such data organization and naturally appropriates to TAO. The relational database consists in structuring the data in multiple tables, with so-called primary or foreign keys that relates between entity types, parameters and their value in unique or multiple connections. We therefore started development of tools for uploading of the TAO data into the format of relational database and creation of a web interface for an interactive communication with the community. This work is expected to be presented as complimentary to a more general presentation about the TAO project by G. L. Schuster and gather valuable feedbacks from modelers, in situ and remote sensing experts on the data needs, convenient exchange formats and potential applications.

There is a need to quickly convert aerosol microphysical properties into optical properties for global modeling, data assimilation, and remote sensing applications. This is generally accomplished through look-up tables (LUTs) of aerosol mass extinction coefficients (MEC), mass absorption coefficients (MAC), asymmetry parameters, normalized phase functions, etc. Unfortunately, many scientists are using outdated LUTs that are based upon measurements and computational techniques first published by Shettle and Fenn (1979) and later updated by Hess et al. (1998). Thus, the computations in common use are still largely based upon Mie theory and in situ information that has not been updated during this century.The Table of Aerosol Optics (TAO) is an open relational database (under construction) that expands upon existing LUTs by including recent measurements and new computational techniques for non-spherical particles (https://science.larc.nasa.gov/mira-wg/topics/tao/). The ‘open’ aspect of TAO is important, since the measurements and techniques of today will undoubtedly yield to different values in the future. This open architecture allows specialists to add new tables and gain exposure for their work and benefits modelers and remote sensing scientists by giving them easy access to computations that utilize the latest techniques. Quality is controlled by requiring methods to be peer-reviewed in the scientific literature.Thus far, we have computed mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at 73 wavelengths ranging from 0.25-40 µm for black carbon (BC), brown carbon (BrC), non-absorbing organic carbon, and mineral dust. For mineral dust, we use hexahedra shapes and mineral mixtures of montmorillonite, illite, hematite, and goethite. The illite volume fraction varies from 0 to 59% to capture the range of real refractive indices found in AERONET climatologies; the sum of the hematite and goethite mass fractions are ~2%. Additional mixtures will be added as appropriate.We have also computed optical properties for 22 size distributions of bare aggregated BC using the Multi-Sphere T-Matrix (MSTM) code (https://github.com/dmckwski/MSTM) at several remote sensing wavelengths. Our MSTM computations use aggregates of 20-nm spherules with particle-cluster growth. We obtained mass absorption coefficients (MACs) of 7.2-7.5 m2/g at a mid-visible wavelength (532 nm) when the BC fractal dimension was fixed at Df = 1.8 (i.e., fresh BC), consistent with values commonly recommended in literature reviews.We will present the TAO vision and example results for several aerosol types. TAO is part of the Models, In situ, and Remote sensing of Aerosols (MIRA) working group. MIRA seeks to build collaboration, consistency, and openness amongst the aerosol disciplines. We seek community feedback from aerosol scientists regarding the construction and content of TAO, especially in this early phase. Check out the MIRA webpage at https://science.larc.nasa.gov/mira-wg/ and subscribe to our mailing list at https://espo.nasa.gov/lists/listinfo/mira.Hess et al. (1998): Optical properties of aerosols and clouds: The software package OPAC, BAMS, 79, 831–844.Shettle and Fenn (1979): Tech. Rep. AFGL-TR-790214, Air Force Geophysics Laboratory, 1979.

This study focuses on the characterization of aerosol hygroscopicity using remote sensing techniques. We employ a Mie–Raman–fluorescence lidar (Lille Lidar for Atmospheric Study, LILAS), developed at the ATOLL platform, Laboratoire d'Optique Atmosphérique, Lille, France, in combination with the RPG-HATPRO-G5 microwave radiometer to enable continuous aerosol and water vapor monitoring. We identify hygroscopic growth cases when an aerosol layer exhibits an increase in both aerosol backscattering coefficient and relative humidity. By examining the fluorescence backscattering coefficient, which remains unaffected by the presence of water vapor, the potential temperature, and the absolute humidity, we verify the homogeneity of the aerosol layer. Consequently, the change in the backscattering coefficient is solely attributed to water uptake. The Hänel theory is employed to describe the evolution of the backscattering coefficient with relative humidity and introduces a hygroscopic coefficient, γ, which depends on the aerosol type. The particularity of this method revolves around the use of the fluorescence which is employed to take into account and correct the aerosol concentration variations in the layer. Case studies conducted on 29 July and 9 March 2021 examine, respectively, an urban and a smoke aerosol layer. For the urban case, γ is estimated as 0.47 ± 0.03 at 532 nm; as for the smoke case, the estimation of γ is 0.5 ± 0.3. These values align with those reported in the literature for urban and smoke particles. Our findings highlight the efficiency of the Mie–Raman–fluorescence lidar and microwave radiometer synergy in characterizing aerosol hygroscopicity. The results contribute to advance our understanding of atmospheric processes, aerosol–cloud interactions, and climate modeling.

We present the capabilities of a compact dual-wavelength depolarization lidar to assess the spatiotemporal variations in aerosol properties aboard moving vectors. Our approach involves coupling the lightweight Cimel CE376 lidar, which provides measurements at 532 and 808 nm and depolarization at 532 nm, with a photometer to monitor aerosol properties. The assessments, both algorithmic and instrumental, were conducted at ATOLL (ATmospheric Observatory of LiLle) platform operated by the Laboratoire d'Optique Atmosphérique (LOA), in Lille, France. An early version of the CE376 lidar co-located with the CE318-T photometer and with a multi-wavelength Raman lidar were considered for comparisons and validation. We developed a modified Klett inversion method for simultaneous two-wavelength elastic lidar and photometer measurements. Using this setup, we characterized aerosols during two distinct events of Saharan dust and dust smoke aerosols transported over Lille in spring 2021 and summer 2022. For validation purposes, comparisons against the Raman lidar were performed, demonstrating good agreement in aerosol properties with relative differences of up to 12 % in the depolarization measurements. Moreover, a first dataset of CE376 lidar and photometer performing on-road measurements was obtained during the FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality) field campaign deployed in summer 2019 over the northwestern USA. By lidar and photometer mapping in 3D, we investigated the transport of released smoke from active fire spots at William Flats (northeast WA, USA). Despite extreme environmental conditions, our study enabled the investigation of aerosol optical properties near the fire source, distinguishing the influence of diffuse, convective, and residual smoke. Backscatter, extinction profiles, and column-integrated lidar ratios at 532 and 808 nm were derived for a quality-assured dataset. Additionally, the extinction Ångström exponent (EAE), color ratio (CR), attenuated color ratio (ACR), and particle linear depolarization ratio (PLDR) were derived. In this study, we discuss the capabilities (and limitations) of the CE376 lidar in bridging observational gaps in aerosol monitoring, providing valuable insights for future research in this field.

Mineral dust significantly influences the Earth's climate system by affecting the radiative balance through the emission, absorption and scattering of solar and terrestrial radiation. Estimating the dust radiative effect remains challenging due to the lack of detailed information on the physical and chemical properties of dust. High-spectral-resolution instruments in the infrared (IR) spectrum, such as the Infrared Atmospheric Sounding Instrument (IASI), have demonstrated the ability to quantify these aerosol properties. A crucial parameter for characterizing mineral dust from space is the complex refractive index (CRI), as it links the dust's physical and chemical properties to its optical properties. This paper examines the impact of six prior laboratory CRI datasets to improve the characterization of dust microphysical properties using IASI. The CRIs include older measurements obtained through the classical pellet method, commonly employed in mineral dust applications, as well as newer datasets that incorporate the latest advancements in laboratory measurement techniques for aerosol generation. These datasets are tested on IASI measurements during a dust storm event over the Gobi Desert in May 2017. We evaluate the sensitivity of IASI to different CRI datasets using the Atmospheric Radiation Algorithm for High-Spectral Resolution Measurements from Infrared Spectrometer (ARAHMIS) radiative transfer algorithm and explore the datasets' impact on retrieving size distribution parameters by mapping their spatial distributions. The results indicate that the laboratory CRI datasets decrease the total error in the covariance matrix by 30 %. In addition, we assess the ability to accurately reconstruct IASI detections and the extent to which we can retrieve the microphysical properties of dust particles. The choice of CRI significantly impacts the accuracy of dust detection and characterization from satellite observations. Notably, datasets that incorporate recent aerosol generation techniques with higher spectral resolution and samples from the case study region show improved compatibility with IASI observations. The outcomes of this research emphasize two key points: the crucial link between chemical composition of dust and its optical properties and the importance of considering the specific composition of the CRI dataset for improved retrieval of the microphysical parameters. Furthermore, this study highlights the critical role of ongoing enhancements in CRI measurement approaches, as well as the potential of high-spectral-resolution infrared sounders for aerosol atmospheric investigation and for understanding the radiative impacts of sounders.

The study presents a climatology of aerosol composition concentrations obtained by a recently developed algorithm approach, namely the Generalized Retrieval of Atmosphere and Surface Properties (GRASP)/Component. It is applied to the whole archive of observations from the POLarization and Directionality of the Earth's Reflectances (POLDER-3). The conceptual specifics of the GRASP/Component approach is in the direct retrieval of aerosol speciation (component fraction) without intermediate retrievals of aerosol optical characteristics. Although a global validation of the derived aerosol component product is challenging, the results obtained are in line with general knowledge about aerosol types in different regions. In addition, we compare the GRASP-derived black carbon (BC) and dust components with those of the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) product. Quite a reasonable general agreement was found between the spatial and temporal distribution of the species provided by GRASP and MERRA-2. The differences, however, appeared in regions known for strong biomass burning and dust emissions; the reasons for the discrepancies are discussed. The other derived components, such as concentrations of absorbing (BC, brown carbon (BrC), iron-oxide content in mineral dust) and scattering (ammonium sulfate and nitrate, organic carbon, non-absorbing dust) aerosols, represent scarce but imperative information for validation and potential adjustment of chemical transport models. The aerosol optical properties (e.g., aerosol optical depth (AOD), Ångström exponent (AE), single-scattering albedo (SSA), fine- and coarse-mode aerosol optical depth (AODF AND AODC)) derived from GRASP/Component were found to agree well with the Aerosol Robotic Network (AERONET) ground reference data, and were fully consistent with the previous GRASP Optimized, High Precision (HP) and Models retrieval versions applied to POLDER-3 data. Thus, the presented extensive climatology product provides an opportunity for understanding variabilities and trends in global and regional distributions of aerosol species. The climatology of the aerosol components obtained in addition to the aerosol optical properties provides additional valuable, qualitatively new insight about aerosol distributions and, therefore, demonstrates advantages of multi-angular polarimetric (MAP) satellite observations as the next frontier for aerosol inversion from advanced satellite observations. The extensive satellite-based aerosol component dataset is expected to be useful for improving global aerosol emissions and component-resolved radiative forcing estimations. The GRASP/Component products are publicly available (https://www.grasp-open.com/products/, last access: 15 March 2022) and the dataset used in the current study is registered under https://doi.org/10.5281/zenodo.6395384 (Li et al., 2022b).

Aerosol absorption is a key property to assess the radiative impacts of aerosols on climate at both global and regional scales. The aerosol physico-chemical and optical properties remain not sufficiently constrained in climate models, with difficulties to properly represent both the aerosol load and their absorption properties in clear and cloudy scenes, especially for absorbing biomass burning aerosols (BBA). In this study we focus on biomass burning (BB) particle plumes transported above clouds over the southeast Atlantic (SEA) region off the southwest coast of Africa, in order to improve the representation of their physico-chemical and absorption properties. The methodology is based on aerosol regional numerical simulations from the WRF-Chem coupled meteorology–chemistry model combined with a detailed inventory of BB emissions and various sets of innovative aerosol remote sensing observations, both in clear and cloudy skies from the POLDER-3/PARASOL space sensor. Current literature indicates that some organic aerosol compounds (OC), called brown carbon (BrOC), primarily emitted by biomass combustion absorb the ultraviolet-blue radiation more efficiently than pure black carbon (BC). We exploit this specificity by comparing the spectral dependence of the aerosol single scattering albedo (SSA) derived from the POLDER-3 satellite observations in the 443–1020 nm wavelength range with the SSA simulated for different proportions of BC, OC and BrOC at the source level, considering the homogeneous internal mixing state of particles. These numerical simulation experiments are based on two main constraints: maintaining a realistic aerosol optical depth both in clear and above cloudy scenes and a realistic BC/OC mass ratio. Modelling experiments are presented and discussed to link the chemical composition with the absorption properties of BBA and to provide estimates of the relative proportions of black, organic and brown carbon in the African BBA plumes transported over the SEA region for July 2008. The absorbing fraction of organic aerosols in the BBA plumes, i.e. BrOC, is estimated at 2 % to 3 %. The simulated mean SSA are 0.81 (565 nm) and 0.84 (550 nm) in clear and above cloudy scenes respectively, in good agreement with those retrieved by POLDER-3 (0.85±0.05 at 565 nm in clear sky and at 550 nm above clouds) for the studied period.

Abstract. The Mediterranean atmosphere is impacted by a variety of natural and anthropogenic aerosols, which exert a complex and variable pressure on the regional climate and air quality. In this study, we investigate aerosol spatial distribution and temporal evolution over the western Mediterranean Sea (west of longitude 20° E) using the full POLDER-3/PARASOL aerosol data record derived from the operational clear-sky ocean algorithm (collection 3) available from March 2005 to October 2013. This 8.5-yr satellite data set includes retrievals at 865 nm of the total, fine, and coarse mode aerosol optical depth (AOD, AODF, and AODC, respectively), Angström exponent (AE), and the spherical/non-spherical partition of the coarse-mode AOD (AODCS and AODCNS, respectively). In a previous paper (Formenti et al., 2018), these POLDER-3-derived aerosol properties have been carefully validated over the study region, based on coincident ground-based and airborne aerosol measurements. Here we analyze the spatial distribution, the seasonal cycle and interannual variability of this ensemble of products in three latitude bands (34–38° N, 38–42° N, and > 42° N) and for three sites (Ersa, Barcelona, Lampedusa) distributed on the western basin Overall the POLDER-3 AOD spatial distribution exhibits a well-known south-to-north decreasing gradient, and a seasonal cycle characterized by enhanced aerosol loads in spring and summer, both controlled by Saharan dust. POLDER-3 retrievals of AE, AODF, AODC, and fine mode fraction (AODF/AOD) highlight the influence of coarse particles in the southern part of the region, off the north African coast, and higher relative contribution of fine particles in the northern part, off the south European coast, with all year long persistent elevated loads over the Adriatic Sea. Over the rest of the western Mediterranean Sea, POLDER-3 retrievals show a more homogeneous spatial distribution of fine particles than that of coarse particles, even though climatological means of AODF highlight seasonal differences in the order of a factor 2 between the cleanest conditions occurring in the southern part of the basin in winter and those most polluted observed in its northern part in Spring. The seasonal and spatial variability of AODCNS is close to that observed for AODC, whereas POLDER-3 exhibit relatively low and weakly variable levels of coarse spherical particles (AODCS