Preprints
https://doi.org/10.5194/essd-2026-327
https://doi.org/10.5194/essd-2026-327
14 Jul 2026
 | 14 Jul 2026
Status: this preprint is currently under review for the journal ESSD.

Fit-for-purpose assessment of satellite aerosol and cloud datasets for constraining and monitor aerosol–cloud interactions

Marta Luffarelli, Nicolas Misk, Analy Baltodano, Thomas Popp, Stefan Kinne, Ulrike Stöffelmair, Michael Schulz, Jan Griesfeller, Ove W. Haugvalstad, Martin Stengel, Sarah Brüning, Gareth Thomas, Elisa Carboni, Daniel Robbins, and Michael Eisinger

Abstract. Aerosol-cloud interactions (ACI) remain one of the dominant sources of uncertainty in estimates of anthropogenic effective radiative forcing. Robust observational constraints on these processes require satellite datasets that are not only physically consistent but also demonstrably fit for the intended scientific purpose. Within the framework of the "Satellite observations to improve our understanding of aerosol–cloud interactions" (SATACI) project, we perform a comprehensive fit-for-purpose (F4P) assessment of existing satellite aerosol and cloud datasets used to (i) quantify aerosol indirect effects on liquid and mixed-phase clouds and (ii) support the feasibility study of a novel aerosol–cloud climate indicator. For each application, scientific and technical requirements are defined in terms of variables, spatial and temporal resolution, co-location capability, validation evidence, and the availability of uncertainty information. Candidate datasets from geostationary and polar-orbiting satellites are evaluated against these criteria, including datasets resulting from the ESA Climate Change Initiative and Copernicus Climate Change Service. Overall, the study highlights the importance of application-specific dataset evaluation and emphasises the complementary roles of geostationary and polar-orbiting satellite observations. While geostationary sensors provide new opportunities to investigate the temporal evolution of aerosol–cloud systems, polar-orbiting climate data records remain essential for long-term monitoring and climate indicator development. Together, these observations provide a robust basis for advancing satellite-based constraints on aerosol–cloud interactions.

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Marta Luffarelli, Nicolas Misk, Analy Baltodano, Thomas Popp, Stefan Kinne, Ulrike Stöffelmair, Michael Schulz, Jan Griesfeller, Ove W. Haugvalstad, Martin Stengel, Sarah Brüning, Gareth Thomas, Elisa Carboni, Daniel Robbins, and Michael Eisinger

Status: open (until 20 Aug 2026)

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Marta Luffarelli, Nicolas Misk, Analy Baltodano, Thomas Popp, Stefan Kinne, Ulrike Stöffelmair, Michael Schulz, Jan Griesfeller, Ove W. Haugvalstad, Martin Stengel, Sarah Brüning, Gareth Thomas, Elisa Carboni, Daniel Robbins, and Michael Eisinger

Data sets

MODIS/Terra Collection 6.1 Dark Target R. Levy et al. https://doi.org/10.5067/MODIS/MOD04_L2.061

Cloud properties global gridded monthly and daily data from 1979 to present derived from satellite observations Copernicus Climate Change Service (C3S), Climate Data Store (CDS) https://doi.org/10.24381/cds.68653055

CLAAS-3: CM SAF CLoud property dAtAset using SEVIRI - Edition 3 J. F. Meirink et al. https://doi.org/10.5676/EUM_SAF_CM/CLAAS/V003

Model code and software

SEVIRI_ML D. Philipp et al. https://github.com/danielphilipp/seviri_ml

Optimal Retrieval of Aerosol and Cloud (ORAC) R. G. Grainger et al. https://github.com/ORAC-CC/orac

Marta Luffarelli, Nicolas Misk, Analy Baltodano, Thomas Popp, Stefan Kinne, Ulrike Stöffelmair, Michael Schulz, Jan Griesfeller, Ove W. Haugvalstad, Martin Stengel, Sarah Brüning, Gareth Thomas, Elisa Carboni, Daniel Robbins, and Michael Eisinger
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Short summary
Understanding how aerosol particles affect clouds is essential for improving climate predictions, yet current satellite data are not always reliable or suitable for this purpose. This study evaluates major datasets for analysing aerosol effects on liquid clouds, dust-driven cloud glaciation, and a potential climate indicator to monitor aerosol-cloud interactions.
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