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 dp and Sp 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 dp and Sp 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 2nd 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 1st 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 this talk, we will discuss plans to maximize the extraction of information from the inversion of hyperspectral infrared (IR) and microwave data obtained from polar-orbiting instruments. Hyperspectral remote sensing, which involves capturing Earth’s emitted energy in the IR spectrum, has become a pivotal tool for understanding atmospheric and surface conditions. A central challenge in this field is the efficient and accurate inversion of hyperspectral IR data to extract quantitative physical and chemical properties. The AdaptiveMETeo HYperSpectral Transformer (AMETHYST) inversion system represents a significant advancement in this regard. It enables the characterization of vertical atmospheric columns by considering variables such as temperature, pressure, and humidity at various altitudes. By comparing observed hyperspectral IR data with simulated radiance, AMETHYST adjusts model parameters to accurately retrieve vertical atmospheric structures.
AMETHYST leverages both hyperspectral data and numerical weather prediction (NWP) model forecasts to produce thermodynamic profiles and transformed retrievals (TRs). These TRs, developed using Migliorini’s transformation, are particularly suited for regional model assimilation due to their reduced data volume, instrument-specific adaptations, and simplified observation error covariance. Recent studies, including Cherubini et al. (2023), have demonstrated the effectiveness of TR assimilation in improving moisture field characterization over the central North Pacific Ocean, particularly at mid-atmospheric levels. This improvement is crucial for refining cloud and precipitation predictions.
Additionally, our team is extending the capabilities of AMETHYST to analyze physical profiles above cloud tops in the Arctic by integrating cloud masks and properties from various satellite instruments, differentiating it from its predecessor, MIRTO.
How to cite: Businger, S. and Antonelli, P.: Enhancing Atmospheric Profiling with the AMETHYST Hyperspectral Inversion System, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15230, https://doi.org/10.5194/egusphere-egu25-15230, 2025.
In recent years, China’s air pollution control efforts have significantly reduced fine particulate matter (PM2.5) 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 PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 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.
Shallow convective cumulus clouds (ShCu) play a crucial role in weather and the global climate system. These clouds are characterized by spatial and temporal variability on a wide range of scales, making ShCu an important contributor to the uncertainty in determining the local and global radiation budget as well as mass transport. Since individual remote sensing instruments can only capture a small part of this variability, a synergy of several observations is beneficial.
By combining very high spatial resolution, multispectral observations from the polar-orbiting Sentinel-2 satellite with a stereo camera-based 4D cloud product, Clouds Optically Gridded by Stereo (COGS), we will analyze 15 scenes of continental ShCu in a 6x6x6km3 domain around the Central Facility of the ARM Southern Great Plains site in the United States. Using an object-based approach, we will highlight the three-dimensional geometric properties of individual ShCu and the relationship to their multispectral reflectances and their cloud shadows. The meteorological influences on the geometric properties, and the relationship between cloud size, cloud thickness and cloud volume will be discussed.
Furthermore, considering the 270km wide observation path of the Sentinel-2 satellite, we will discuss the influence of cloud geometry, meteorological conditions and the organization of ShCu on the variability of cloud fraction and cloud size distributions, as an important step towards the parameterization of ShCu in climate models. The results will also be placed in the context of temporal cloud development.
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.
Posters on site: Fri, 2 May, 08:30–10:15 | Hall X5
The Korea Meteorological Administration Weather Radar Center (WRC) has collaborated with Taiwan National Central University (NCU) and ported the multiple-Doppler radar wind field retrieval technique (WISSDOM) and thermodynamic variable retrieval technique. WISSDOM utilizes a variational method to overcome the limitations of conventional wind retrieval techniques. It determines the optimal wind vector from radial velocities of multiple weather radars through iterative calculations of control variables (horizontal and vertical wind components) to minimize the cost function of dynamic constraints. Consequently, WISSDOM produces a 3D wind field that satisfies the physical equations and reflects the influence of observational data. WRC has tuned the algorithm to suit the complex terrain of Korea, enabling real-time operation. As a next step, we aim to develop a radar wind field-based thermodynamic variable retrieval technique called the Terrain-Permitting Thermodynamic Retrieval Scheme (TPTRS). TPTRS retrieves thermodynamic variables such as pressure, temperature, and water vapor mixing ratio using a 3D wind field synthesized from multiple Doppler radars in complex terrain. To address the challenges posed by complex terrain, TPTRS applies the Immersed Boundary Method to constrain the flow of fluids on the ground and utilizes a cost function composed of momentum and thermodynamic equations. By iteratively minimizing the cost function, TPTRS retrieves significant 3D thermodynamic variables. In this study, we implemented a radar-based TPTRS algorithm suitable for the complex terrain of Korea and analyzed its results. We conducted experiments to determine the optimal number of iterations for real-time operation and obtained meaningful results with over 1000 iterations. A case study was conducted on a heavy rainfall event that occurred on 31 July 2019, analyzing the potential temperature, mixing ratio, and pressure fields. In the cross-section of the developing major precipitation system, we observed an increase in potential temperature with altitude, accompanied by high and thick mixing ratios. This aligns with the characteristics of a developing system and is considered a significant result. We plan to develop a system for retrieving thermodynamic variables across the entire Korean Peninsula in the future.
This research was supported by the " Development of radar based severe weather monitoring technology (KMA2021-03121)" of "Development of integrated application technology for Korea weather radar" project funded by the Weather Radar Center, Korea Meteorological Administration.
How to cite: Choi, Y., Kim, K.-H., Teng, Y.-L., and Liou, Y.-C.: Tailoring TPTRS for Operational Thermodynamic Retrieval in the Complex Terrain of Korea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7503, https://doi.org/10.5194/egusphere-egu25-7503, 2025.
Air temperature is an important parameter in both icing and fog, and thus plays a critical role in assessing the operational stability of Urban Air Mobility (UAM) during takeoff, landing, and routine operations. However, there has been relatively little research focused on directly retrieving air temperature from satellite observations. This study estimated air temperature over the Korean Peninsula in East Asia using satellite-based land surface temperature (LST). This study employed the fine-resolution LST (~100 m), which was derived from coarse-resolution temperature of the Geostationary Korea Multi-Purpose Satellite-2A (GK-2A) and Landsat 8 using Taylor series expansions and surface characteristic indices. To mitigate the atmospheric effects, the surface indices, derived from Landsat 8, included the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Moisture Index (NDMI). The fine-resolution LST was then incorporated into the surface energy balance budget equation to estimate air temperature. It is anticipated that this study will enable the derivation of high-resolution atmospheric temperatures and that obtaining these directly from satellite observations will greatly aid research on modeling fog and icing formation.
This work was funded by the Korea Meteorological Administration Research and Development Program under Grant RS-2024-00404042.
How to cite: Shin, D. and Park, S. S.: Estimation of Satellite-Based Air Temperature Using Land Surface Temperature, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7797, https://doi.org/10.5194/egusphere-egu25-7797, 2025.
Accurately modelling the distribution of mineral dust in the atmosphere is a complex task that poses significant challenges. Dust aerosols influence critical atmospheric processes, such as the radiation balance and nutrient deposition, making their study essential for understanding Earth’s dynamics. However, the inherent variability and complexity of dust emissions, transport, and deposition contribute to large uncertainties in aerosol numerical predictions.
This study combines advanced numerical modelling with satellite observations, to tackle these challenges and enhance dust forecasts over the Mediterranean region. We use the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to simulate dust activity during September 2021. The simulations are improved by assimilating satellite-based dust optical depth data from the MIDAS (Mineral Dust Aerosol Satellite) product, which provides observations at a spatial resolution of 1°×1°.
By integrating MIDAS data, we significantly refine the model’s dust predictions, aligning them more closely with observed conditions. The improved forecasts demonstrate clear benefits, especially for applications in air quality management and solar energy optimization. Additionally, a more accurate representation of dust aerosol provides a solid base for studying aerosol-cloud interactions.
These findings highlight the value of blending high-quality observational datasets with sophisticated modelling approaches to address uncertainties in dust aerosol studies.
Acknowledgements. This research work has been supported by the EU-funded programme CiROCCO under Grant Agreement No 101086497. Α part of this work has been supported by AIRSENSE (Aerosol and aerosol cloud Interaction from Remote SENSing Enhancement) project, funded from the European Space Agency under Contract No. 4000142902/23/I-NS.
How to cite: Drakaki, E., Gkikas, A., Georgiou, T., El-Askary, H., and Amiridis, V.: Enhancing WRF-Chem Dust Predictions Through Assimilation of Satellite-Based MIDAS Dust Optical Depth Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18448, https://doi.org/10.5194/egusphere-egu25-18448, 2025.
Mineral dust aerosol is important in the Earth system, and the correct representation of its size distribution is fundamental for shaping the current state and evolution of the climate. Despite many observational dust size data that are available in the literature, using this body of information to properly guide the development and validation of climate models and remote sensing retrievals remains challenging. In this study we collect, evaluate, harmonize, and synthesize 58 size distribution data from the past 50 years of in situ field observations with the aim of providing a consistent dataset to the community for use in constraining the representation of dust size across its life cycle.
Four levels (LEVs) of data treatment are defined, going from original data (LEV0), data interpolated and normalized on a standardized diameter grid (LEV1), and data in which original particle diameters are converted to a common geometrical definition under both spherical (LEV2a) and aspherical (LEV2b) assumptions. Size distributions are classified as emission or source (SOURCE, < 1 d from emission; number of datasets in this category N = 12), mid-range transport (MRT, 1–4 d of transport; N = 36), and long-range transport (LRT, > 4 d of transport; N = 10). The harmonized dataset shows consistent features suggesting the conservation of airborne particles with time and a decrease in the main coarse-mode diameter from a value on the order of 10 μm (in volume) for SOURCE dust to a value on the order of 1–2 μm for LRT conditions. An additional mode becomes evident below 0.4 μm for MRT and LRT dust. Data for the three levels (LEV1, LEV2a, and LEV2b) and the three categories (SOURCE, MRT, and LRT), together with statistical metrics (mean, median, 25th and 75th percentiles, and standard deviation), are publicly available and distributed on the DATA TERRA EasyData portal.
The significance of the dataset for remote sensing and modelling of mineral dust will be discussed.
How to cite: Formenti, P. and Di Biagio, C.: Large synthesis of in situ field measurements of the size distribution of mineral dust aerosols across their life cycles, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11368, https://doi.org/10.5194/egusphere-egu25-11368, 2025.
Airborne dust plays a significant role in influencing weather phenomena, climate dynamics, and human health. Accurate quantification of dust concentration and its vertical distribution in the atmosphere, as well as accurate monitoring of dust microphysical properties including chemical composition, is essential for understanding dust impacts on radiation, cloud formation, weather and climate, and for developing corresponding mitigation strategies. Various observational methods have been developed to measure atmospheric dust properties, utilizing remote sensing (e.g. lidar and sun-photometers) and in-situ techniques. These techniques use different assumptions and their combination is a challenging task (e.g. Tsekeri et al., 2017). Herein, we try to harmonize their outputs for dust concentration profiles, using an extensive dataset gathered during the ASKOS campaign in the Cabo Verde Islands, a region uniquely positioned to observe dust outbreaks.
The ASKOS campaign (Marinou et al., 2023) was the ground-based component of the JATAC campaign organized by ESA and NASA in the islands of Cabo Verde (Fehr et al., 2023) during 2021 and 2022. Its main aim was to provide data for the calibration and validation of the Aeolus mission, with a focus on aerosol products. Over the course of these two years, a combination of aircraft, UAV, and ground-based remote sensing measurements was conducted.
The instruments deployed during ASKOS included a multiwavelength Raman-polarization lidar (PollyXT), an AERONET sun-photometer, and in-situ sampling performed using optical particle counters (OPCs) and impactors onboard UAVs (Kezoudi et al., 2023). The UAV in-situ measurements were acquired from ground level up to 5 km above sea level, collocated with the remote sensing data. The OPCs provided measurements of particle size distribution, and the impactors of particle mineralogy.
The dust concentration profiles were calculated from lidar data using the POLIPHON method (Mamouri & Ansmann, 2014). This method utilizes extinction-to-mass conversion factors derived from AERONET data for various aerosol types (including dust), and calculates the mass concentration profiles from the extinction coefficient profiles provided by the lidar.
Dust mass concentration at different altitudes was also derived by using in-situ observations of the number size distribution of the particles. First, the corresponding volume size distribution and the total volume of the particles, are calculated. The dust mass concentration is calculated based on the percentage of dust particles in the volume (provided by the impactor chemical composition observations), using a mean density for dust particles, equal to 2.6 g/cm3. For cases for which no in-situ observations are available, the volume size distribution of AERONET is utilized, though providing column-effective values.
The initial results indicate that the integrated mass concentration across the dust layer, as determined by both techniques, lies within the uncertainty ranges of the respective methods. Also, the analysis from the impactors provides information on the mineralogical composition of the dust particles that are transported from the Sahara.
Our work will assess each technique’s validity and identify the conditions under which the remote sensing method can be used independently.
This research was supported by the REVEAL project (GA 7222) funded by the Hellenic Foundation for Research & Innovation and by the PANGEA4CalVal project (GA 101079201) EU-funded.
How to cite: Tsichla, M., Tsekeri, A., Kandler, K., Baars, H., Haarig, M., Gialitaki, A., Kezoudi, M., Floutsi, A., Papetta, A., Marenco, F., Marinou, E., Voudouri, K.-A., Mihalopoulos, N., and Amiridis, V.: Quantifying dust concentration and mineralogy in the atmosphere, by combining remote sensing and airborne (UAV) in-situ, during the ASKOS campaign, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12682, https://doi.org/10.5194/egusphere-egu25-12682, 2025.
The impacts of climate change on desert ecosystems are profound and far-reaching, influencing not only local environments but also neighbouring regions, where dust storms transport pollutants and particulate matter over thousands of kilometers. These phenomena pose significant challenges to environmental monitoring and policy-making, requiring innovative approaches to data collection and analysis. In the Horizon Europe CiROCCO project, we have adopted an approach ensuring comprehensive environmental monitoring by leveraging the strengths of high-end sensors offering precise and reliable measurements and low-cost sensors, enabling extensive spatial coverage and high-frequency data acquisition. This integration creates a robust and scalable network, which enhance data accuracy and consistency, can support real-time monitoring and long-term environmental research and conservation efforts. The CiROCCO system architecture has been designed to facilitate the deployment and exploitation of this advanced monitoring framework across diverse environments, addressing the specific needs of four pilot sites in Cyprus, Egypt, Serbia and Spain. It incorporates state-of-the-art data fusion techniques, remote sensing integration, and a flexible modular design, ensuring adaptability to various ecological and socio-economic contexts. Our presentation will provide an overview of the CiROCCO system architecture, emphasising its potential to support not only environmental conservation and research but also evidence-based policy-making and climate adaptation strategies.
Acknowledgement:
The CiROCCO project is funded by the European Union’s Horizon Europe Programme. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or REA. Neither the European Union nor the granting authority can be held responsible for them.
How to cite: Georgiou, M., Romas, I., Papathanasiou, C., Vlachos, M., Sophocleous, M., Erotokritou, K., Drakaki, E., Grivas, G., Kosmopoulos, P., Ghanad, M., Al-Askary, H., Elbadawy, O., Mouzourides, P., Alexandrou, G., Mesaroš, M., Alcalá, F., and Segura, R.: Real-time environmental monitoring system architecture using distributed networks of low-cost and high-end sensors combined with remote sensing and data assimilation , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20466, https://doi.org/10.5194/egusphere-egu25-20466, 2025.
There is a natural partitioning of scientific interest amongst three focus areas of aerosol research: modeling, in situ measurements, and remote sensing observations. The community benefits when these groups interact, with overall benefits towards advancing our understanding of climate, weather, and air quality. To this end, MIRA seeks to foster international collaborations across disciplines and regional boundaries and offers a complementary association with established international working groups. A special focus is on collaborations that help advance operational services and products for near term benefits to society.
Within the present framework, MIRA has identified four initial focus areas. One effort advances knowledge of the aerosol lidar ratio for different aerosol compositions and locations to improve backscatter lidar retrievals from satellites and ground-based instruments. Another effort seeks to improve aerosol and cloud optical parameters used by climate and radiative transfer models. A third effort focuses on harmonizing aerosol assimilation models with satellite measurement retrievals, and a fourth interest seeks to develop retrievals of aerosol particulate matter from satellite remote sensing measurements.
The grassroots working group was formed in 2021 and includes more than 250 participants with representatives from Asia, Europe, Australia, and North America. A newsletter is published quarterly and webinars are held bi-monthly on topics of interest to the members. A workshop in Greece is also planned for June 2025. The presentation will provide an overview on MIRA and ways for the community to engage.
How to cite: Trepte, C., Amiridis, V., Andrews, E., Cambaliza, M. O., Chin, M., Di Biagio, C., Dubovik, O., Kim, S. W., Marinou, E., Redemann, J., Saito, M., Schuster, G., Yang, P., and Ziemba, L.: Models, In situ, and Remote sensing of Aerosols (MIRA)International Working Group: An Update, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2908, https://doi.org/10.5194/egusphere-egu25-2908, 2025.
In this study, we analyze the daily aerosol variability from synergetic multi-satellite GRASP retrieval. On a regional to local scale, aerosol diurnal concentration and microphysical properties can change rapidly due to inherent short lifespan, intense source emissions and weather processes. To observe the aerosol diurnal variability of a region, it is necessary to have multiple satellite measurements (greater than two measurements per day), and desirable to have per-hour satellite measurement. The capability to observe aerosol diurnal patterns is of interest to many research and applications such as: basic research of the aerosol global spatial distribution, variability and climate effects; aerosol transport modelling; Assimilation into atmospheric circulation models, etc. To meet these needs, it is essential to utilize all available satellite measurements to increase the sampling in time, in scattering angle and in spectral space.
In the ESA SYREMIS project, we performed a pioneering attempt of synergetic retrieval combining OLCI/Sentinel-3(A and B), TROPOMI/Sentinel-5p and AHI/Himawari-8 measurements using the GRASP algorithm. Such synergy of instruments from different satellite platforms greatly expands the spectral range, observation angle range and temporal observation density compared to existing synergy/merged satellite products. This led to much enhanced observation capability and retrieval accuracy for the merged instrument network. Among the aerosol products from synergetic retrieval, Aerosol Optical Depth (AOD) show very good fit to AERONET AOD diurnal time series, aerosol microphysical parameters such as Angstrom Exponent (AE) and Single Scattering Albedo (SSA) also show very good fit to the corresponding AERONET diurnal time series. Lateral comparison with the XAERDT merged aerosol products (MODIS+VIIRS+AHI) were made, and GRASP synergetic aerosol products show superior performance, especially in terms of the temporal stability of all aerosol parameters, and accuracy of the aerosol microphysical parameters. The improved synergy aerosol product should greatly benefit downstream applications such as aerosol transport modelling, assimilation into atmospheric circulation models and air quality forecast models.
How to cite: Zhai, S., Litvinov, P., Dubovik, O., Matar, C., Li, C., Fuertes, D., Chen, C., Liu, Z., Lapyonok, T., Dornacher, M., Lehner, A., Dandocsi, A., Gasbarra, D., Fluck, E., and Retscher, C.: Daily aerosol variation revealed by synergetic multi-satellite GRASP retrieval, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16550, https://doi.org/10.5194/egusphere-egu25-16550, 2025.
The Eastern Arabian Peninsula experiences elevated atmospheric particle loads due to anthropogenic emissions from the extraction and use of fossil fuels, as well as natural dust events, resulting in significant aerosol optical thickness (AOT). However, despite the region's significance, there is a lack of studies focusing on the optical and microphysical characterization of aerosols, leaving critical gaps in understanding their radiative effects. This study examines the optical properties of atmospheric particles over Qatar using more than one-year sun photometer data, with an emphasis on temporal variations and source origins. Measurements of direct sunlight were recorded every 5 minutes across wavelengths from 340 to 1020 nm between March 2023 and November 2024. Aerosol optical thickness (AOT) was calculated from these measurements using the Beer-Lambert-Bouguer law, while the Angstrom Exponent (AE) was derived to assess particle size. The results revealed notable daily variability, with average AOT values at 440 nm of 0.41 ± 0.21 and AE values averaging 0.87 ± 0.35. Seasonal patterns showed higher AOT during the summer months and a transition from dust-dominated to anthropogenic aerosols between March and December. Aerosols were classified into three categories: mineral dust-dominated (AE < 0.5), mixed (0.5 < AE < 1), and anthropogenic (AE > 1), accounting for 18%, 44%, and 38% of the total observations, respectively. These findings provide new insights into the aerosol composition over the region and emphasize the need for further research using radiative transfer models to evaluate aerosol-induced changes to the radiation budget.
How to cite: Tutsak, E., M. Mahfouz, M., Shahid, I., A. Al-Thani, J., Yiğiterhan, O., and M.A.S. Al-Ansari, E.: Aerosol Optical Properties in the Eastern Arabian Peninsula from Direct Sun Observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14885, https://doi.org/10.5194/egusphere-egu25-14885, 2025.
The U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) user facility aims to improve climate and earth system models through providing detailed observations of the atmosphere to the scientific community. These observations are provided by ARM's atmospheric observatories which combine dozens of remote and in situ sensors for characterizing many atmospheric parameters relating to clouds, precipitation, aerosols, and radiation balance. This presentation will focus on the recent and upcoming deployments of two of ARM's ground based observatories, the ARM Mobile Facility (AMF) 1 & 2. These AMFs travel the globe to collect observations from diverse regions and meteorological regimes through proposal-driven deployments. This will focus on studies in Houston, Texas, USA,; La Jolla, California, USA; Tasmania, Australia, and upcoming deployments of ARM’s AMFs.
How to cite: Powers, H.: ARM Mobile Observatory Recent and Field Studies, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20704, https://doi.org/10.5194/egusphere-egu25-20704, 2025.
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, 2021
How to cite: Dubovik, O., Litvinov, P., Fuertes, D., Lopatin, A., Lapyonok, T., Li, C., and Matar, C.: Multi-term LSM as methodological platform for advanced multi-sensor remote sensor synergy , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9959, https://doi.org/10.5194/egusphere-egu25-9959, 2025.
Advances in aerosol characterization through remote sensing rely on improved inversion algorithms. Scattering phase matrix measurements of ambient aerosols, now feasible with advanced polar nephelometry, are key to these advancements. The Polarized Polar Imaging Nephelometer (PI-Neph, GRASP-Earth PIN-100) has been operating continuously since 2022 in Granada (Spain) providing direct measurements of the phase function (F11) and the degree of linear polarization (−F12/F11) at three wavelengths (405, 515, and 660 nm).
During an extreme biomass-burning event from September 10–12, 2022, surrounding Granada, PM10 and PM2.5evels reached 100–150 µg/m3. Aerosol scattering and absorption coefficients peaked at 500 and 150 Mm−1, respectively. Chemical analysis of PM10 revealed elevated carbonaceous species concentrations, with organic carbon (OC) and elemental carbon (EC) reaching 14 µg/m3 and 3 µg/m3, respectively. Microscopy analyses identified spherical carbonaceous particle agglomerates.
This study explores different configurations of the Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm to retrieve aerosol optical and microphysical properties during this biomass-burning event using multiwavelength F11 and F12 measurements. Three inversion approaches were evaluated: a classical scheme assuming a uniform refractive index for all aerosol modes, a bimodal scheme allowing distinct refractive indexes for each mode, and a novel approach incorporating multiwavelength absorption coefficients from Aethalometer measurements.
The classical inversion yielded modal radii of r1=0.13 μm and r2=8.1 μm, with a refractive index of 1.66+2.70⋅10−4i at 515 nm. The bimodal scheme produced smaller radii (r1=0.12 μm, r2=0.44 μm) and refractive indexes of 1.66+2.01⋅10−4i and 1.50+6.30⋅10−5i, respectively Both approaches showed single scattering albedo (SSA) values above 0.99 but underestimated the measured absorption coefficients.
Incorporating Aethalometer data improved agreement with measured absorption. This method retrieved modal radii of r1=0.11 μm and r2=0.30 μm and refractive indexes of 1.65+6.70⋅10−2i and 1.70+3.10⋅10−4i for each modes respectively. The derived total SSA was 0.85 (with values of 0.75 and 0.99 for each mode), accurately reproducing measured absorption coefficients.
In all cases, inversion residuals were below 2%, highlighting the effectiveness of these retrieval approaches in characterizing aerosols during intense biomass-burning events.
How to cite: Rejano Martínez, F., Pérez-Ramírez, D., Li, C., Bazo, E., Fuertes, D., Martins, V., Dubovik, O., Valenzuela, A., Castillo, S., Titos, G., and Olmo, F. J.: Optical and microphysical properties of fire smoke aerosol from in-situ polar nephelometry using GRASP , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12468, https://doi.org/10.5194/egusphere-egu25-12468, 2025.
Radiative forcing by light-absorbing aerosols, particularly black carbon (BC), a major climate forcing agent alongside CO2 and CH4, remains poorly constrained due to insufficient characterisation of their optical properties and highly variable spatio-temporal distributions. Here we aim to refine BC’s spatio-temporal variability using the GEOS-Chem 3D Eulerian chemistry-transport model, which incorporates BC’s well-defined physical and chemical properties. The model includes aerosol-phase chemistry relevant to urban atmospheres, such as desert dust, BC, organic carbon, sea salts, SiO2, metal oxides, SO4²⁻, NO3-, NH4⁺, Na⁺, and Ca²⁺, at a global resolution (2°×2.5°) with primary aerosols only. Our primary objective is to precisely map BC’s spatial and temporal distributions, which is critical for evaluating the long-term impact of absorbing aerosols on net radiative forcing.
Using the 4D-Var assimilation method with TROPOMI/GRASP aerosol optical depth (AOD) and aerosol absorption optical depth (AAOD) data, we adjust global-scale emissions at an hourly resolution from March 2019 to November 2020. From a satellite remote sensing perspective, this characterization of aerosols via a single-viewing spectrometer is unprecedented. The GRASP open-source algorithm has generated this novel dataset. The GEOS-Chem model is driven by 3-hourly meteorological fields obtained from GEOS-FP reanalysis data. Our study includes the extreme events of the Australian bushfire season and Canadian forest fire events, where we identify emission sources absent from the GFED3 inventories (1996–2012) used in the forward run. Assimilation of TROPOMI/GRASP AOD and AAOD data into the model allows to reproduce carbonaceous aerosol emissions. These results are validated using MODIS and VIIRS RGB imagery. Ground-level BC concentrations are further validated against in situ measurements from France in the frame of the ANR BLACKNET project and from AERONET.
This framework will enable creating a global particulate matter (PM) database with high temporal resolution, spanning several years. Satellite data alone cannot achieve this level of detail. High-resolution BC distribution via inverse modelling will benefit from future spaceborne multi-angular polarimetric sensors, such as 3MI, CO2M MAP, and PACE. Additionally, aerosol vertical distributions will be studied to assess their influence on temperature profiles and atmospheric stability. This work will aid in validating and comparing suborbital measurements. The inverse modelling approach aligns closely with LiDAR-based observations from the EarthCARE mission.
How to cite: Behera, A., Chen, C., Dubovik, O., Litvinov, P., Gu, Y., Henze, D., Lapyonok, T., Thieuleux, F., and Guinot, B.: Improving Black Carbon Emission Estimates at Global Scale Using GEOS-Chem model and 4D-Var assimilation of TROPOMI/GRASP data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14616, https://doi.org/10.5194/egusphere-egu25-14616, 2025.
Accurately quantifying local road emissions is crucial for understanding urban air quality and its health impacts. This study presents a novel approach for retrieving high-resolution emissions data, achieving up to 1-meter resolution, from relatively coarse resolution satellite images (500 meters). The methodology integrates Computational Fluid Dynamics (CFD) to simulate wind fields and pollution dispersal from selected road segments in complex urban conditions.
The model is based on several key assumptions: emission rates remain constant along each road segment, pollution dynamics are treated as a passive scalar without considering chemical transformations, and the pollution field within the domain is defined solely by the selected road segments and boundary conditions. The CFD simulation covers a domain of 1km by 1km with a vertical extent of 800 meters, achieving a resolution of 1 meter near buildings to accurately capture fine-scale variations in the pollution field, different surface types are using in this model: buildings, water, vegetations and roads.
For each road segment, we calculate the Aerosol Optical Depth (AOD) from the pollution field. Given that the pollution patterns are linear with respect to the velocity field, we can scale the pollution field according to emission values, allowing for flexible adaptation to varying emission rates. Our approach considers the 25 largest road segments, constructing a basis set from their respective AOD patterns. By using a linear combination of these AOD patterns, we develop a regression model where the weights correspond to the emission values for each road segment.
To solve this regression problem, we employ the Non-Negative Least Squares (NNLS) method, ensuring physically plausible, non-negative emission values. This technique provides a robust and scalable framework for transforming coarse satellite imagery into high-resolution emission maps, significantly enhancing the spatial granularity and accuracy of urban air quality assessments. Our approach represents a significant advancement in environmental monitoring, offering valuable insights for urban planners and policymakers aiming to mitigate pollution and improve air quality.
How to cite: Kuznetsov, K., Dubovik, O., Livinov, P., and Fuertes, D.: High-Resolution Retrieval of Local Road Emissions from Coarse Satellite Images Using CFD Modeling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19758, https://doi.org/10.5194/egusphere-egu25-19758, 2025.
Accurate modeling of gas absorption is essential for understanding atmospheric radiative transfer and enabling reliable retrievals of atmospheric composition. To address this need, we have developed a new gas computation module into the GRASP (Generalized Retrieval of Atmosphere and Surface Properties, Dubovik et al., 2021) code, extending its capability for simultaneous retrieval of atmospheric gases and aerosols.
The new gas module primarily employs an optimized correlated k-distribution method (Momoi et al., 2022) to efficiently calculate gas absorption optical thickness with high accuracy across a wide spectral range. Additionally, the module supports the line-by-line method as a complementary approach for comparison and validation, ensuring high accuracy and flexibility for a variety of atmospheric scenarios. The implementation of the gas module significantly expands GRASP’s capabilities, making it a more comprehensive tool for simultaneous retrieval of atmospheric gas vertical profiles and aerosol properties.
Preliminary results regarding the combination of multi-angular polarimeters and SWIR spectrometers (e.g., CO2M, S5 and 3MI) highlight the module's computational efficiency, precision, and adaptability, making it well-suited for operational deployment. Its ability to handle diverse atmospheric scenarios enables the development of advanced retrieval algorithms. Integrating this advanced gas module into GRASP code marks a transformative advancement, enhancing the capacity of remote sensing sensors to monitor aerosol and gases and address environmental challenges effectively.
How to cite: Lin, W., Herreras-Giralda, M., Momoi, M., Lapyonok, T., Lopatin, A., Rejano, F., Dubovik, O., Barr, A., and Landgraf, J.: Development of a flexible module accounting gas absorption in GRASP allowing simultaneous retrieval of gases and aerosols, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18680, https://doi.org/10.5194/egusphere-egu25-18680, 2025.
Atmospheric aerosols play a key role in influencing the Earth's radiation budget. Still, their impacts remain poorly quantified due to the complex mechanisms involved in the interaction between aerosols and clouds. Indeed, aerosols act as ice-nucleating particles and cloud condensation nuclei, significantly altering the formation of precipitation and clouds. These environmental impacts of aerosols are strongly dependent on their composition, origin, and types. Moreover, high concentrations of aerosols in the atmosphere degrade air quality, posing large health risks which are also highly dependent on their composition (which is related to their types).
In recent decades, a space-borne lidar called the cloud–aerosol lidar with orthogonal polarization (CALIOP) onboard cloud–aerosol lidar and infrared pathfinder satellite observation (CALIPSO) satellite was providing aerosol vertical distribution from space using two wavelengths, namely 532 nm which provides attenuated backscatter and depolarization profiles and 1064 nm which deliver attenuated backscatter profile. Combining its 3 channels, CALIOP measurements provide a purely qualitative aerosol typing detection, indicating the presence or absence of a single aerosol type at each altitude of the atmosphere. To provide a more detailed and quantitative characterization of aerosols and to gain new insights into the interactions between aerosols, clouds, convective processes and precipitation, the upcoming mission called Atmosphere Observing System (AOS), which includes contributions from the space agencies NASA (United States), CNES (France), ASI (Italy), JAXA (Japan) and CSA (Canada) is currently in preparation for launching in a horizon near 2030. AOS payload will include an advanced high-energy 3-wavelength lidar with Raman capabilities during nighttime, called CALIGOLA.
In our present work, we examine the potential of CALIGOLA lidar during the daytime (three wavelength attenuated backscatter and depolarization measurements) and nighttime (one additional Raman channel in the UV which is suitable for nighttime measurements) flying in a polar orbit. By utilizing our newly developed retrieval approach, we quantitatively discriminate the concentration vertical profiles of five distinct aerosol types, such as smoke, continental, oceanic, dust and urban polluted. The development and first implementation of the method were performed using the pseudo-reality simulations obtained from the chemistry-transport model called Modèle de Chimie Atmosphérique de Grande Echelle (MOCAGE). In addition, the first tests of our innovative retrieval approach are planned using real lidar measurements from the High Spectral Resolution Lidar-2 (HSRL-2) airborne lidar from NASA Langley Research Center (LaRC).
How to cite: Qayyum, F., Cuesta, J., Merdji, A. B., Lopatin, A., Dubovik, O., Nandan Piyush, D., El Amraoui, L., and Ferrare, R.: Vertical distribution of the concentrations of multiple aerosol types derived from the multiwavelength spaceborne lidar of the future Atmosphere Observing System , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15896, https://doi.org/10.5194/egusphere-egu25-15896, 2025.
The Atmosphere Observing System (AOS), a collaborative initiative from the international cooperation of NASA, CNES, JAXA, ASI, and CSA, aims to substantially enhance the observation of aerosols and clouds through the deployment of an advanced spaceborne lidar and a multi-angular polarimeter, expected to fly in tandem. Within this framework, we present a novel methodology for retrieving vertical concentration profiles of aerosol chemical species by synergistically leveraging measurements from co-located lidar and polarimeter instruments. This approach, named Aerosol Chemical Profiling (AEROCHEMPro), extends the GRASP (Generalized Retrieval of Aerosol and Surface Properties) framework to provide vertically resolved profiles of aerosol modes: (i) a fine mode containing black carbon, brown carbon, inorganic salts, and water content; (ii) a coarse desert dust mode composed of iron oxide and quartz; and (iii) a coarse sea salt mode with associated water content.
First, the AEROCHEMPro methodology is developed and implemented on synthetic observations from an Observing System Simulation Experiment (OSSE). Synthetic lidar and polarimeter measurements are simulated by radiative transfer code using a pseudo-reality built from the MOCAGE chemistry-transport model. We consider the instrumental configuration of AOS: the high energy 3-wavelength elastic backscatter lidar called CALIGOLA and the 8-wavelength ultraviolet-to-near-infrared multi-angular polarimeter of the AOS-Sky mission. These case studies demonstrate the capability of AEROCHEMPro to accurately retrieve the vertical profiles of aerosol chemical species, along with their optical and microphysical properties, offering a robust foundation for real-world applications.
In a second stage, a first adaptation of the AEROCHEMPro approach to real measurement is conducted. We use real airborne measurements from the Research Scanning Polarimeter (RSP) and NASA's High Spectral Resolution Lidar-2 (HSRL-2). While the RSP delivers complementing passive observations of polarized radiances across many spectral bands, the HSRL-2 offers high-resolution active aerosols remote sensing. HSRL-2 measurements are used to derive elastic backscatter signals as those that will be performed by CALIGOLA and level 2 products for comparison with respect to AEROCHEMPro output.
The proposed presentation will provide results of AEROCHEMPro based on both OSSE synthetic measurements and first implementations with airborne real measurements.
Keywords: AEROSOL OBESERVING SYSTEM; LIDAR; POLARIMETER; AEROSOL SPECIES PROFILE; GRASP; AEROCHEMPro
How to cite: Merdji, A. B., Cuesta, J., Qayyum, F., Lopatin, A., Dubovik, O., Nandan, D., El Amraoui, L., and Ferrare, R.: Vertical Profiles of Aerosol Chemical Species Concentrations derived from the Synergism of the Future Spaceborne Lidar and Polarimeter of the Atmosphere Observing System, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17053, https://doi.org/10.5194/egusphere-egu25-17053, 2025.
Aerosol profile measurements are crucial for validating and improving atmospheric models, satellite remote sensing algorithms, and regional dynamic models that consider the fine vertical structure of boundary layer dynamics. The boundary layer, where the atmosphere interacts with the Earth’s surface, is characterized by rapid changes in temperature, humidity, and turbulence. These thermodynamic conditions influence aerosols’ hygroscopic growth, mixing, and their roles in global atmospheric processes such as cloud formation and radiative transfer. The applying of unmanned aerial vehicles (UAVs) offers the potential for high-resolution in-situ profiling of aerosol parameters, enabling the capture of fine-scale variations often missed by traditional methods such as satellite observations or ground-based instruments. Since aerosols in the boundary layer are rarely uniformly distributed, their spatial heterogeneity significantly impacts air quality assessments and pollutant transport modeling.
In coastal regions, aerosol PM measurements are particularly valuable for evaluating the combined effects of marine and terrestrial emissions on air quality, ecosystem health, and nearby populations. However, deploying rotary UAVs as air quality sensor platforms presents unique challenges. The turbulence generated by UAV propellers can alter the sampled aerosol concentrations, potentially leading to quasi-systematic inaccuracies. Addressing this issue requires careful calibration of UAV-based sensors in the field.
Given study presents the results of vertical aerosol profile measurements, focusing on PM1, PM2.5, and PM10 concentrations, conducted during a short measurement campaign above the sea surface near Hel (54°44'25.9" N, 18°34'02.5" E), Poland. Data were collected using an OPC-N3 sensor mounted on a UAV at altitudes ranging from 5 to 120 m. Calibration of the drone-based measurements was performed using the specially designed Integrated Aerosol Monitoring Unit (IAMU), which houses three aerosol sensors (SPS30, OPC-N3, and OPS 3330) within a single enclosure [1]. All IAMU sensors as well as drone-based sensor are sensitive to hygroscopic growth of aerosol because of the absence of sample drying. However, the calibration approach formulated in [1] allows for approximating aerosol grow factor coefficient. This assessment was supported by auxiliary observations from a nephelometer Aurora 4000, Sun photometer and meteorological station. A calibration technique is proposed for the OPC-N3 sensor, incorporating synchronous IAMU data and accounting for aerodynamic losses in the sampling inlet tubes.
- Bruchkouski, I.; Szkop, A.; Wink, J.; Szymkowska, J.; Pietruczuk, A. Multi-Sensor Instrument for Aerosol In Situ Measurements. Atmosphere 2025, 16, 42. https://doi.org/10.3390/atmos16010042
How to cite: Bruchkouski, I., Szkop, A., Wink, J., and Pietruczuk, A.: Drone-Based Aerosol Profiling: Calibration Using an In Situ Multi-Sensor System, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3192, https://doi.org/10.5194/egusphere-egu25-3192, 2025.
The greenhouse gases (GHG) methane (CH4) and carbon dioxide (CO2) have been emitted at an increasing rate since the Industrial Revolution, leading to amplified global warming. The Paris agreement, signed by 175 nations, represents the world’s first sound political framework to regulate GHG emissions. It entails a need to quantify GHG fluxes, ideally with global coverage.
Since the pioneering missions able to detect and quantify trace gases in the Troposphere, green gas monitoring instrument (GMI) and scanning imaging absorption spectrometer for atmospheric cartography (SCIAMACHY) almost 30 years ago, a number of satellite missions that provide global coverage have been launched and are used to serve that need. There is, however, a significant discrepancy between bottom-up GHG emission estimates from inventories and top-down estimates using a combination of space-borne GHG concentration measurements and atmospheric dispersion modeling. Over the last 12 years or so, a new generation of satellites-borne imaging spectrometers emerged with sub-kilometre pixel resolution, able to map trace gas plumes and thus able to quantify GHG fluxes directly at the source, contributing to improved GHG inventories. Among those are the first commercial Earth observation missions to monitor GHG sources.
The commercial AIRMO mission aims to quantify GHG fluxes, notably CH4, in the planetary boundary layer, over regions that may contain significant aerosol concentrations, such as sulfate, marine and desert aerosols and aerosols from biomass burning. These aerosols exhibit extinction of solar photons by scattering and absorption, which may significantly modify the path of solar photons so that apparent and actual column lengths differ, leading to a possible over or underestimation of GHG column densities from passive spectroscopy.
To correct for this bias in the retrieval algorithm, employing full physical modeling of light extinction by aerosols in the forward model is envisaged. Sensitivity tests are performed using the GRASP (Generalized Retrieval of Atmosphere and Surface Properties) retrieval and simulation code to assess the sensitivity of three crucial model parameters: The aerosol concentration parametrized as aerosol optical depth (AOD), the bidirectional surface reflectance (BRDF) and the aerosol layer height (ALH). A conceptually straightforward way to constrain the model aerosol parameters is a lidar co-located to the spectrometer, operating in a spectral region where the gases of interest have absorption lines. Consequently, a pulsed micro-lidar is simulated as a tool to constrain ALH. The benefits of this input information in the retrieval against methodologies based on oxygen A-band absorption bands are assessed. Furthermore, work is underway that assesses the overall benefits of the lidar, including those for other model parameters and mission objectives.
How to cite: Stepanova, D., Armandillo, E., Herreras-Giralda, M., Dubovik, O., Lopatin, A., Tomás, S., Queißer, M., and Vilaseca, D.: Aerosol layer height constrained by micro-lidar to enhance space borne push-broom spectrometer measurements of CH4 and CO2, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19313, https://doi.org/10.5194/egusphere-egu25-19313, 2025.
Posters virtual: Tue, 29 Apr, 14:00–15:45 | vPoster spot 5
EGU25-9946 | ECS | Posters virtual | VPS2
Long-term changes in black carbon aerosols and their health effects in rural India during the past two decades (2000–2019)Tue, 29 Apr, 14:00–15:45 (CEST) | vP5.27
Black carbon (BC) is a short-lived atmospheric aerosol having light absorbing properties with climate-changing potential. In addition, BC aerosols are also responsible for several adverse health effects including cardiovascular and respiratory problems. Here, we examine the long-term changes in BC, using MERRA-2 (Modern-Era Retro spective analysis for Research and Applications) and Emissions Database for Global Atmospheric Research (EDGAR) data for the period 2000–2019, and the associated health burden in rural India. This study finds a decreasing trend in BC in the rural IGP (Indo-Gangetic Plain) and NWI (North West India) during 2007–2019, at about -0.004 and –0.005 μg/m3/yr, respectively. A significant reduction in BC (from 0.03 to 0.01 μg/m3/yr after 2006) is observed in the rural Peninsular India (PI), where the reduced wind speed limits the transport of BC aerosols from other regions and thus, limits the BC concentration there. Our assessment finds that government policies such as BS (Bharat Stage) emission norms, electrification of rail routes, use of electric and compressed natural gas-based vehicles, the transformation of brick kilns to zig-zag technology, mechanised farming for on- site handling of crop residues and recent changes in atmospheric drivers (e.g. winds in IGP) contributed to this reduction in BC. However, the health burden associated with BC causes the highest all-cause mortality to be around 5,17,651 and 34,082 inhabitants in winter (December-February) and post-monsoon (October-November) seasons, respectively, in the rural IGP in the latest year 2019. In brief, the reduction of BC in rural India indicates that it complements the government policies. However, an improvement in the policy implementation might prove to be conducive to reduce the BC-driven mortality and regional climate warming.
How to cite: Pathak, M., Kuttippurath, J., and Kumar, R.: Long-term changes in black carbon aerosols and their health effects in rural India during the past two decades (2000–2019), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9946, https://doi.org/10.5194/egusphere-egu25-9946, 2025.
Additional speakers
- Soheila Jafariserajehlou, EUMETSAT, Germany
- Juan Cuesta, UPEC/LISA CNRS/IPSL, France