Generalized Retrieval of Atmosphere and Surface Properties (GRASP) is an algorithm provided as open-source software for remote sensing observations (Dubovik et al., 2021). The algorithm is designed for the interpretation of diverse remote sensing observations and is suitable for realizing synergetic processing using observations from multiple sensors. GRASP is based on several fundamental principles. It utilizes complete and rigorous modeling of atmospheric radiation applicable for simulating a variety of observations. The numerical inversion is implemented as an elaborated, statistically optimized fitting following the Multi-Term Least Square (MTLS) minimization concept, which serves as the basis for the efficient combination of different observations. For example, this concept allows for the use of multiple a priori constraints, which are essential when retrieving a large number of parameters of different types (e.g., describing properties of aerosols, gases, surface reflectance, etc.). This concept is also applied in “multi-pixel retrieval” scenarios, where the retrieval is implemented simultaneously for a large group of coordinated observations (such as observations in different satellite pixels). By processing these observations together, the retrieval incorporates prior knowledge regarding the temporal and spatial variability of the retrieved parameters. For instance, land surface reflectance tends to remain stable over weeks, while aerosols can change within hours or days. Similarly, aerosol properties typically vary minimally across several kilometers, whereas the land surface can exhibit high spatial heterogeneity. The algorithm’s design for interpreting diverse remote sensing data makes it ideal for the synergetic processing of observations from multiple sensors. This approach enables efficient synergy even for observations that are not fully coincident or co-located.

At present, GRASP has been used to develop a number of synergy retrievals. This presentation overviews and discusses the following key GRASP applications:

- Ground-based remote sensing synergies:

- Sun/sky-radiometer + lidar;

- Sun/sky-radiometer + Pandora spectrometer;

- Sun/sky-radiometer + Pandora spectrometer + lidar;

- Satellite remote sensing synergies:

- combining the same platform instruments with different capabilities (e.g. radiometers + spectrometers measuring;  radiometers + lidars; combining   UV, VIS, SWIR and TIR measurements, etc.);

- multi-platform LEO + LEO observations;

- multi-platform LEO + GEO observations;

- Satellite + ground-based remote sensing synergies:

-retrieval both atmospheric and surface reflectance properties from co-located ground-based and satellite observations.

The discussed developments are realized using observations from Copernicus Sentinel-2, -3, -5P, MTG, EPS-SG, and EarthCARE, and are implemented within the frameworks of the EU PANORAMA, ESA AIRSENSE, EarthCARE+, and other projects.

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., Lapyonok, T., Lopatin, A., Momoi, M., Herreras Gerada, M., Zhai, S., Li, C., Herrera, M., Matar, C., Antuña-Sánchez, J. C., Derimian, Y., Torres, B., Liu, Z., Zhang, Y., Lin, W., Sinuyk, A., and Lind, E.: Overview of remote sensing multi-instrument synergy retrieval realized using GRASP retrieval platform  , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4460, https://doi.org/10.5194/egusphere-egu26-4460, 2026.

EGU26-4460

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Absorbing aerosols in industrial regions exhibit rapidly evolving particle size distributions and mixing states that are poorly represented by common fixed-parameter assumptions, introducing coupled uncertainties in both aerosol radiative forcing and shortwave infrared trace-gas retrievals, particularly for methane (CH₄) in the 2.3-2.4 μm window. Here we develop a multi-constraint framework that combines column optical observations (multi-band AOD and SSA) with in situ size-resolved measurements and multi-wavelength black carbon mass to jointly constrain aerosol microphysics and optical behavior. A physically constrained core-shell Mie model is used to generate microphysically plausible solution ensembles, filtered by multi-waveband optical consistency and probability-density overlap with observed size spectra, thereby reducing inversion non-uniqueness and suppressing biases toward coarse-mode dominance and overly strong internal mixing.

The resulting constrained aerosol optical properties are propagated through radiative transfer modeling to quantify top-of-atmosphere and atmospheric forcing sensitivities to microphysical variability in industrial environments. Finally, the same observation-constrained absorption spectra are extended across 0.25-4 μm (with enhanced spectral resolution in methane-sensitive bands similar to TROPOMI) to diagnose wavelength-dependent aerosol-CH₄ spectral coupling: we show that even when absolute SWIR absorption is modest, aerosol-induced transmittance perturbations can partially overlap CH₄ absorption troughs and destabilize continuum/baseline fitting, such that broadband retrieval windows may accumulate small spectral mismatches into substantial interference. This behavior is further amplified by time-varying spectral slopes (e.g., non-stationary AAE), implying that fixed aerosol parameterizations are insufficient for robust CH₄ retrieval correction in complex emission regions. We note that we have direct radiative forcings ranging from -4 to -33 W/m², which at the lower end of the range may allow a way to bias-correct retrievals of CH₄, while at the higher end of the range implies that any signals retrieved for CH₄ are significantly caused by BC. Overall, this integrated approach provides a transferable pathway to simultaneously improve absorbing-aerosol forcing estimates and reduce aerosol-induced biases in satellite methane retrievals via band-optimized, aerosol-aware retrieval strategies.

How to cite: Guan, L., Cohen, J., Wang, S., TIwari, P., and Qin, K.: A Multi Constraint Absorbing Aerosol Microphysics and Optics Framework for Radiative Forcing Uncertainty and Methane Retrieval Biases in Industrial Regions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7230, https://doi.org/10.5194/egusphere-egu26-7230, 2026.

EGU26-7230

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This study explores the synergetic combined retrieval of remote sensing measurements in the solar and thermal infrared (TIR) spectral ranges from ground based and satellite sensors to provide a simultaneous gas-aerosol retrieval and an extended characterization of dust mineralogical composition. The Generalized Retrieval of Atmosphere and Surface Properties (GRASP) (Dubovik et al., 2021) is employed to jointly retrieve basic aerosol properties and selected dust mineralogical indicators—specifically the quartz–clay contrast and iron oxide fraction—together with representative trace gases, including ozone and water vapor. The new approach exploits complementary satellite and ground-based measurements, using IASI (Infrared Atmospheric Sounding Interferometer) (Cuesta et al., 2015) for TIR and 3MI (Fougnie et al., 2018) for solar spectral band, together with ground-based data from CLIMAT TIR radiometer (Brogniez et al., 2003) and CIMEL sunphotometer. Synthetic retrieval tests are conducted for both TIR–solar measurement combinations, using data from ground-based and spaceborne observations. The synthetic analysis shows good consistency under realistic noise and uncertainty conditions, demonstrating the robustness of the proposed scheme. This integrated approach shows strong potential to improve synergistic dust–gas retrievals in the TIR by reducing the required retrieval a priori and improving the accuracy of the retrieved products.

References

Brogniez, G., Pietras, C., Legrand, M., Dubuisson, P., & Haeffelin, M. (2003). A high-accuracy multiwavelength radiometer for in situ measurements in the thermal infrared. Part II: Behavior in field experiments. Journal of Atmospheric and Oceanic Technology, 20(7), 1023-1033. https://doi.org/10.1175/1520-0426(2003)20<1023:AHMRFI>2.0.CO;2

Cuesta, J., Eremenko, M., Flamant, C., Dufour, G., Laurent, B., Bergametti, G., ... & Zhou, D. (2015). Three‐dimensional distribution of a major desert dust outbreak over East Asia in March 2008 derived from IASI satellite observations. Journal of Geophysical Research: Atmospheres, 120(14), 7099-7127. https://doi.org/10.1002/2014JD022406

Dubovik, O., Fuertes, D., Litvinov, P., Lopatin, A., Lapyonok, T., Doubovik, I., ... & Federspiel, C. (2021). A comprehensive description of multi-term LSM for applying multiple a priori constraints in problems of atmospheric remote sensing: GRASP algorithm, concept, and applications. Frontiers in Remote Sensing, 2, 706851. https://doi.org/10.3389/frsen.2021.706851, 2021

Fougnie, B., Marbach, T., Lacan, A., Lang, R., Schlüssel, P., Poli, G., ... & Couto, A. B. (2018). The multi-viewing multi-channel multi-polarisation imager–Overview of the 3MI polarimetric mission for aerosol and cloud characterization. Journal of Quantitative Spectroscopy and Radiative Transfer, 219, 23-32. https://doi.org/10.1016/j.jqsrt.2018.07.008

How to cite: Zhang, Y., Herreras-Giralda, M., Cuesta, J., Eremenko, M., Gomes, C., Lin, W., Momoi, M., Gomez, A., and Dubovik, O.:  Simultaneous Retrieval of Dust Mineralogy and Trace Gases from the Synergetic Observations in Solar and Thermal Infrared Spectral Bands using GRASP Algorithm, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10594, https://doi.org/10.5194/egusphere-egu26-10594, 2026.

EGU26-10594

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There are a myriad of methods for matching data between satellites and surface-based observations (co-location), and no singular way to objectively compare the quality of the matching between methods. This work proposes a framework that allows for an optimised choice of co-location to be evaluated, and shows that this framework selects co-location schemes that demonstrably produce better output data than other typically used choices of co-location scheme.

Matching data described on different spatial and temporal coordinates and retrieved from different sources – spatiotemporal co-location – is an important step in any analysis utilising multiple sources of Earth observation data. For example, validating satellite data against surface-based remote sensing data often requires that the satellite data be spatially aggregated over its field of view near the surface-based observatory, and the surface-based data is temporally aggregated around the time of the satellite overpass. A good data co-location permits sufficient data such that subsequent analyses are viable, whilst limiting the mismatch error induced by comparing data between sources with larger spatiotemporal separations. The schemes by which data are co-located are often parameterised by a few variables that can be arbitrarily selected (for example, the maximum distance between a surface-based observatory and the footprint of a satellite obervation). The choice of these co-location parameters directly impacts all subsequent analyses, and there is no single correct method for selecting a parametrisation.

We describe a data-driven approach for selecting an optimised co-location parametrisation that is domain- and data-agnostic. The mutual information between data sources describes the amount of variability within the data coming from one source that can be described by variability in data from another source. The presented approach selects the co-location parameters such that the data co-location maximises the mutual information between the data sources. The output is paired data between the sources that is as close as possible to being described by a one-to-one relationship, given the input data and co-location scheme.

We apply this method of co-locating data to a validation of the cloud layer height retrievals in the ICESat-2 ATL09 data product against surface-based Cloudnet retrievals. Our method finds location-specific distances within which ICESat-2 data should be compared against data from a given Cloudnet observatory, and that a one-size-fits-all approach to selecting the co-location parameterisation degrades the quality of the resulting matched data through different failure modes, depending on the location. The comparison between vertical cloud fraction profiles between ATL09 and Cloudnet data are demonstrably better when using optimised co-location parameters as opposed to other choices.

As well as improving the quality of data provided to satellite validation studies, this method can be used across many contexts. It may be possible to improve multi-sensor synthesis of data through weighting of the contributions of different data products to the synthesis as a function of the mutual information between the input data products. The method can also be used to programmatically generate labelled training pairs of related data for deep learning models that best encode the relationship between the data sources.

How to cite: Martin, A., Guy, H., Gallagher, M., and Neely III, R.: Non-parametric optimised spatiotemporal data co-location using mutual information, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18704, https://doi.org/10.5194/egusphere-egu26-18704, 2026.

EGU26-18704

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Accurate characterization of land surface reflectance remains a fundamental challenge in satellite remote sensing, particularly over heterogeneous and bright surfaces where surface and atmospheric contributions are strongly coupled. Ground-based AERONET direct-sun and sky-radiance observations provide robust constraints on aerosol optical and microphysical properties, while satellite measurements provide spatially resolved information on surface reflection. In the GROSAT-GLOB approach, these complementary measurement types are combined to enable a more reliable separation of surface and atmospheric signals for surface characterization.

The GROSAT-GLOB approach implements a synergetic retrieval framework based on the GRASP inversion algorithm, integrating ground-based AERONET observations with collocated satellite radiance measurements. Aerosol optical and microphysical properties are primarily constrained by AERONET direct-sun and sky-radiance data, while satellite observations are used to retrieve surface reflectance. To ensure robustness and computational efficiency at the global scale, a two-step retrieval strategy is employed: aerosol microphysical properties are first retrieved by combining spatially aggregated (10–30 km) satellite observations with temporally collocated AERONET almucantar and direct-sun measurements, and are subsequently introduced as constrained a priori information to retrieve surface reflectance at the native satellite resolution using satellite radiances and direct-sun AOD measurements only.

The GROSAT-GLOB retrieval framework has been applied to multiple satellite sensors, including Sentinel-3 OLCI-A/B, Sentinel-5P/TROPOMI, PACE/HARP2, and MTG-FCI, demonstrating its general applicability across instruments with differing spatial resolutions, spectral coverage, and viewing geometries. The retrieved surface reflectance products are validated against independent reference datasets, including MODIS white-sky albedo, HYPERNET reflectance, and RadCalNet bottom-of-atmosphere reflectance, while aerosol retrievals are assessed against AERONET products. These intercomparisons provide a quantitative assessment of retrieval consistency and stability, supporting the use of GROSAT-GLOB products as a surface reference dataset for cross-sensor harmonization and satellite surface reflectance validation.

How to cite: Panda, S., Litvinov, P., Matar, C., Zhai, S., Gómez, J., Liu, Z., Antuña-Sánchez, J. C., Lopatin, A., Fuertes, D., Dubovik, O., Lapionak, T., Torres, B., Retscher, C., Scifoni, S., and Goryl, P.: GROSAT-GLOB: Synergetic Ground-Based and Satellite Retrievals for Global Surface Characterization and Validation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14777, https://doi.org/10.5194/egusphere-egu26-14777, 2026.

EGU26-14777

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We present a two-step framework for estimating black carbon (BC) emissions by integrating satellite remote sensing, ground-based observations, and physically grounded algorithms. First, BC mass and number column densities are retrieved using OMI satellite and AERONET sun photometer data, based on a Mie theory–driven core–shell model that accounts for particle microphysics. This integration of complementary platforms improves the sensitivity and spatial coverage of retrievals. Second, BC emissions are estimated from the retrieved columns using both mass- and number-conservative methods, allowing comparison of results under different assumptions about particle behavior and size distribution.

Applied over South, Southeast, and East Asia in 2016, the framework reveals emissions in regions such as Myanmar, Laos, northern Thailand, and Vietnam that exceed reported values in current inventories (e.g., FINN and EDGAR-HTAP) by more than an order of magnitude during high-intensity events. These emissions, concentrated between March and May, suggest a longer biomass burning season than typically captured by satellite NO₂ observations. Day-to-day estimates show substantial temporal variability, with emission uncertainties reaching up to 82% using the mass-conservative method and 75% using the number-based approach. Notably, the number-conservative method yields 20–43% higher emissions in biomass burning and urban areas, highlighting the limitations of mass-only assumptions that do not account for particle number sensitivity.

This framework also enables comparison between different emission estimation strategies, and reveals structural discrepancies linked to underlying particle representations. The number-based approach may offer a more complete picture of episodic BC emissions, especially in regions with high particle number concentrations or coarse assumptions in current inventories. While this study focuses on 2016 events, the methodology is flexible and compatible with upcoming satellite missions such as EarthCARE, supporting potential extensions to finer spatiotemporal scales. By embedding particle-level physics into a multi-instrument observational framework, this approach contributes to improved BC emission estimates in data-sparse and dynamic environments, providing a practical alternative to bottom-up inventories under high-impact conditions.

How to cite: Liu, J., Cohen, J., Yim, S., and Qin, K.: A Synergistic Framework for Black Carbon Emission Estimation via Satellite–Ground Retrievals and Particle-Conserving Methods, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16314, https://doi.org/10.5194/egusphere-egu26-16314, 2026.

EGU26-16314

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Aerosol composition plays a key role in quantifying its impacts on climate and human health, as well as in understanding aerosol sources, transport, and evolution. Using the high spectral resolution of thermal infrared radiances measured by the spaceborne IASI sensor, the AEROIASI approach has been developed to quantify aerosol species that significantly absorb in the thermal infrared spectral domain (Cuesta et al., 2015; Guermazi et al., 2021; Kutzner et al., 2021). To date, this approach has been applied using dedicated configurations that allow the retrieval of only one aerosol species at a time. These species include desert dust, sulfuric acid, and ammonium sulfate.

In this work, we present a new unified retrieval framework capable of simultaneously quantifying these three aerosol species and their respective fractions when they coexist in the atmosphere. This is achieved by exploiting the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) methodology (Dubovik et al., 2021), newly adapted to thermal infrared observations in the framework of the PANORAMA European Horizon 2020 project. The initial results establish a premise of the ability of the proposed approach to analyze mixed aerosol events over Europe using IASI measurements.

This GRASP-based method represents a first step toward a multispectral synergistic retrieval exploiting IASI-like thermal infrared measurements from IASI-NG together with observations from the multi-angular polarimeter 3MI, both onboard the MetOp-SG satellite since 2025. Such synergism is expected to significantly enhance aerosol speciation capabilities, including the characterization of fine-mode aerosol species primarily constrained by polarimetric measurements.

How to cite: Gomes, C., Cuesta, J., Eremenko, M., Herreras, M., Zhang, Y., Momoi, M., Garcia, A., Lin, W., and Dubovik, O.: Unified Satellite Observation of Thermal Infrared-Absorbing Aerosol Composition, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12101, https://doi.org/10.5194/egusphere-egu26-12101, 2026.

EGU26-12101

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We present TARSA  (Transport Aerosol model for Remote Sensing Applications), a lightweight three-dimensional Eulerian transport model designed for regional studies and tight integration with atmospheric remote-sensing frameworks. TARSA solves a linear conservation equation for generic tracers expressed as mass mixing ratios, including advection by prescribed winds, turbulence-driven vertical diffusion, gravitational settling, and parameterised dry and wet deposition. Nonlinear aerosol microphysics and radiative feedbacks are excluded from the prognostic core, so that all active processes can be written as linear operators acting on a common state vector. The model employs a finite-volume discretisation with first-order upwind advection and implicit time stepping on a structured grid, driven by meteorological fields from the ERA5 reanalysis. All tracers share the same numerical infrastructure, and physical processes can be switched on or off on a per-tracer basis.

We verify and validate TARSA using a hierarchy of experiments. An idealised manufactured Gaussian plume test in a uniform flow demonstrates accurate reproduction of the analytical reference over many orders of magnitude in concentration and confirms near machine-precision mass conservation. A real-world simulation of the ETEX-1 field tracer experiment shows that TARSA captures the large-scale trajectory and arrival sequence of an inert gas over Europe, while reproducing station-wise peak concentrations and dosages within the range reported for established Eulerian models. A short-range consistency experiment against Copernicus Atmosphere Monitoring Service (CAMS) reanalysis fields for carbon monoxide and several aerosol species shows that, when initialised and bounded by reanalysis mixing ratios without additional emissions, TARSA preserves the main spatial patterns and vertical structures of realistic tracers over a synoptic (2–3 day) time scale.

Finally, we demonstrate TARSA’s suitability for satellite-constrained inverse problems with a proof-of-concept retrieval of volcanic sulfur dioxide emissions. Using column SO₂ observations from a polar-orbiting sensor and a linear emission-rate parameterisation, we estimate time-varying source strength by minimising the mismatch between observed and simulated columns under Gaussian observation errors. The inferred emissions reproduce the observed plume timing and downwind structure and provide an end-to-end example of TARSA as a transparent, efficient forward operator for source inversion. Owing to its linear formulation, sparse implicit solver, and modest computational cost, TARSA is well suited for inverse problems and multi-sensor data assimilation; a companion study will describe the corresponding inverse framework in detail.

How to cite: Kuznetsov, K., Dubovik, O., Litvinov, P., Panda, S., and Behera, A.: TARSA: Transport Modeling for Remote Sensing Applications and Volcanic Emission Retrieval, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19553, https://doi.org/10.5194/egusphere-egu26-19553, 2026.

EGU26-19553

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Aerosols are solid and liquid particles present in the atmosphere and play a crucial role in atmospheric composition. They are emitted from natural sources, such as mineral dust, sea spray, biogenic emissions, and volcanic eruptions, as well as anthropogenic sources, including traffic, industrial processes, and biomass burning. The presence of aerosols in the atmosphere can have detrimental effects on air quality, and thereby, human health; however, accurately quantifying these effects remains challenging due to the complexity of the processes involved in the interaction between aerosols and clouds. To better understand and simplify the complexity of aerosol composition, it is necessary to discriminate them into distinct types.

Recent spaceborne lidar, called Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) platform, provided profiles of qualitative identification of the main aerosol type on a global scale. To address these limitations and to provide more insights, we have developed an innovative retrieval approach called AEROTYPro/GRASP (Aerosol Type Profiling/Generalized Retrieval of Atmosphere and Surface Properties) to discriminate the fractions of five types, such as Smoke, Continental, Oceanic, Dust, and Urban Polluted, using three wavelengths (355 nm, 532 nm, and 1064 nm).

In this study, we apply the AEROTYPro/GRASP retrieval approach to discriminate the aerosol concentration vertical profiles for Smoke, Continental, Oceanic, Dust, and Urban polluted using the real airborne lidar measurements, such as backscatter, extinction, and depolarization, obtained from the second-generation NASA Langley Research Center (LaRC), High Spectral Resolution Lidar-2 (HSRL-2) lidar. In addition, the AEROTYPro/GRASP retrieval approach provides the bulk optical and microphysical properties, including aerosol optical depth, single scattering albedo, lidar ratio, absorbing aerosol optical depth, and effective radius. We further evaluated the retrieval approach on several airborne lidar flight transects.

How to cite: Qayyum, F., Cuesta, J., Merdji, A. B., Lopatin, A., Dubovik, O., Ferrare, R., and P. Burton, S.: Quantification of aerosol type vertical profiles from real airborne multiwavelength lidar observations using the AEROTYPro/GRASP approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7893, https://doi.org/10.5194/egusphere-egu26-7893, 2026.

EGU26-7893

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As the MODIS era concludes, new missions like 3MI/EPS-SG and PACE/NASA are now delivering extensive multi-angular, multi-viewing polarimetric data on aerosols. This shift necessitates an evolution in chemistry-transport models (CTMs). Specifically, the successful assimilation of sophisticated aerosol optical properties into the European Centre for Medium-Range Weather Forecasts (ECMWF) CAMS model depends on precise microphysical definitions. This study addresses the existing microphysical inconsistencies that currently prevent the seamless assimilation of remote sensing observations into CTMs.

We compare two generations of the CAMS model using observations from 2008. The first is the Cy42R1 Reanalysis, which incorporates MODIS Aerosol Optical Depth (AOD) at 550 nm through assimilation. The second is the Cy49R2 Forecast, an unconstrained forward simulation. Our analysis uses aerosol properties retrieved from both POLDER measurements and AERONET ground-based data, employing the GRASP algorithm. To ensure a consistent and fair comparison with CAMS assumptions, we adopt a chemical component approach. This involves decomposing the total aerosol loading into its specific components—Black Carbon (BC), Organic Matter (OM), Dust (DU), Sulphate (SU), and Sea Salt (SS)—and fixing their refractive indices and size parameters during the retrieval process.

The CAMS model consistently underestimates AOD compared to both POLDER/GRASP and AERONET, a negative bias present in both its reanalysis and forecast products. Analysis of the Ångström Exponent indicates that the model frequently miscategorizes fine and coarse mode particles. This confusion results in a significant negative bias in CAMS's coarse mode AOD. Additionally, the Single Scattering Albedo (SSA) in CAMS lacks the spectral and spatial variability evident in the POLDER/GRASP retrievals. Further analysis reveals that optical discrepancies in the model's performance are rooted in chemical component-specific errors. The model significantly underrepresents the total column volume concentrations of fine-mode aerosols, especially BC and OM. Furthermore, modeled volume concentrations of SU and SS are negligibly low compared to observational data. For DU, a distinct shift in model strategy is apparent: the older Cy42R1 version underestimates DU volume concentration, while the newer Cy49R2 overestimates it, indicating a transition towards modeling coarser particle emissions. Validation against AERONET data confirms that POLDER/GRASP retrievals offer a reliable benchmark for these comparative assessments.

Current CTMs and retrieval algorithms evidently operate under differing microphysical assumptions. This strongly implies underlying inaccuracies in the assumed aerosol size distributions and refractive indices within these models. The improved DU representation in Cy49R2 is a step forward, but the persistent underestimation of other components limits the model's application for radiative forcing calculations. The subsequent essential step involves harmonization. It is necessary that ECMWF update CAMS aerosol microphysics to incorporate effective radii, size distribution, and refractive indices consistent with state-of-the-art polarimetric retrievals. Establishing a unified definition for aerosol components will enable the next generation of CAMS reanalysis to effectively assimilate data from 3MI and PACE, consequently mitigating uncertainties in global aerosol forcing.

How to cite: Behera, A., Litvinov, P., Herrera, M., Berdina, L., Dubovik, O., Matar, C., Lapyonok, T., Ducos, F., Fuertes, D., and Tishkovets, V.:  Optical and Compositional Biases in ECMWF/CAMS and POLDER/GRASP: Lessons from Aerosol Products Comparison , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13678, https://doi.org/10.5194/egusphere-egu26-13678, 2026.

EGU26-13678

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This study focuses on the use of state-of-the-art ground-based Earth observation measurements, primarily from the AERONET network, to support the development and validation of new aerosol retrieval approaches for current and future multi-platform satellite missions operated by EUMETSAT and Copernicus, such as EPS-SG (Metop-SG), Sentinel-3, Sentinel-5P, CO2M, the geostationary MTG, etc. These missions provide complementary photometric, polarimetric and spectrometric observations covering a broad spectral range from the ultraviolet (UV) to the short-wave infrared (SWIR) and thermal infrared (TIR).

A central objective of this work is to extend AERONET-based aerosol retrievals beyond their standard operational spectral range (440–1020 nm) towards both the UV and the SWIR. Recent developments allow the use of measurements from 340 nm in the UV to 1640 nm, and potentially up to 2200 nm, enabling a more consistent validation of satellite aerosol products across the full spectral domain. Many AERONET sites already provide long-term observations at 380–1640 nm, and a subset also includes measurements at 340 nm, forming a unique reference dataset for this purpose. AERONET-like retrievals at these extended wavelengths enable the evaluation of satellite-derived aerosol properties such as spectral refractive index, single-scattering albedo and size distributions, including fine-mode and super-coarse particles. These products are also essential for improving the treatment of aerosols in trace- and greenhouse- gases retrievals (e.g. NO₂ from UV,  CO₂ and CH₄ from SWIR).

The study presents the first aerosol inversions performed with the GRASP algorithm using this extended spectral range and describes the associated processing chain, including aerosol optical depth (AOD) and sky-radiance preparation, surface reflectance treatment, and inversion metadata. The preliminary results on the data collected at Rotterdam de Slufter during CINDI-3 campaign shows the good agreement in the data preparation and the inversion results derived from developed processing chain with the one from AERONET. This study found the importance of the treatment of the instrumental features such as spectral filter response. The results demonstrate the potential of long-term multi-spectral AERONET observations to strengthen the validation and development of next-generation satellite aerosol and trace- and greenhouse-gas retrievals.

How to cite: Veloso Varela, M., Torres, B., Momoi, M., Matar, C., Dubovik, O., Fuertes, D., Goloub, P., Lopatin, A., Lind, E., Toledano, C., Slutsker, I., and Jafariserajehlou, S.: Optimal use of AERONET measurements in UV-SWIR for the development and validation of satellite aerosol products, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13421, https://doi.org/10.5194/egusphere-egu26-13421, 2026.

EGU26-13421

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Accurately characterizing atmospheric aerosols remains a primary challenge in achieving high precision in satellite retrievals of XCO2 and XCH4. While Shortwave Infrared (SWIR) spectral bands provide optimal sensitivity to greenhouse gas concentrations, Multi-Angular Polarimetric (MAP) measurements represent the most advanced approach for constraining aerosol and surface properties. Consequently, upcoming Copernicus missions, such as CO2M and MetOp-SG (hosting Sentinel-5/UVNS spectrometer and 3MI polarimeter), are equipped to exploit the synergy between these measurement types.

In this context, we present  an open-source, full-physics retrieval algorithm for GHG retrievals  to demonstrate its capabilities through the synergistic inversion of SWIR spectrometric (i.e., S5-UVNS and CO2M/CO2I spectrometers) and multi-angle polarimetric data (3MI and CO2M/MAP). The core of this retrieval approach is the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm (Dubovik et al., 2021). GRASP relies on rigorous radiative transfer modeling and statistically optimized fitting (Multi-Term Least Squares) to process a wide range of optical instruments. While originally designed for MAP applications (e.g., POLDER, 3MI; Li et al., 2019; Chen et al., 2020), the approach has been extended to combine MAP and SWIR spectrometric measurements, accounting for gas absorption, offering a simultaneous retrieval of detailed aerosol microphysics and surface properties alongside with columnar XCO2 and XCH4.

In this work the GRASP algorithm has been successfully adapted to perform gas retrievals, allowing for the robust simultaneous inversion of aerosol properties and XCO2 and XCH4. We demonstrate the capabilities of this new GRASP inversion scheme through synthetic datasets representing the Sentinel-5+3MI and CO2M synergies. These synthetic experiments highlight that incorporating MAP measurements yields significantly improved accuracy for XCO2 and XCH4 compared to standalone spectrometer retrievals. This project has been funded through the OPERA-S5 project (OPEn platform for the Retrieval of Aerosol and CO2 from S5), an ESA-funded initiative developed by GRASP SAS company and SRON. This development lays the groundwork for the operational processing of future multi-sensor satellite missions, offering a powerful tool for enhanced global monitoring of greenhouse gases and aerosol interactions.

References

Chen, C., Dubovik, O., Fuertes, D., Litvinov, P., Lapyonok, T., Lopatin, A., ... & Federspiel, C. (2020). Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring. Earth System Science Data Discussions, 2020, 1-108.

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.

Li, Lei; Derimian, Yevgeny; Chen, Cheng; Zhang, Xindan; Che, Huizheng; Schuster, Gregory L.; Fuertes, David; Litvinov, Pavel; Lapyonok, Tatyana; Lopatin, Anton; Matar, Christian; Ducos, Fabrice; Karol, Yana; Torres, Benjamin; Gui, Ke; Zheng, Yu; Liang, Yuanxin; Lei, Yadong; Zhu, Jibiao; Zhang, Lei; Zhong, Junting; Zhang, Xiaoye; Dubovik, Oleg Climatology of aerosol component concentrations derived from multi-angular polarimetric POLDER-3 observations using GRASP algorithm. Earth Syst. Sci. Data, vol. 14, no. 7, pp. 3439–3469, 2022, ISSN: 1866-3516.

How to cite: Rejano, F., Herreras-Giralda, M., Momoi, M., Lin, W., García-Gómez, A., Barr, A., Landgraf, J., Lippert, F., Litvinov, P., Dubovik, O., Fuertes, D., Gasbarra, D., Veihelmann, B., and Malina, E.: Joint retrieval of aerosols, XCO2, and XCH4 from polarimetric and spectrometric data using GRASP, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18466, https://doi.org/10.5194/egusphere-egu26-18466, 2026.

EGU26-18466

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We study the seasonal variability of aerosols over Changchun, Northeast China, using ground-based observations from the recently established AERONET Changchun_JLU site. A sun-lunar-sky photometer was installed in the city in October 2024. The seasonal variability of key aerosol optical properties, including aerosol optical depth and the Ångström exponent, is analyzed, along with the influence of extreme events such as biomass burning and mineral dust transport. Aerosol types are first examined using the traditional AOD–AE classification scheme, which is commonly applied for broad aerosol type identification. In addition, a more advanced aerosol classification is performed using a hybrid approach that combines clustering centroids derived from global AERONET data with a Nearest-Center Matching (NCM) algorithm. This method uses data on the Single Scattering Albedo at 440 nm and the Extinction Ångström Exponent at 440-870 nm. The analysis focuses on how aerosol types vary seasonally over Changchun and evaluates the effectiveness of the clustering-centroid combined with the NCM approach in a cold urban environment. The results highlight the influence of human activities, including residential heating, waste burning, and biomass burning, as well as regional transport processes, particularly mineral dust transport from the Taklamakan and Gobi deserts, on the seasonal distribution of aerosols.

How to cite: Han, W., Yukhymchuk, Y., Milinevsky, G., and Chen, P.: Variability of aerosols over Changchun, Northeast China, based on new AERONET site observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9522, https://doi.org/10.5194/egusphere-egu26-9522, 2026.

EGU26-9522

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Aerosols affect climate and air quality, but it remains challenging to simultaneously quantify their optical properties, vertical distribution, chemical components, and associated direct radiative effects using any single observing system. Here, we present a ground-based synergy retrieval study in Central China (Wuhan University; 30°32ʹN, 114°21ʹE) combining a CE-318T sun photometer, a 532-nm Mie lidar, and surface black-carbon measurements (AE-31) from July 2021 to August 2022, using the GRASP/GARRLiC framework with a component-based aerosol model (BC, BrC, dust, iron oxide, water-soluble salts, and aerosol water). The joint retrieval captures strong seasonality: winter shows the highest aerosol loading (AOD ~0.7 at 440 nm) with enhanced absorption (SSA <0.92) and elevated near-surface BC, while spring is strongly influenced by transported dust with a characteristic extinction peak near ~2.5 km and relatively high SSA; summer and autumn feature lower mean AOD but episodic enhancements consistent with regional transport/biomass burning. Retrieved annual column mass concentrations indicate low BC burden (2.49 mg m⁻²) yet disproportionate warming, with BC contributing +9.27 W m⁻² to shortwave DARE at the top of atmosphere (BrC: +0.10 W m⁻²), whereas total aerosols cool the system overall (−12.28 W m⁻² at TOA; −39.33 W m⁻² at the surface). Incorporating lidar-constrained vertical structure also improves agreement of retrieved surface BC versus measurements (R = 0.56), highlighting the value of synergy observations for component-aware radiative impact assessments and for complementing reanalysis products.

How to cite: Ma, Y. and Jin, S.: Characterizing Aerosol Optical Properties and DirectRadiative Effects From the Perspective of Components: A Synergy Retrieval Study Based on Sun Photometer andLidar in Central China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21950, https://doi.org/10.5194/egusphere-egu26-21950, 2026.

EGU26-21950

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Aerosols play an important role in atmospheric chemistry and physics. They also negatively affect human and ecosystem health. Although the aerosol in lower atmosphere is essentially important, accurately characterizing their vertical distribution in the lower troposphere remains challenging due to the "overlap" limitations of ground-based lidars. Aerosol vertical distribution in the lower troposphere (below 3 km) is often monitored using MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) technique 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 aerosol profile retrievals from synergetic ground-based observations by AERONET sun-sky photometer, Pandonia Global Network spectrometer and lidar/ceilometer system. 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 the retrieval of vertical aerosol properties from multi-axis differential slant column densities of O₂O₂, lidar signal (i.e., ceilometer, EALINET, ADNET, etc.), and radiance measurements (almucantar/hybrid scanning). This presentation demonstrates the developed approach applied for several collocated sites (i.e., Rotterdam de Slufter, Warsaw, etc) and discusses potential advantages of retrieval of aerosol vertical profiles from synergy of the MAX-DOAS, AERONET, and lidar.

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.

How to cite: Momoi, M., Lopatin, A., Stöckhardt, M., Lind, E., Veloso, M., Szczepanik, D., Dubovik, O., Herreras-Giralda, M., Torres, B., Lapyonok, T., Kreuter, A., Cede, A., Janicka, L., and Stachlewska, I.: Aerosol profiling through bottom-to-top atmosphere from the synergetic observations of sun-sky photometer, spectrometer and lidar, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9623, https://doi.org/10.5194/egusphere-egu26-9623, 2026.

EGU26-9623

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NASA's PACE (Plankton, Aerosol, Clouds, and ocean Ecosystem) mission was successfully launched on February 8, 2024. PACE provided coordinated complementary observations from three key instruments: HARP2, SPEXone and OCI. Both HARP2 and SPEXone are advanced multi-angular polarimeters that measure both the intensity and polarization of reflected solar light, providing high sensitivity to aerosol characteristics such as particle size, type, and absorption etc. OCI, on the other hand, is a hyperspectral radiometer designed to measure ocean color and atmospheric properties across the UV to SWIR, providing high resolution data for ocean and atmospheric applications.

This study exploits the complementarity of all three PACE instruments to develop advanced aerosol and surface synergy products using the GRASP algorithm. As a first step, we demonstrated the correctness and robustness of GRASP for each instrument individually by designing and implementing technical and methodological developments, including harmonization of data format, accuracy specifications of each instrument, selection of channels for spectrometric observations, corrections for gaseous absorption, etc. Validation of aerosol and surface properties retrievals from each sensor have shown encouraging performance, highlighting the strong potential of PACE/GRASP products for accurate aerosol and surface characterization.

Building on these results, we implemented a synergistic retrieval combining all 3 sensors to maximize information content and improve the retrieval coverage and accuracy. HARP2 provides up to 60 viewing angles at 4 wavelengths with two-day global coverage, its high information content is crucial for determining aerosol particle size and shape; SPEXone, provides continuous spectral measurements from 385 to 770 nm, which are particularly valuable for constraining aerosol absorption; OCI provides wide global coverage and broad spectral coverage from 340 to 890 nm continuously with discrete bands in the near-infrared. Synergy strategies were developed following the experience from the SYREMIS project, accounting for differences in information content and calibration accuracy among the instruments and weighting the measurements accordingly. Overall, the results demonstrate that combining measurements from all three PACE instruments significantly improves the retrieval of aerosol properties and surface BRDF compared to single-instrument approach.

How to cite: Li, C., Dubovik, O., Puthukkudy, A., Lopatin, A., Litvinov, P., Martins, V., Fuertes, D., Gómez López, J., Gomez, A., Antuña-Sánchez, J.-C., and Matar, C.: Synergistic Retrieval of aerosol and surface properties from PACE polarimetric and spectrometric observations using GRASP algorithm , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7739, https://doi.org/10.5194/egusphere-egu26-7739, 2026.

EGU26-7739

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Oceans remain severely under-sampled in aerosol optical properties, limiting our ability to assess marine aerosol–climate feedbacks, long-range transport and to validate satellite products over two-thirds of Earth’s surface. The Sun–sky–lunar photometer CIMEL CE318-T has been successfully adapted for autonomous shipborne operation through the PHOTONS Observation Service (ACTRIS, Univ. Lille, CNRS) in collaboration with CIMEL and within ACTRIS-CARS activities. The system is fully compatible with AERONET processing. Here we summarize recent developments and multi-year results supporting the deployment of a global network of automatic ship-based photometers.

Since 2021, a CE318-T has operated continuously on the research vessel (R.V.) Marion Dufresne under the framework of MAP-IO program. Between July 2021 and June 2024, it collected >25,000 Level 1.5 measurements in the southwestern Indian Ocean, with mean AOD (Aerosol Optical Depth) of 0.09 ± 0.07 (440 nm) and 0.05 ± 0.03 (870 nm), and EAE (Extinction Angstrom Exponent) of 0.7 ± 0.4, typical of clean marine conditions. A biomass-burning aerosol (BBA) event allowed retrieval of microphysical properties (size distribution, refractive index), showing the capability of the system under real ship-motion.

During TRANSAMA campaign (La Réunion–Barbados, Apr–May 2023), two CE318-T photometers combined with a micropulse lidar aboard R.V. Marion Dufresne provided complementary column and vertical information. Despite low AOD (0.08 ± 0.04 at 440 nm) in the remote South Atlantic, the lidar detected transported continental layers not evident from column-integrated data alone. Photometer intercomparison showed excellent agreement (R > 0.96; RMSE = 0.005–0.008). Motion-induced degradation on data quality highlighted the need for the ongoing instrumental tests, using a motion-simulation hexapode platform.

A second permanent site aboard the R.V. Gaia Blu (CNR, Italy) has collected >20,000 measurements mainly in the Mediterranean since Feb 2024. Mean AOD (0.19 ± 0.14 at 440 nm) and EAE (1 ± 0.4) reflect more variable aerosol regimes, including BBA and Saharan dust. Comparisons with nearby AERONET ground-based stations validated retrieval quality. In addition, the installation of a 3D scanning lidar (Sep 2025) further enhances observations of aerosol vertical structure and air–sea interactions.

These first results demonstrate the capability of ship-based photometers, and their synergy with lidar, to fill critical observational gaps over the oceans. Improved data acquisition strategies addressing vessel structure and motion are ongoing. To date, five ship-photometers operate across major maritime regions: R.V. Marion Dufresne-France (Indian Ocean), R.V. Gaia Blu-Italy (Mediterranean Sea), R.V. Sarmiento de Gamboa-Spain (Atlantic Ocean), R.V. Perseverance-France (currently Pacific Ocean), and MS Richard With-Norway (Arctic/Norwegian coast). These installations represent a major European step toward the first global network of automatic shipborne photometers to improve aerosol characterization over remote oceans and support satellite CAL/VAL.

How to cite: Sanchez Barrero, M. F., Torres, B., Blarel, L., Dubois, G., Canon, A., Goloub, P., Maupin, F., Metzger, J. M., Tulet, P., Slutsker, I., Marbach, T., Brizzi, G., Liberti, G. L., Langone, L., Gonzalez, R., Toledano, C., Etienne, J. L., Leclout, G., Fjæraa, A. M., and Jaccard, P. F. and the co-authors: Automatic Ship-Based Photometers for Enhanced Aerosol Characterization Over the Open Ocean: Towards a Global Network, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20297, https://doi.org/10.5194/egusphere-egu26-20297, 2026.

EGU26-20297

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