North Africa and the Middle East encompass the most active dust sources on the planet. Due to the limited availability of ground-based aerosol observations across the deserts, spaceborne retrievals represent the most reliable source of information for monitoring dust particles over these vast areas. In the current study, we present a synergistic approach incorporating aerosol retrievals acquired by active (CALIOP) and passive (POLDER-3, MODIS) instruments mounted on satellites of the A-Train constellation. Our main objective is to dynamically (in terms of space and time) estimate the dust lidar ratio (LR) at 532 nm throughout a 12-year period (2006-2017) by collocating columnar aerosol optical depth observations (POLDER-3/GRASP, MIDAS) and vertically resolved dust aerosol profiles obtained by CALIPSO. According to our findings, the derived dust LRs reveal a clear spatial variability. The highest LRs are found over major Saharan source regions such as the Bod & eacute;l & eacute; Depression and the Libyan Desert, while moderate to low values dominate the Arabian Peninsula. Enhanced values also appear across Central Asia, particularly over the Karakum and Kyzylkum deserts. The corresponding uncertainty fields demonstrate that LR estimates are most robust over regions with a larger number of dust cases, whereas higher uncertainties occur along transition zones - such as the Sahel and parts of Central Asia - where dust mixing or aerosol-type misclassification increases retrieval variability. A key objective of this work is to establish a robust methodology for deriving aerosol-speciated LRs using synergies between active and passive observations. Although focused here on dust over North Africa and the Middle East, the same framework can be readily applied to other CALIPSO aerosol subtypes - such as marine, polluted dust, or smoke - when implemented over regions where these aerosol types predominate. The advent of the EarthCARE satellite mission, along with the incorporation of new aerosol models into the forthcoming CALIPSO Version 5 aerosol retrieval algorithm, will serve as a reference for our calculations. In this context, our findings also highlight that a synergy of multisensor aerosol products with modelling tools can enhance the spatiotemporal representation of aerosol properties, such as the LR, further improving retrieval utility.

We present an innovative retrieval approach called AEROTYPro/GRASP (Aerosol Type Profiling/Generalized Retrieval of Aerosol and Surface Properties) to quantitatively discriminate the vertical profiles of five distinct aerosol types simultaneously present in the atmosphere, corresponding to smoke, continental, oceanic, dust, and urban polluted. Along with their abundances, it also derives bulk optical and microphysical properties for the total aerosol mixture (those of individual aerosol types are assumed). These are original capabilities compared to Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) spaceborne backscatter aerosol typing approaches, which offer a qualitative identification of the most probable aerosol type. AEROTYPro is here designed to use measurements of spaceborne multi-wavelength backscatter lidars, such as the one called LUCE, initially conceived to be part of the Atmosphere Observing System (AOS) mission formulation development program. This newly developed AEROTYPro retrieval approach is here implemented using simulations from the chemistry transport model (CTM) Mode`le de Chimie Atmospherique de Grande Echelle (MOCAGE) to derive a pseudoreality. Simulated aerosol concentration profiles are used to calculate lidar signals of attenuated backscatter and depolarization vertical profiles at 355 nm, 532 nm, and 1064 nm. Then, these synthetic lidar signals are utilized as inputs of AEROTYPro to retrieve pseudo-observations of vertical profiles of aerosol types and their bulk optical and microphysical properties. Our findings show a satisfactory performance of AEROTYPro for retrieving aerosol mixing ratio vertical profiles for smoke, continental, oceanic, dust and urban polluted aerosol types, even when several aerosol types are present at the same locations and altitudes in the atmosphere. For this, we use the GRASP algorithm with distinct initial guesses of mixing ratio vertical profiles for each aerosol type, which are identical for all pixels. The other variables, such as aerosol optical depth (AOD) at 532 nm, single scattering albedo (SSA), lidar ratio (LR), absorbing aerosol optical depth (AAOD) and effective radius (Reff), are also in good agreement with the pseudo-reality. These results are obtained for both a detailed single-transect analysis describing several aerosol outbreaks and 18 complete orbits covering the whole globe with a similar global coverage as daily CALIOP spaceborne lidar measurements. This shows that our retrieval approach can retrieve quantitatively aerosol vertical profiles for five distinct types, along with other aerosol properties across the globe based on multiwavelength backscatter lidar measurements. These AEROTYPro-derived aerosol properties present a significant opportunity for developing innovative applications in air quality assessment and direct and indirect aerosol radiative forcing analysis.

The Copernicus Sentinel-3 mission, carrying the Ocean and Land Colour Instrument (OLCI) and the Sea and Land Surface Temperature Radiometer (SLSTR), provides critical observations for monitoring atmospheric composition. Operational Level-2 algorithms for aerosol and cloud retrievals rely on accurate information from the Sentinel-3 Land Surface Reflectivity (LSR) Auxiliary Product to stabilize the inversion process. To address this requirement, this static LSR product is being developed at 1–2 km spatial resolution using a hybrid GRASP retrieval approach.The hybrid GRASP approach is designed to provide stable full BRDF retrievals by reducing the number of parameters to be inverted. In this framework, aerosol properties at coarse resolution are not retrieved but are instead reused from existing multi-year datasets, such as PARASOL/GRASP and VIIRS. Furthermore, coarse-resolution surface products from the PARASOL/POLDER-3 satellite are utilized as a priori information for the high-resolution retrieval. Within this framework, OLCI benefits from its dense spectral sampling in the visible to near-infrared range, which is well suited for characterizing surface reflectance and BRDF spectral dependence. SLSTR complements this capability through its dual-viewing geometry, which provides additional constraints on surface anisotropy and helps reduce ambiguities between atmospheric and surface contributions. In addition, SLSTR’s short-wave and thermal infrared bands enhance cloud and snow screening and support more robust atmospheric correction.In this work, we evaluate the generated LSR auxiliary product derived from Sentinel-3 OLCI and SLSTR measurements. The assessment follows a hierarchical strategy: first, the impact of the generated LSR is demonstrated by validating retrieved aerosol properties (AOD, Ångström exponent) globally against AERONET ground observations. Second, the retrieved surface BRDF is validated regionally against the GROSAT reference dataset, which provides synergetic AERONET and OLCI-A/B retrievals. Third, the products are compared with MODIS MCD43A3 surface albedo at the global scale, demonstrating strong spatial and radiometric consistency. The impact of the generated LSR dataset on aerosol property retrievals, aerosol layer height (ALH), water vapor (WV) and cloud properties is also discussed.

Abstract. Accurately retrieving the properties of mineral dust aerosol is critical for quantifying its impacts on climate and air quality. However, these retrievals are often hindered by overly simplistic assumptions about particle shape. To address this, we test the ability of two non-spherical particle models—a conventional spheroid model and a more recent hexahedral model from the TAMUdust2020 database—to simultaneously reproduce co-located lidar (HSRL-2) and polarimeter (RSP) observations. We performed this test on two Saharan dust events observed over the Atlantic Ocean during the ORACLES 2018 campaign. The test was conducted via a combined atmosphere and surface retrieval using the Generalized Retrieval of Atmosphere and Surface Properties (GRASP), for which we augmented the standard spheroid kernel with a newly implemented hexahedral kernel. Each shape model was then evaluated across three distinct retrieval configurations: HSRL-only, RSP-only, and a combined synergistic HSRL+RSP retrieval. This combined approach leverages the polarimeter’s high sensitivity to total column absorption and particle size with the lidar’s precise vertical profiling. Significantly, this work also presents the first reported one-step synergistic retrieval for desert dust using combined High Spectral Resolution Lidar (HSRL) and polarimeter observations. We find the hexahedral model consistently provides physically plausible estimates of dust size, refractive indices (n, k), and single-scattering albedo (SSA), whereas the spheroid model requires unrealistic values—such as negligible absorption and an uncharacteristically low real refractive index (n ≤ 1.45)—to match the stringent constraints imposed by the synergistic lidar and polarimeter observations. The spheroid-based retrievals also led to significant cross-instrument inconsistencies, with divergent size and refractive index estimates between RSP-only and RSP+HSRL retrievals. We found that this is rooted in the spheroid model’s limited ability to reproduce high observed particle depolarization ratios within the size distributions and complex refractive indices in the range expected for coarse-mode Saharan dust. Ultimately, the hexahedral model provides a consistent and more physically realistic retrieval of coarse-mode dust properties that fits all observations within their measurement uncertainties.

The new satellite missions including active sensors (e.g. EarthCare), passive multi-angular polarimeters (e.g. PACE/SPEXone, PACE/HARP-2) and single-viewing instruments (e.g. OLCI), together with synergies among existing sensors, are foreseen to characterize aerosols and clouds with high accuracy. However, robust validation activities are essential to ensure the quality of the new satellite products.In this study, we focus on the evaluation of the aerosol optical properties synergistically retrieved from three sensors, i.e., TROPOMI, OLCI-A, and OLCI-B, within the framework of the AIRSENSE ESA project (https://www.grasp-earth.com/portfolio/airsense/). The derived optical properties include the aerosol optical depth (AOD), Ångström exponent (AE), coarse- and fine-mode AOD, and single-scattering albedo (SSA). Validation is performed against ground-based sun-photometer observations from five ACTRIS/AERONET stations across Europe (https://aeronet.gsfc.nasa.gov/). The results show good agreement for AOD with root-mean-square errors (RMSE) ranging from 0.006 to 0.09. In contrast, AE and SSA show lower agreement, with RMSE values of 0.27 and 0.02, respectively, at the Limassol station, even when quality flags are applied.Moreover, we evaluate the aerosol properties retrieved using PACE/SPEXone observations. PACE (Plankton, Aerosol, Cloud, and ocean Ecosystem) mission was launched in February 2024 and employs advanced passive polarimetric observations to enhance the aerosol characterization. In addition to aerosol optical properties (e.g., AOD, AE) the PACE/SPEXone products generated within the framework of AIRSENSE, include the aerosol layer height (ALH), a parameter that is critical for quantifying aerosol-cloud interactions. Since EarthCARE/ATLID provides vertically resolved aerosol profiles, it offers an independent reference for the assessment of ALH. Here, we present first comparison results of the PACE/SPEXone ALH product over the ocean, produced with two algorithms, RemoTAP and FastMAPOL, compared to EarthCARE/ATLID weighted backscatter heights. Overall, RemoTAP ALH products are systematically lower than those derived from EarthCARE/ATLID, whereas FastMAPOL retrieves a larger number of ALH estimates but exhibits lower overall agreement with the EarthCARE/ATLID reference. As a next step, we intend to expand the area of interest and increase the number of collocations. Acknowledgements:This research is financially supported by the PANGEA4CalVal project (Grant Agreement 101079201) funded by the European Union and the AIRSENSE (Aerosol and aerosol cloud Interaction from Remote SENSing Enhancement) project, funded by the European Space Agency under Contract No. 4000142902/23/I-NS.

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.

The Advanced Himawari Imager (AHI) onboard the Himawari-8 geostationary satellite is an imager with 16 spectral bands covering from the visible to infrared. The AHI has high temporal resolution with observation frequency of every 10 min and high spatial resolution 0.5–2 km (depending on channel) for full disk, which provides great potential for studying the dynamics of aerosol properties in East Asia and Western Pacific regions. In this study, the development of aerosol and surface property retrievals from the AHI/Himawari-8 using the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm is described. Due to the pseudo multi-angular observations obtained from AHI/Himawari-8 and the flexibility of GRASP algorithm with its innovative multi-pixel concept, multiple time and spatial pixels were retrieved simultaneously with both aerosol and surface properties constrained between the pixels together with additional constraints on spectral variability of underlying surface parameters within each pixel. The developed GRASP based algorithm has been applied to AHI/Himwari-8 observations over land for the entire year of 2018, and over ocean for May 2018 only, due to computational resource limitations and the relatively lower complexity of aerosol retrievals over ocean. The generated retrieval products were validated against the Aerosol Robotic Network (AERONET) measurements and were also intercompared with the Moderate Resolution Imaging Spectroradiometer (MODIS) surface products. Overall, the validation analysis shows robust agreement of AHI/GRASP spectral AOD product with AERONET with correlation coefficients of 0.82–0.93 across the spectrum over land. The AHI/GRASP results demonstrate encouraging agreement with AERONET that is with 34.4 % of the AOD (510 nm) satisfying the Global Climate Observing System (GCOS) requirement, and a bias within ±0.02 for AOD over land. The validation for fine and coarse mode AOD also showed promising results with a correlation of 0.89 and mean bias of 0.04 for fine mode AOD when compared with AERONET measurements. As for the intercomparisons with MODIS products, the overall performance is quite comparable to MODIS surface products. In addition to the analysis of AHI/Himawari-8 alone retrieval, this study demonstrated a novel synergetic retrieval between AHI/Himawari-8 and micro-pulse lidar (MPL). Using this synergy resulted in further improvements of the aerosol retrievals especially over the low AOD conditions due to the improved sensitivity to aerosol.

The potential presence of super coarse desert dust aerosol particles with volume radii larger than 15 microns in the atmosphere has recently become one of hot topics intensively discussed in the modeling and observation community. Such large particles may represent an essential part of aerosol mass in the atmosphere and while their contribution to atmospheric radiation is rather moderate. Therefore, the characterization of super coarse aerosols is very challenging while they are responsible for sizable overall contributions in aerosol effects environment and climate dynamics. Indeed, AERONET network, that arguably can be considered as the most comprehensive source of information about ambient columnar aerosol properties does not consider aerosol particles with radius larger than 15 microns. In contrast, most chemical transport models do consider super course particles and a number of in situ campaigns have reported the presence of such particles. This presentation describes efforts to test and evaluate the capabilities and limitations of detecting the super coarse dust particles from AERONET like measurements. It also considers possibilities to detect such particles using other remote sensing methods including lidar active observation and measurements in IR spectral range. Several modifications of the retrieval approaches that allow for optimizing remote sensing of super coarse ambient aerosol are proposed and discussed.

The assimilation and reanalysis efforts have essentially advanced in last decades benefiting from the progress in both modeling and observations. However, there is an essential gap between aerosol modelling approaches used in remote sensing algorithms and in the global climate models. This complicates the utilization of the remote sensing data in the reanalysis for constraining global climate models and improving their forecast capabilities. This gap also has a restraining effect on the evolution of remote sensing. For example, the predicted or climatological aerosol information from global climate models (e.g., aerosol type, vertical profiles, etc.) can be a valuable source of a priori information to constrain the retrievals, while some inconsistences in aerosol representations complicate the use of this information in the remote sensing algorithms.The presentation discusses the harmonization and aligning aerosol modeling assumptions used in CAMS and MERRA-2 model and aerosol retrieval from multi-angular polarimetric data realized by the GRASP/Components approach. The GRASP/Components approach uses quite similar aerosol modeling concept to that of aerosol transport models. Indeed, it considers aerosol as a mixture of aerosol components with known index of refraction and derives particle size distribution and fractions of different aerosol components. The aerosol components used in CAMS and MERRA-2 and were compared with GRASP and analyzed by outlining possible advantages and shortcoming in both concepts. As a result, several modifications were recommended for both models and GRASP in order to improve consistency of two approaches. It is expected that once the suggested modifications are realized the aerosol parameters derived from remote sensing are more adapted for the assimilation of the observation and the use of model forecast data (e.g., aerosol vertical distribution, changes in aerosol properties due to humidity variations, etc.) are straight forward for constraining the remote sensing retrieval.

The presentation discusses the Multi-term Least Square Method (LSM) as a methodological platform for realizing of the multi-instrument synergy. As discussed by Dubovik et al. (2021), the Multi-term LSM has been used to develop complex inversion algorithms for a number of years and have been successfully applied to aerosol retrievals from diverse satellite, ground-based and laboratory measurements. Theoretically, the approach unites the advantages of a variety of approaches and to provide transparency and flexibility in development of efficient retrievals. It provides a methodology for using multiple a priori constraints to atmospheric problems. One of the most important practical features of the approach is that it allows for synergy processing of observations that are not fully coincident nor fully co-located. Specifically, synergy of such observation can be realized following the multi-pixel approach (Dubovik et al., 2011), when the large groups of satellite observations (pixels) are inverted simultaneously. By processing observations from multiple pixels together, the retrieval efficiently incorporates prior knowledge about the temporal and spatial variability of the retrieved parameters.Indeed, while the synergy of not coincident or not co-located observation is less intuitive, it is very promising. Whereas the fusion of co-incident multi-angular polarimeter and lidar observations is considered as efficient approach, in practice the coincidence of such observations can be limited. For example, the trajectories of currently operating EarthCARE and PACE have very limited overlaps, therefore the possible synergy product of these two satellites can only be very sparse. In contrast, the synergy of not fully coincident or co-located observations can be applied always for combining any observations from operating satellites with different trajectories. Based on our current experience such synergy, realized using multi-pixel approach, allows for substantial improvement of aerosol characterization due to two phenomena: (i) propagation of superior information about aerosol details from more sensitive observations to less sensitive, and (ii) overall increase of observations volume of the same aerosol event in different times and locations. The benefits of such synergy of non-coincident observations have been demonstrated in the framework of ESA SYREMIS project (https://www.grasp-earth.com/portfolio/syremis/), where the synergetic multi-instrument retrieval approach was developed for characterizing aerosol and surface properties using different combinations of S-3A, S-3B, S-5p, polar and HIMAWARI geo observations. It was shown that realized methodology helped the information from polar satellite to propagate geo retrieval and made possible the retrieval of AE and SSA for the pixel with HIMAWARI observations reasonable accuracy, while processing these observations separately does not provide these parameters. In these regards, the combined processing of PACE, EarthCARE and HIMAWARI could also be used to provide enhanced aerosol global product.Dubovik, O., M. Herman, A. Holdak, et al., “Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations”, Atmos. Meas. Tech., 4, 975-1018, https://doi.org/10.5194/amt-4-975-201, 2011.Dubovik, O., D. Fuertes, P. Litvinov, et al. , “A Comprehensive Description of Multi-Term LSM for Applying Multiple a Priori Constraints in Problems of Atmospheric Remote Sensing: GRASP Algorithm, Concept, and Ap-plications”, Front. Remote Sens. 2:706851. doi: 10.3389/frsen.2021.706851, 202

Abstract Exploring various properties of aerosols can help to better understand global climate changes, emissions, and environment. In this study, a synergy observation experiment from sun photometer and Lidar was carried out to reveal aerosol optical properties and direct radiative effect (DARE) in Central China from the novel perspective of aerosol components. Our results showed that the annual mass concentration of black carbon (BC) was low (2.49 mg/m2), but having large heating effect with the DARE of 9.27 W/m2 at the top of atmosphere. The brown carbon was found highest in summer (0.52 mg/m2) and its annual DARE was 0.10 W/m2, close to the average of China. Additionally, retrieved columnar concentration of BC had the same magnitude with the MEERA‐2 product, and showed better results at the surface (R = 0.56) because the considering of aerosol vertical profiles. This study showed the significance of exploring expanded aerosol information from observations.

The presentation discusses the approaches to model aerosol properties realized in GRASP (Generalized Retrieval of Aerosol and Surface Properties) algorithm (Dubovik et al., 2021). GRASP algorithm is developed based heritage of earlier efforts on the AERONET retrieval development (Dubovik and King, 2000, Dubovik et al., 2000) with idea to use the same algorithm for different applications. Thus, at present, GRASP is a versatile algorithm that could be applied diverse observations including laboratory, passive and active remote sensing measurements from ground and space. All those observations have different sensitivities to details of aerosol properties and, therefore, analysis of each type of observations requires adequate approach to model aerosol properties. For example, aerosol model used for interpretation of AERONET observations includes many more paraments than aerosol model used for interpretation of satellite observations from single view satellite imager such a MODIS or OLCI. At the same time, the aerosol models used for different observations should be consistent and compatible. Following this concept, GRASP aerosol forward model can be adequately adjusted for applications to very different observations ranging from in situ nephelometers, ground-based AERONET radiometers to satellite polarimetric and radiometric imagers, as well as, to ground-based and satellite lidar observations. The aerosol model describes all aerosol properties: size distribution, complex index of refraction, or composition, particle shape, rules of for several component mixing, vertical profile description, etc. The presentation overviews historical evolution of all details of aerosol model, the assumptions made for adaptation to different observations of different types of and the rational used for the current specific design od aerosol model. Finaly, the comparative analysis will be done to outline the differences and agreements with other common approaches used in aerosol remote sensing. Dubovik, O., A. Smirnov, B. N. Holben, etc., “Accuracy assessments of aerosol optical properties retrieved from AERONET Sun and sky-radiance measurements”, J. Geophys. Res.,105, 9791-9806, https://doi.org/10.1029/2000JD900040, 2000.Dubovik, O. and M. D. King, “A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements”, J. Geophys. Res., 105, 20,673-20,696, https://doi.org/10.1029/2000JD900282, 2000.Dubovik, O., D. Fuertes, P. Litvinov, et al. , “A Comprehensive Description of Multi-Term LSM for Applying Multiple a Priori Constraints in Problems of Atmospheric Remote Sensing: GRASP Algorithm, Concept, and Applications”, Front. Remote Sens. 2:706851. doi: 10.3389/frsen.2021.706851, 2021.

Atmospheric aerosol is one of the main drivers of climate change. Currently, a number of different satellites in Earth orbit are dedicated to aerosol studies. Due to limited information content, the primary aerosol product of most satellite missions is AOD (Aerosol Optical Depth), while the accuracy of aerosol size and type retrieval from spaceborne remote sensing still requires improvement. Combining measurements from different satellites increases their information content and, therefore, can provide new possibilities for retrieving an extended set of both aerosol and surface properties. In this paper, we present the physical basis and concept of the recently developed synergetic approach for aerosol and surface characterization using diverse spaceborne measurements (hereinafter SYREMIS (SYnergetic REtrieval from Multi-MISsion instruments) approach). The approach was implemented in the GRASP (Generalized Retrieval of Atmosphere and Surface Properties) algorithm and has been tested on two types of synergetic measurements: (i) synergy of polar-orbiting satellites (LEO + LEO synergy combining Sentinel-5P/TROPOMI, Sentinel-3A/OLCI, and Sentinel-3B/OLCI instruments), (ii) synergy of polar-orbiting and geostationary satellites (LEO + GEO synergy based on Sentinel-5P/TROPOMI, Sentinel-3A/OLCI, Sentinel-3B/OLCI, and Himawari-8/AHI instruments). On the one hand, such a synergetic satellite constellation extends the spectral range of the measurements. On the other hand, it provides unprecedented global spatial coverage with high temporal resolution, which is crucial for a number of climate studies. It is shown that the SYREMIS/GRASP approach facilitates the transfer of information content from instruments with richer information content to those with lower one. This results in substantial enhancements in aerosol and surface characterization for all instruments within the synergy.

Big variety of different satellites on Earth orbit are dedicated to aerosol studies. However, due to limited information content, the main aerosol products of the most of satellite missions is AOD while the accuracy of aerosol size and type retrieval from space-borne remote sensing still requires essential improvement. . The combination of measurements from different satellites essentially extends their information content and, therefore, can provide new possibility for much better retrieval of extended set of both aerosol and surface properties.In the frame of ESA SYREMIS project GRASP algorithm was adapted for synergetic retrieval from combined space-borne instruments: (i) synergy from polar-orbiting (LEO) satellites (in particular, synergy of Sentinel-5p/TROPOMI, Sentinel-3A, -3B/OLCI instruments) and (ii) synergy of LEO and geostationary (GEO) satellites (in particular, synergy of Sentinel-5p/TROPOMI, Sentinel-3A, -3B/OLCI and HIMAWARI/AHI sensors). On one hand such synergy constellation extends the spectral range of the measurements. On another hand it provides unprecedented global spatial coverage with several measurements per day which is crucial for global climate studies and air-quality monitoring.In this talk we discuss physical basis and concept of the LEO-LEO and LEO-GEO synergies used in GRASP retrieval. It will be demonstrated that SYREMIS/GRASP synergetic approach allows transition of information from the instruments with richest information content to the instruments with lower one. This results in increased performance of AOD, aerosol size and absorption properties retrieval and more consistent surface BRDF characterization.

During the last years there have been a great advance in the development of satellite missions for Earth Observation. Most of them rely on passive remote sensing measurements, particularly on multiwavelength multi-angular polarimetry measurements (MAP). Upcoming missions such as Sentinel-5 will also deploy MAP and there are even private initiatives to expand space MAP measurements. Although MAP measurements have been proven to be ideal for expanding our knowledge in aerosol optical and microphysical properties (Dubovik et al., 2019), they provided very limited information of the aerosol properties vertically-resolved. On the other hand, multiwavelength lidar measurements are capable of providing accurate aerosol vertical profiles but face with limitations in the retrieval of aerosol optical and microphysical properties because of the limited information content of the stand-alone lidar measurements (Perez-Ramirez et al., 2019). Here we explore the potentiality of inverting aerosol microphysical properties vertically-resolved by combining in the Generalized Retrieval of Atmosphere and Surface Properties (GRASP – Dubovik et al., 2021) space lidar and polarimetry measurements.We present extensive simulations of aerosol optical and microphysical properties vertical-profiles retrievals combining multiwavelength MAP and lidar measurements in GRASP, with the enhanced capability of differentiating between aerosol fine and coarse mode properties. The retrieval is pushed forward by trying to obtain 22 bins size distribution, similar to those provided by AERONET. In the simulations different mixtures of fine and coarse mode were used, varying refractive indexes from low to high absorption. We have used the HARP-like polarimetry configuration that uses the heritage of POLDER space polarimetry and is deployed in the NASA PACE mission. For lidar measurements, multiwavelength configurations are tested, from single backscattering measurements to adding additional extinction measurements. Our results show full capacity of GRASP to retrieve aerosol properties vertically-resolved differentiating between fine and coarse properties, although the more accurate results are obtained when using all lidar information. However, we found out that optimized retrieval needs of constraining surface properties, particularly because of the impact of BPDF in coarse mode retrieval. Limitations in surface retrievals can be solved with the multi-pixel approach in GRASP when applied to real missions. Finally, we present case-study of synergy retrievals from airborne measurements obtained during NASA field campaigns when AirHARP + lidar flew together. The results of the simulations serve as baseline for future space mission that will combine space lidar + polarimetry or to the synergy of different satellite missions.ReferencesDubovik, O., et al., 2019: Polarimetric remote sensing of atmospheric aerosols: instruments, methodologies, results, and perspectives. J. Quant. Spectrosc. Radiat. Transfer, 224, 474-511,Dubovik, O, et al., 2021: A comprehensive description of multi-term LSM for applying multiple a priori constraints in problems of atmospheric remote sensing: GRASP algorithm, concept and applications. Front. Remote. Sens., 2, 706851.Perez-Ramirez, D, et al., 2019: Retrievals of aerosol single scattering albedo by multiwavelength lidar measurements: Evaluations with NASA Langley HSRL-2 during DISCOVER-AQ field campaigns. Remote. Sens. Environ., 222, 144-164.

This research aims to estimate long-term aerosol radiative effects by combining radiation and Aerosol Optical Depth (AOD) observations in Barcelona, Spain. Aerosol Radiative Forcing and Aerosol Forcing Efficiency (ARF and AFE) were estimated by combining shortwave radiation measurements from a SolRad-Net CM-21 pyranometer (level 1.5) and AERONET AOD (level 2), using the direct method. The shortwave AFE was derived from the slope between net solar radiation and AOD at 440, 675, 879, and 1020 nm, and the ARF was computed by multiplying the AFE by AOD at six solar zenith angles (20°, 30°, 40°, 50°, 60°, and 70°). Clear-sky conditions were selected from all-skies days by a quadratic fitting. The aerosol was classified to investigate the forcing contributions from each aerosol type. The aerosol classification was based on Pace and Toledano’s thresholds from AOD vs. Ångström Exponent (AE). The GRASP inversions were performed by combined AOD, radiation, Degree of Linear Polarization (DoLP) by zenith angles from the polarized sun–sky–lunar photometer and the elastic signal from the UPC-ACTRIS lidar system. The long-term AFE and ARF are both negative, with an increasing tendency (in absolute value) of +24% (AFE) and +40% (ARF) in 14 years. The yearly AFE varied from −331 to −10 Wm−2τ−1, and the ARF varied from −64 to −2 Wm−2, associated with an AOD (440 nm) from 0.016 to 0.690. The three types of aerosols on clear-sky days are mixed aerosols (61%), desert dust (10%), and urban/industrial-biomass burning aerosols (29%). Combined with Gobbi’s method, this classification clustered the aerosols into four groups by AE analysis (two coarse- and two fine-mode aerosols). Then, the contribution of the aerosol types to the ARF showed that the desert dust forcing had the largest cooling effect in Barcelona (−61.5 to −37.4 Wm−2), followed by urban/industrial-biomass burning aerosols (−40.4 to −20.4 Wm−2) and mixed aerosols (−31.8 and −24.0 Wm−2). Regarding the comparison among Generalized Retrieval of Atmosphere and Surface Properties (GRASP) inversions, AERONET inversions, and direct method estimations, the AFE and ARF had some differences owing to their definitions in the algorithms. The DoLP, used as GRASP input, decreased the ARF overestimation for high AOD.

Satellites are required for the global measurement of aerosol cloud-mediated radiative forcing, but satellite retrievals of aerosols and cloud properties still have challenges to overcome.

This paper is the second part of companion papers describing the development of GRASP approach for aerosol and surface retrieval from Sentinel-5P/TROPOMI. Here we focus on the S5P/TROPOMI GRASP aerosol and surface products global validation and systematic intercomparison with other products from independent instruments and algorithms. Specifically, we have validated the S5P/TROPOMI GRASP, Suomi-NPP/VIIRS DB and MODIS/TERRA DT + DB aerosol products with the ground-based AERONET referenced measurements using the same methodology and intercompare the validation results. In addition, the global pixel-to-pixel intercomparisons of the aerosol products (AOD, fine/coarse mode AOD and SSA) are performed over different surfaces, i.e., ocean and land surface with different NDVIs. Besides, we compared the S5P/TROPOMI GRASP, MODIS MCD43 surface BRDF/albedo as well as OMI, GOME-2 and SCIAMACHY Lambertian-Equivalent Reflectivity (LER) albedo climatology developed by Royal Netherlands Meteorological Institute (KNMI) with the surface reference dataset generated based on the synergetic retrieval of AERONET and S5P/TROPOMI measurements. Finally, the intercomparisons of the surface BRDF and albedo datasets were performed globally at the UV, VIS, NIR and SWIR parts of the spectrum. Overall, generally good agreement was observed between independent aerosol and surface datasets with a high percentage of pixels satisfying the Optimal and Target requirements. We would emphasize two advantages for TROPOMI/GRASP aerosol and surface products: (i) it provides spectral AOD together with detailed aerosol properties, such as fine/coarse mode AOD, spectral AAOD and SSA at UV, VIS, NIR and SWIR wavelengths, which are important for constraining aerosol environmental and climate effects; (ii) the TROPOMI/GRASP aerosol and surface products are globally retrieved simultaneously in a fully consistent manner.

Atmospheric aerosols have strong impact on climate, environment, and health. To account correctly for such impact, extended aerosol characterization, including spectral Aerosol Optical Depth (AOD), Angstrom Exponent (AE), spectral Single Scattering Albedo (SSA) etc., are required to be derived globally from space-borne observations. Together with the aerosol, the Earth's surfaces are an important component of climate system, reflecting and absorbing solar and atmospheric radiation and being sources of emission of different natural aerosol, for example, sea-salt, mineral dust or organic aerosol.Since the beginning of space-borne atmospheric observation it was recognized that the most comprehensive extended aerosol and surface characterization can be achieved from multi-angular polarimetric measurements. In this paper, we show that the extended aerosol characterization can be obtained even from single viewing radiance only satellite measurements when several crucial conditions are fulfilled both for the observations and retrieval algorithm: (i) wide spectral range (for example, covering UV, VIR, NIR and SWIR spectra) providing rich spectral information about aerosol and surface; (ii) wide swath of measurements ensuring frequent overpassing over the same ground pixel to account for the different temporal variability of aerosol and surface properties as well as for angular dependence of surface reflectance; (iii) applied algorithm should be able to treat multi-temporal and multi-spatial observation accounting for spatial and temporal dependencies of aerosol and surface characteristics.The new possibilities of retrieval of aerosol and surface properties are investigated by applying the advanced GRASP (Generalized Retrieval of Atmosphere and Surface Properties) algorithm to the space-borne S5P/TROPOMI observations. The most optimal for these purposes forward and inversion approaches are discussed, and the quality of retrieved aerosol and surface properties is evaluated. The possibilities of TROPOMI/GRASP approach for aerosol extended characterization are demonstrated on several aerosol events including dust storms, biomass burning and anthropogenic aerosol pollution outbreaks in worldwide locations.