Aerosols and clouds play a major role in the Earth Climate systems, while the quantification and clear understanding of their variabilities, interactions and feedbacks remain a great challenge. In particular, aerosols strongly impact the energy budget by direct modification of solar and infrared radiation, alteration of cloud properties and their formation processes as well as the thermodynamic properties of the atmosphere. Aerosols are also the most harmful air pollutant, being responsible of several millions of premature deaths worldwide each year. Even though diverse observation and modelling approaches of aerosols exist, numerous unknowns remain concerning the chemical and physical mechanisms that affect them, their vertical redistribution in the atmosphere, the quantification of their environmental impacts and their interactions with clouds and convective processes.

In order to tackle these major environmental issues at global scale, a new spaceborne Atmosphere Observing System (AOS) has been conceived as an international cooperation between NASA from USA, CNES from France, JAXA from Japan, CSA from Canada and ASI from Italy. This mission is built as a constellation of several satellites following two orbits, a polar orbit with global coverage in the continuity of the A-Train constellation and an inclined designed to document the diurnal variation of convection in the Tropics and mid-latitudes. They satellites will carry new generation active and passive instruments for sounding aerosols, clouds, convection, and precipitation, including an advanced multiwavelength lidar in tandem with a multi-angular polarimeter, whose launching period is planned for 2030.

In the current presentation, we will provide an overview of French efforts for the innovative characterization of aerosols and its interactions with clouds  for preparing the scientific exploitation of AOS. They gather relevant contributions from 8 French scientific laboratories: LISA, LOA, LATMOS, CNRM, LAERO, LACy, CERI EE and LSCE and a French industrial partner: GRASP-SAS. These efforts are threefold: (i) the development of innovative French aerosol satellite products based on AOS observations, (ii) suborbital measurements for feeding both the aerosol products and conceiving a synergetic exploitation with AOS and (iii) synergism with chemistry-transport models. The AOS aerosol observations will provide a new quantification of the vertical profile of aerosol concentration simultaneously for different particle types and chemical species. This information will be derived from lidar only and the synergism of lidar and polarimeter measurements using a so-called GRASP retrieval approach. Additional products aim the quantification of cloud condensation nuclei for studying aerosols/cloud interactions. The suborbital contribution will characterize aerosol optical, microphysical, and chemical properties from airborne, ground-based from several French sites and laboratory instrumentation. While documenting aerosols properties for different aerosol types and species, they provide a scientific framework for studying complex interactions such as the impact of aerosols on convective activity in specific regions. This is the case of the BACCOPA French field campaign aiming the studying of the impact of biomass burning aerosols emitted from Central Africa on convective activity. Finally, synergetic approaches with chemistry transport-models aim the development of data assimilation methods of AOS measurements and the use of these last ones for evaluating their numerical simulations.

How to cite: Cuesta, J., Lopatin, A., Flamant, C., El Amraoui, L., Ferreira De Brito, J., Mallet, M., Sicard, M., Turquety, S., Di Biagio, C., Formenti, P., Khaykin, S., Xueref-Remy, I., Gros, V., Noël, V., Petit, J.-E., Torres, B., Qayyum, F., and Merdji, A.: Overview of French efforts for the innovative characterisation of aerosols and cloud interactions with the future Atmosphere Observing System, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14129, https://doi.org/10.5194/egusphere-egu25-14129, 2025.

The latest range of CMIP6 model dust simulations shows a greater diversity than previous generations of models in terms of dust emission, deposition, burden and dust optical depth (DOD) (Zhao et al., 2022). Validation of dust models is crucial for understanding the impact of dust on climate and climate change, as well as for quantifying socio-economic and health impacts of dust.

While models (and reanalyses) mostly provide output in terms of mass, satellite observations used for model validation are optical measurements. Thus we require good knowledge of the dust mass extinction coefficient (MEC) to successfully validate our dust models. However, the MEC is intricately linked to the dust size distribution, fraction of coarse particles and composition, all of which may vary regionally, in the vertical and in time.

This presentation will provide a perspective on some recent efforts exploring the challenges in model validation relating to dust size, composition, optical depth and dust mass loading in climate models (Zhao et al., 2024; Ratcliffe et al., 2024), reanalyses (Ryder et al., 2024), space-borne lidar, space-borne optical depth and in-situ measurements, demonstrating the critical importance and uncertainty of the dust MEC.

References

Ratcliffe, N.G., Ryder, C.L., Bellouin, N., Woodward, S., Jones, A., Johnson, B., Wieland, L.-M., Dollner, M., Gasteiger, J., Weinzierl, B. Long range transport of coarse mineral dust: an evaluation of the Met Office Unified Model against aircraft observations, Atmos. Chem. Phys., 24, 12161–12181, https://doi.org/10.5194/acp-24-12161-2024, 2024.

Ryder, C.L., Bézier, C., Dacre, H., Clarkson, R., Amiridis, V., Marinou, E., Proestakis, E., Kipling, Z., Benedetti, A., Parrington, M., Rémy, S., Vaughan, M., Aircraft Engine Dust Ingestion at Global Airports, https://doi.org/10.5194/nhess-24-2263-2024, 24, 7, Natural Hazards and Earth System Science, 2024.

Zhao, A., Ryder, C.L., Wilcox, L., How well do the CMIP6 models simulate dust aerosols?, Atmos. Chem. Phys., 22, 2095–2119, https://doi.org/10.5194/acp-22-2095-2022, 2022.

Zhao, A., Wilcox, L., Ryder, C.L., The key role of atmospheric absorption in the Asian Summer Monsoon response to dust emissions in CMIP6 models, Atmos. Chem. Phys., https://doi.org/10.5194/acp-24-13385-2024, 2024.

How to cite: Ryder, C., Ratcliffe, N., Zhao, A., Bellouin, N., Wilcox, L., Dacre, H., Bézier, C., Amiridis, V., Marinou, E., Proestakis, E., Weinzierl, B., Woodward, S., Johnson, B., and Jones, A.: The Mass Extinction Coefficient for Dust: challenges in the link between mass and optical properties for models, reanalyses, in-situ and satellite observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3484, https://doi.org/10.5194/egusphere-egu25-3484, 2025.

With the launch of EPS-SG in 2025, EUMETSAT will operate a space platform hosting a series of instruments among which VII, 3MI, IASI-NG and UVNS (Sentinel-5). The potential of a synergistic approach combining 3 instruments has been already demonstrated with the release of the EPS/PMAp product, operational as a Near-Real-Time aerosol product since 2014. After a colocation of all the measurements provided by the instruments, the synergistic retrieval becomes possible. For EPS-SG, an important step forward will be made with the polarimeter 3MI which will allow the provision of many aerosol properties. The synergistic use of the other instruments will contribute to improve this characterisation from 3MI. The spectral extension to UV and TIR, the sub-pixel information, but also the use of absorption bands. The pre-design of this synergistic product will be presented.

How to cite: Jafariserajehlou, S. and Fougnie, B.: Multi-sensor Aerosol Product from EPS-SG – Consideration for the Operational Aerosol Product, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16773, https://doi.org/10.5194/egusphere-egu25-16773, 2025.

In this work, we present the use of random shape mixtures of irregular hexahedrals and spheroids to simulate the spectral dependence of lidar-derived dust depolarization ratio and lidar ratio in 3 wavelengths traditionally used in aerosol research: 355, 532 and 1064nm.

Vertically-resolved polarimetric remote sensing provides a comprehensive understanding of atmospheric dust properties and its’ effects on radiation, weather and climate. Optical property profiles derived from polarimetric lidar observations such as the lidar ratio (Sp) and the depolarization ratio (dp), are sensitive to the particles’ morphology. However, in order to extract particle microphysical properties from these observations, accurate modelling of dust scattering properties is required. Dust particles appear to be highly-irregular and while complex shape models have been developed to describe them (e.g. Gasteiger et al. 2011), the scattering calculations are expensive in terms of computational power, which limits their applicability.

Thus, in most cases dust particle shapes are modelled using simplified representations such as spheroids. Spheroid shape mixtures have been demonstrated to successfully reproduce the angular dependence of light scattering from dust aerosols, nevertheless deviations are observed, particularly close to backscattering angles (Dubovik et al., 2006). Recent developments show that irregular hexahedral ensembles can better reproduce the measured dust lidar-relevant properties (Saito & Yang, 2021; Saito et al., 2021), however it is still challenging to reproduce their spectral dependence.

In all cases, additional assumptions are made with respect to the distribution of the different particle shapes considered in the ensemble (i.e. a shape distribution).

Herein we explore a different pathway, using random shape mixtures of irregular hexahedrals and spheroids to simulate the spectral dependence of lidar-derived dust dp and Sp. Since the considered particle shapes are not realistic, we do not constrain the simulations with measured shape distributions, but rather allow the different particle shapes to vary randomly in the mixtures. For the simulations we utilize the MOPSMAP (Gasteiger & Wiegner, 2018) and the TAMUdust2020 (Saito & Yang, 2021; Saito et al., 2021) scattering databases.

The size distributions and complex refractive indices considered for the calculations, are provided by AERONET retrievals collocated with the lidar observations, and height-resolved airborne in-situ data, acquired during the ASKOS-ESA campaign, implemented in Mindelo, Cabo Verde (Marinou et al., 2023). The simulated d_p and S_p for dust particles are evaluated against multi-wavelength polarization lidar data from ASKOS and lidar-derived climatological values.

As an independent consistency check of the simulation results, the derived random spheroids/hexahedral mixtures are utilized in radiative transfer calculations to simulate multi-wavelength sky-radiances from AERONET almucantar sequences. More specifically, the sun-photometer observational geometry is considered for two cases: i) assuming the spheroid shape distribution used in AERONET (Dubovik et all, 2006) and ii) assuming the random spheroids/hexahedral mixture found to better reproduce the lidar data. The modelled sky radiances are then compared to the co-located sun-photometer measurements.  

First results show that the random hexahedral/spheroid shape mixtures can accurately reproduce the spectral dependence of d_p and S_p for a selected dust case study of ASKOS, while the results are also within the uncertainty of the corresponding climatological lidar data.

How to cite: Gialitaki, A., Tsekeri, A., O’Callaghan, M., Kouklaki, D., Papachristopoulou, K., Kezoudi, M., Papetta, A., Marenco, F., Kandler, K., Aryasree, S., Eknayan, M., and Amiridis, V.: Introducing random mixtures of irregular hexahedrals and spheroids to reproduce polarimetric lidar observations of desert dust, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11446, https://doi.org/10.5194/egusphere-egu25-11446, 2025.

In order to solve the problem of insufficient monitoring capabilities of water vapor transport (WVT) induced by low-level jets (LLJs), which restricts the improvement of regional extreme rainfall forecasting capabilities, the atmospheric water vapor as one of the key variables to monitor WVT will be synergistically estimated through ground-based, airborne and space-borne multi-platform including ground-based GNSS, microwave radiometer, lidar, radiosonde, high-altitude unmanned aerial vehicles and Fengyun satellites and so forth. The estimates of atmospheric water vapor from different platforms will be compared to clarify the advantages and disadvantages of different monitoring methods, observation error characteristics and optimal applicable conditions. The GNSS tomography method will be developed to retrieve three-dimensional water vapor distribution. The observation network and observation mode will be optimized and the technology to synergistically monitor atmospheric water vapor through multiple instruments will be developed. In addition, the methods to combine and fuse the retrievals of water vapor from multi-platform will be developed. The fusion datasets of water vapor will be established. This datasets and wind datasets provided by another program will be used to compute integrated water vapor transport induced by LLJs. To sum up, this study would be of great help to advance LLJs monitoring and improve the accuracy of regional extreme rainfall forecasts induced by LLJs.

How to cite: Liang, H., Zhang, P., Zhou, L., Zhao, P., Bu, Z., and Mao, J.: Estimating atmospheric water vapor synergistically through ground-based, airborne and space-borne observations for monitoring water vapor transport induced by low-level jets during regional extreme rainfall events, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5381, https://doi.org/10.5194/egusphere-egu25-5381, 2025.

Aerosols affect climate in two main ways: directly, through scattering and absorption of solar radiation, and indirectly, through affecting cloud formation and cloud properties. Combined, these effects result in a net cooling, partially offsetting the warming caused by greenhouse gases (GHGs). While there is consensus about the existence of this cooling effect, its magnitude remains uncertain. This is problematic; as anthropogenic aerosol emissions decrease, we expect the cooling effect to diminish, leading to an enhanced warming effect from GHGs in the near future. Therefore, the accuracy of future warming projections strongly depends on our understanding of aerosols.

In particular, the hygroscopicity (i.e., efficiency of water uptake) of aerosols is a poorly understood property, yet highly influential on both cloud droplet nucleation capacity and light scattering. Typically, aerosols are complex mixtures of particles which themselves are a mixture of various materials, some of which are hydrophilic, and others hydrophobic. The distribution of these species, both within and among aerosol particles, is a key factor determining the effect of water uptake. As a result, different model treatments of aerosol compositions produce widely varying radiative forcing estimates. This strongly contributes to the uncertainty on the aerosol cooling term.

Global hygroscopicity data is crucial to inform model choices and thereby improve forcing estimates, except the available data is sparse and limited. Our goal is to address this gap by compiling polarimetric satellite observations from POLDER-PARASOL (for 2006-2010) and SPEXone-PACE (2024+) into the first ever global climatology of aerosol hygroscopicity. We use the RemoTAP algorithm to retrieve the aerosol refractive index, among other properties, from the multi-angle polarimeters. Through comparison of the retrieved refractive index to the known refractive indices for dry material and of water, a volume fraction of water in the aerosol is derived.

Given the novelty of our approach, validation of the retrievals is of particular importance. First, we compare the satellite retrievals to ground-based measurements such as refractive indices derived from AERONET observations. Furthermore, to validate our method of deriving the water fraction from the refractive index in general, we compare the retrievals to aerosol water fractions derived from ground-based in-situ nephelometer measurements of particle growth in response to changes in humidity, combined with ambient relative humidity measurements.

Another fundamental pillar of this validation is the PACE-PAX campaign, which was conducted in September 2024 with the express purpose of validating PACE and EarthCARE results. The campaign involved a high-altitude aircraft serving as a direct satellite proxy, which included the SPEX airborne instrument. Furthermore, one low-altitude aircraft gathering in-situ measurements, two boats, and a glider participated in the campaign. Observation targets included AERONET stations and satellite overpasses, providing ample opportunities for intercomparison between high-altitude aircraft observations and ground-based, aircraft in-situ, and satellite measurements.

We discuss our validation strategies and results, demonstrating the accuracy and limitations of our approach

How to cite: Mens, J., van Diedenhoven, B., and Hasekamp, O.: Satellite retrievals of aerosol water uptake and their validation using ground-based, in-situ, and airborne campaign data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10732, https://doi.org/10.5194/egusphere-egu25-10732, 2025.

The influence of aerosols on climate is determined not only by their global distribution but also by their specific composition. Knowledge of the aerosol component distribution on a global scale is important (among other factors) for the radiation balance and the hydrological cycle due to the different influence of different components on the direct and indirect aerosol effect. Ideally, the component distribution should be known globally. For this reason, we propose a novel approach to derive the components using satellite observations.  Since no single instrument can provide a comprehensive analysis, we integrate data from three satellite-based instruments with complementary information content to achieve a synergistic aerosol retrieval. Our approach utilizes measurements with varying observational characteristics, including different spectral ranges (UV, VIS, thermal IR) and viewing geometries (nadir and oblique). The instruments involved are the dual-view SLSTR (Sea and Land Surface Temperature Radiometer) aboard Sentinel 3A and 3B, the Infrared Atmospheric Sounding Interferometer (IASI), and the Global Ozone Monitoring Experiment-2 (GOME-2), both on METOP A/B/C. The data are averaged onto a common grid of 40x80 km², temporally aligned within a 60-minute window, and subjected to cloud masking.

This study aims to extract the total Aerosol Optical Depth (AOD) as well as the AOD of major aerosol components from the satellite data using an optimal estimation framework. An information content analysis showed that an upper limit of up to 22 parameters (surface albedo at different wavelengths, surface temperature, Aerosol Optical Depth (AOD) and the AOD for up to 15 different aerosol components) with their uncertainties can be retrieved out of the combined dataset depending on the aerosol amount and the surface properties. For the a priori values of the retrieval parameters, we utilize climatological data: the GOME-2 surface LER database for albedo values, which contains Lambertian-equivalent reflectivity (LER), and climatological MERRA-2 reanalysis data for AOD and aerosol composition.

This combination of instruments thus has the potential to accurately ascertain aerosol composition and with this additional information to refine our understanding of their climate impact. In this study we show first promising results of the retrieval in different scenarios. 

How to cite: Stöffelmair, U., Popp, T., Vountas, M., and Bösch, H.: Satellite Aerosol Composition Retrieval from a Combination of three different Instruments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9642, https://doi.org/10.5194/egusphere-egu25-9642, 2025.

We present the “EarthCARE ATLID and MSI Instruments Synergy for Advanced Retrieval of Aerosol Vertical Profiles” (ECAMS) project, which aims to enhance the integration of passive and active observations by combining Level 1 (L1) data from EarthCARE and various imagers. This project focuses on aerosol retrieval through the fusion of L1 observations from lidar (ATLID) and imagers on EarthCARE (MSI) and PACE (SPEXone, HARP-2). This approach, though methodologically promising, presents significant technical challenges and requires substantial resources.

Atmospheric aerosols are major drivers of climate change and have significant impacts on human health. Global information on aerosol properties is primarily obtained from space-based measurements. Passive remote sensing involves spectral observations of top-of-atmosphere reflectance at various angles, providing data on aerosol quantity, particle size and morphology, with limited sensitivity to its vertical distribution. Conversely, active lidar observations excel in detecting aerosol vertical distribution but lidar stand-alone retrievals require assumptions about aerosol size and morphology, making collocated radiometric measurements crucial for their comprehensive interpretation.

Current methods for synergetic aerosol property retrievals mainly focus on ground-based active and passive observations and do not fully leverage recent advancements in lidar technology, such as high spectral resolution lidars (HSRLs). Moreover, existing methods lack the flexibility to integrate various lidar configurations with passive measurements for space-based observations. ECAMS aims to address these limitations by developing new methods for generating global aerosol vertical distribution products with improved accuracy, aiding climate model validation. The project’s synergetic retrieval approach uses highly optimized forward models (including aerosol and surface reflectance) and the statistical estimation framework of the open-source GRASP (Generalized Retrieval of Atmosphere and Surface Properties) software.

The ECAMS framework is designed for adaptability, enabling the synergistic processing of various active and passive satellite observations across different spatial, vertical, and spectral resolutions and ranges. It serves as platform for advancing remote sensing of atmospheric and surface structures, providing a virtual laboratory for diverse remote sensing research and applications.

One of the project’s objectives is to support and complement synergy developments in the context of ESA AIRSENSE project and its studies on aerosol-cloud interactions, in collaboration with the EC CleanCloud and CERTAINTY projects. Ongoing developments and results will be presented and discussed.

How to cite: Lopatin, A., Gialitaki, A., Li, C., Tsekeri, A., Tytgat, P., Rizos, K., Marinou, E., Amiridis, V., Dubovik, O., and Malina, E.: Advanced retrieval of aerosol vertical profiles using synergy of EarthCARE ATLID and passive spaceborne observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6160, https://doi.org/10.5194/egusphere-egu25-6160, 2025.

Atmospheric aerosols are tiny liquid and solid particles suspended in the air. They can scatter and absorb electromagnetic radiation, thus affecting the Earth’s radiative balance and climate. Additionally, aerosols can influence air quality, leading to respiratory and cardiovascular health problems.

To acquire information about the space-time variability of atmospheric aerosols and their optical and microphysical properties, various techniques are employed. In situ methods are typically performed at ground level, while remote methods use light to determine optical aerosol parameters.

This study focuses on the polar integrating nephelometer Aurora 4000 (Chamberlain-Ward and Sharp, 2011), which measures aerosol light scattering at different angles ranging from 10° to 170° across three wavelengths: 450, 525, and 635 nm. The main objective is to conduct sensitivity studies of the nephelometer by simulating theoretical signals for varying sets of optical and microphysical aerosol parameters. Thus examining the influence of various particle distribution parameters on light scattering measured by the nephelometer.

To simulate the nephelometer signals, the an advanced and versatile retrieval algorithm is employed. The Generalized Retrieval of Atmosphere and Surface Properties (GRASP) software (Dubovik et al., 2014; Lopatin et al., 2021) represents a state-of-the-art approach to integrating multi-source remote aerosol data, capable of retrieving atmospheric properties based on active (LIDAR) and passive (sun-sky photometer) remote techniques, as well as ground-based nephelometers.

Statistical parameters of aerosol size distributions (ASD) are derived from measurement data recorded by a ground-based system of aerosol size spectrometers, which includes a mobility particle size spectrometer (MPSS) and an aerodynamic particle size spectrometer (APSS). This combination allows for the determination of particle sizes within 10 nm to 10 μm. The synergy of these two instruments enables the acquisition of high-quality and wide range aerosol size distribution spectra.

Chamberlain-Ward, Steve, and Felicity Sharp. "Advances in nephelometry through the Ecotech Aurora nephelometer." The Scientific World Journal 11.1 (2011): 2530-2535.

Dubovik, Oleg, et al. "GRASP: a versatile algorithm for characterizing the atmosphere." SPIE Newsroom 25.10.1117 (2014): 2-1201408.

Lopatin, Anton, et al. "Synergy processing of diverse ground-based remote sensing and in situ data using the GRASP algorithm: applications to radiometer, lidar and radiosonde observations." Atmospheric Measurement Techniques 14.3 (2021): 2575-2614.

This work is supported by the National Science Centre grant number 2021/41/B/ST10/03660.

How to cite: Szymkowska, J., Szkop, A., and Pietruczuk, A.: Can bimodal aerosol size distribution be retrieved from AURORA4000 polar integrating nephelometer data?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16761, https://doi.org/10.5194/egusphere-egu25-16761, 2025.

With the launch of EPS-SG in 2025, a new era for a long-term operational Near-Real-Time provision of aerosol product is starting. If most of the potential for such a new remote sensing polarimetry has been demonstrated since 1996 with the 3 POLDER and PARASOL missions, the recent advance in term of retrieval but also analysis and exploitation of the data reveal more and more the potential. Indeed, polarimeters allow the observation of aerosols with a significantly improved information content which will feed the retrieval. On top of the aerosol optical thickness classically retrieved, an additional set of parameters characterizing the aerosol properties can now be derived such as the fraction of aerosol chemical components, which contributes to filling the gap between satellite retrieval and modelling community by going beyond aerosol typing, the new retrieved parameters also highlights the need for in-situ measurements to support on one hand the assumptions that could be needed in the algorithm (constraints, definition of aerosol chemical components…), and on the other hand contribute to the validation of the products. This set of new parameters is also stimulating new discussion about aerosol modelling.    

How to cite: Jafariserajehlou, S. and Fougnie, B.: New Space-borne Remote Sensing Capabilities Based on Polarimetry and the Implication in term of Aerosol Chemical Components and the needs for in-situ Measurements , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18328, https://doi.org/10.5194/egusphere-egu25-18328, 2025.

Trace gasses (e.g., NO₂, SO₂, HCHO) and aerosols play an important role in atmospheric chemistry and physics. They also negatively affect human and ecosystem health. Vertical distribution of these gasses in the lower troposphere (up to 3-4 km) is often monitored using MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) technique. Conversion of the trace gas slant absorption (from different viewing angles) into vertical concentration profile requires information about aerosol optical properties and their vertical distribution. Aerosol extinction coefficient profiles are retrieved from the MAX-DOAS measurements of absorption induced by oxygen collision complex (O₂O₂). The missing Information about columnar aerosol properties is typically taken, with some simplification, from the closest AERONET sun-sky photometer measurements.

This study investigates the possibility of simultaneous aerosol and tropospheric NO₂ concentration profile retrievals from synergetic ground-based observations by AERONET sun-sky photometer and Pandonia Global Network spectrometer. We consider standard AERONET sun-sky photometer measurements at 440, 675, 870, and 1020 nm, as well as, available additional observations at 340, 380, 500, and 1640 nm.

We use GRASP (Generalized Retrieval of Atmosphere and Surface Properties, Dubovik et al., 2021) to implement simultaneous retrieval of tropospheric NO₂ and vertical aerosol properties from multi-axis differential slant column densities of NO₂ and O₂O₂, and radiance measurements (almucantar and vertical scanning).

The GRASP algorithm was modified to include trace gases (NO₂, HCHO, O₂O₂) differential slant column density measurements and pseudo spherical correction of Earth curvature. In addition, a flexible gas absorption calculation based on optimized correlated k-distribution method (Momoi et al., 2022) was implemented. This presentation demonstrates advantages of synergetic observations for the aerosol and tropospheric NO₂ vertical profile retrievals in comparison to the current MAX-DOAS only inversion approaches.

Reference:

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.

Momoi, M., H. Irie, M. Sekiguchi, et al., “Rapid, accurate computation of narrow‑band sky radiance in the 940 nm gas absorption region using the correlated k‑distribution method for sun‑photometer observations”, Prog. Earth Planet. Sci., 9, 10, 1 - 22, https://doi.org/10.1186/s40645-022-00467-6, 2022.

How to cite: Momoi, M., Dubovik, O., Lind, E., Herreras-Giralda, M., Lapyonok, T., Lopatin, A., Lin, W., Rejano, F., Charlotte Stöckhardt, M., Kreuter, A., and Cede, A.: Simultaneous profiling of aerosol and tropospheric nitrogen dioxide from synergetic ground-based observations of sun-sky photometer and spectrometer, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11541, https://doi.org/10.5194/egusphere-egu25-11541, 2025.

As an operational user-driven Earth observation satellite agency, EUMETSAT is the reference European provider of Near Real Time (NRT - < 3h from the sensing time) Level 2 (L2) aerosol satellite observations from a constellation combining both Low Earth Orbit (LEO), with Metop / Sentinel-3 and EPS-SG, and GEOstationary (MSG & MTG). Primary users are operational air quality and climate services. Notably, for several years, EUMETSAT has closely interacted with the Copernicus Atmospheric Monitoring Service (CAMS) and provided expertise to support the uptake of all its observations into the modelling and assimilation processes.

With two multi-spectral optical sensors and observations acquired at a high spatial resolution at 10:00, Sentinel-3 is the main Copernicus mission mandated by the European Commission (EC) to provide a high quality of Aerosol Optical Depths (AODs) at global coverage during morning overpass time for the long future. As such, EUMETSAT is mandated since 2014 by its Member States and Copernicus to develop, enhance and ensure the Copernicus NRT Sentinel-3 Aerosol product. This is the 2^nd European product delivering Aerosol Optical (AOD) after Metop with PMAP (Polar Multi-sensor Aerosol optical Properties). Since 2020, it is derived from the OSSAR-CS3 (Optimized Simultaneous Surface Aerosol Retrieval for Copernicus Sentinel-3) algorithm, jointly specified & developed by EUMETSAT scientific experts & the Swansea University team led by Prof. Dr. Peter North (Chimot et al., 2021). Furthermore, EUMETSAT intensively works with the European Centre for Medium-Range Weather Forecasts (ECMWF) by exchanging the necessary expertise to support the future operational assimilation by the Copernicus Atmospheric Monitoring Service (CAMS), as done with PMAP.

The latest evolution, called Collection 3.1, compiles several major developments: 1) a sophisticated classification mask (called Naïve probabilistic) leading to enhanced coverage over all waters, and better cloud, snow, dust / ash, and dark vs. inland waters distinction, 2) more accurate 1^st guess of land vegetation reflectance, 3) revised underlight scattering caused by Ocean Colour features by using the Sentinel-3 Level 2 OLCI water reflectance, 4) improved constraints for bare soils in the dual-angular land model, and 4) a new Quality Indicator (QI) system integrated in the L2 product to guide further the users.

Based on lessons learned, EUMETSAT is now leading a major redesign of this algorithm, structured in two steps: first a Day-2 solely based on SLSTR, and a Day-3 intended as a NRT synergy (OLCI + SLSTR) to be based on the future Sentinel-3 NRT L1C under study and generated by EUMETSAT (De Bartolomei, 2014). As such, enhanced aerosol typing and further understanding of interaction with clouds are being investigated. This redesign also covers the development of Aerosol Layer Height (ALH) retrieval from the OLCI O2-A bands.

This presentation will summarise an extensive set of validation results including match-up with ground-based AERONET, inter-comparison of time series with MODIS/VIIRS from NASA and NOAA, and exchanges with the oeprational user community. Then, it will share the details of the plans of developments of the NRT Sentinel-3 Synergy and the major algorithm redesign items under specification, implementation, and testing.

How to cite: Chimot, J., Martins, E., Onderwater, J., Fougnie, B., Litvinov, P., and Dubovik, O.: Towards Advanced Sentinel-3 Near Real Time (NRT) L2 synergy aerosols capabilities - On-going Day 2 & Day 3 developments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18930, https://doi.org/10.5194/egusphere-egu25-18930, 2025.

In recent years, China’s air pollution control efforts have significantly reduced fine particulate matter (PM_2.5) concentrations. However, ozone (O₃) pollution has emerged as a key issue, becoming the second major pollutant affecting air quality. During certain periods, simultaneous high concentrations of PM_2.5 and O₃ lead to “dual-high” compound pollution. Understanding the dynamic evolution of these pollutants is essential for precise control strategies.

Existing observational data on PM_2.5 and O₃ are insufficient for research and applications. Ground-based monitoring stations provide temporally continuous data but have limited spatial coverage, while geostationary satellites offer wide spatial coverage but suffer from data gaps due to cloud interference, retrieval algorithm limitations, and the lack of nighttime observations. These challenges highlight the need for spatiotemporally continuous, all-weather data.

This study develops a high-precision retrieval model for near-surface PM_2.5 and O₃ concentrations, integrating AI algorithms with multispectral data from Himawari-8/9, reanalysis meteorological data, and geographic parameters. By incorporating the spatiotemporal autocorrelation of pollutants as a physical constraint, the model innovatively combines Gaussian smoothing adjustment and discrete cosine transform to create a data fusion framework. This framework generates seamless, all-weather datasets, addressing data gaps and correcting systematic biases in satellite retrievals.

Independent validation shows strong model performance, with hourly R² values exceeding 0.85. Using retrieval results from 2018 to 2023, we analyzed the spatiotemporal distribution of PM_2.5 and O₃ across four major urban agglomerations in China (Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta, and Central China) before, during, and after the COVID-19 outbreak. The findings reveal the effects of emission reductions and the post-pandemic pollution recovery.

This study demonstrates the potential of integrating remote sensing, AI, and mathematical modeling to achieve spatiotemporally continuous monitoring of PM_2.5 and O₃. It offers critical support for air pollution control and environmental policy evaluation.

How to cite: Zang, L., Su, Y., Zhang, Y., Mao, F., and Pan, Z.: Hourly Seamless Retrieval of Near-Surface PM2.5 and O3 Concentrations across China from 2018 to 2023, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20416, https://doi.org/10.5194/egusphere-egu25-20416, 2025.

The influence of aerosols on climate is determined not only by their global distribution but also by their composition. However, a large fraction of the development efforts for satellite-based aerosol retrievals has focused on inverting the total column aerosol optical depth (AOD) from different single instruments. As the information content of single instruments is smaller than necessary to retrieve a comprehensive quantification of all parameters of the atmospheric aerosol, there is a need for using auxiliary information to fill this gap (e.g. pre-defined optical aerosol properties, climatological vertical profiles, ...). Retrievals inverting further aerosol parameters from one instrument (e.g. Fine Mode or Dust AOD) depend on the auxiliary assumptions and on the sensitivity of the available instrument channels to the various aerosol properties. This leads to inconsistencies even between AOD results and certainly for additional parameters inverted from different sensors. Examples of consequential inconsistencies are the step in the AOD Climate Data Record built from subsequent pieces from similar instruments but with opposing viewing directions in the “dual view radiometer” series (A)ATSR(-2) and SLSTR) or the combined use of retrieval results from thermal with UV-VIS instruments at the same wavelength (usually 550 nm). For both examples, synergetic retrievals hold the potential to reduce the dependence on assumed properties and thus improve consistency.

It can be argued that each new generation of satellite instruments offers new additional capabilities so that the most recent era of multi-angle, multi-spectral polarimeters provide significantly larger information content and are thus able to invert more aerosol parameters. However, the wealth of satellite-based aerosol climate-relevant time series dating back to early 1980s comes from much simpler instruments. Here I see the largest field of synergetic retrievals, ranging from combinations of AVHRR with TOMS over combinations of MODIS and MISR or AATSR / MERIS / SCIAMACHY (and IASI) and their successor instruments.

One alternative road to achieve this could be in data assimilation of single-sensor aerosol retrieval results. However, any inconsistency of those separate pieces ingested into an atmospheric model will create difficulties and, in addition, the effort for including several independent satellite aerosol products (error covariance matrices, bias corrections) has put a stringent limitation so far. Ultimately, the use of all available information from different sensors offers the perspective of “self-consistent” results.

Building on lessons from the decade of Aerosol_cci developments and my own early and simplistic synergetic retrievals (SYNAER with AATSR and SCIAMACHY), this work presents a conceptual framework for advancing synergetic aerosol retrieval methodologies. Key elements include multi-sensor information content analysis, strategies for addressing historical data gaps and practical challenges (e.g. cross-calibration, cross-channel correlations, colocations and differences in field of views). In combination with priorities for needed parameters and length and gaps in historic records, this paper aims to establish a roadmap for synergetic aerosol retrievals, paving the way for more robust and comprehensive, i.e. self-consistent climate data records.

How to cite: Popp, T.: A concept for synergetic retrievals of self-consistent aerosol property climate data records, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15893, https://doi.org/10.5194/egusphere-egu25-15893, 2025.

How to cite: Ritter, O., Bley, S., Oktem, R., Romps, D. M., and Deneke, H.: Object-based characterization of continental Shallow Cumulus using synergistic decameter-scale observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16759, https://doi.org/10.5194/egusphere-egu25-16759, 2025.

There are 9 Fengyun (FY) meteorological satellites on the orbit to obtain the global meteorological observation data. The validation is fundamental for satellite product and the quantitative application. At present, China Meteorological Administration (CMA) maintains the huge ground-based meteorological observation network with nearly 80,000 sets of ground-based equipment spanning over 340 types to measure over 100 items of meteorological parameters. This network provides the independent means to assess the accuracy of the data products derived from the FY satellites. An operation-oriented validation system for FY-3 polar orbiting satellites has been designed and established since 2022. This system is named as the Integrated Space-Ground System for Calibration and Validation (ISGS4CV).

The objective of ISGS4CV is to assess the FY satellite products routinely and to generate the integrated dataset by data fusion as well. With the data fusion, ISGS4CV can generate the integrated dataset to better describe the digital Earth. The new dataset will inherit the advantages of the space-based measurement in spatiotemporal resolution and the ground-based measurement in high accuracy. The current CMA ground-based meteorological observation network will be selected to support ISGS4CV. For example, the surface network, the upper-air network, the new generation weather radar network, the atmospheric composition network, the ground-based remote sensing network, and the airborne observation system and field campaigns will be included.

How to cite: Zhang, P.: Chinese Integrated Meteorological Observation Network for FY Satellite Validation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4707, https://doi.org/10.5194/egusphere-egu25-4707, 2025.