Articles | Volume 18, issue 20
https://doi.org/10.5194/amt-18-5619-2025
https://doi.org/10.5194/amt-18-5619-2025
Research article
 | 
21 Oct 2025
Research article |  | 21 Oct 2025

Extension of the Complete Data Fusion algorithm to tomographic retrieval products

Cecilia Tirelli, Simone Ceccherini, Samuele Del Bianco, Bernd Funke, Michael Höpfner, Ugo Cortesi, and Piera Raspollini

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Cited articles

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Aires, F., Aznay, O., Prigent, C., Paul, M., and Bernardo, F.: Synergistic multi-wavelength remote sensing versus a posteriori combination of retrieved products: Application for the retrieval of atmospheric profiles using MetOp-A, J. Geophys. Res.-Atmos., 117, D18304, https://doi.org/10.1029/2011JD017188, 2012. a
Andrey-Andrés, J., Fourrié, N., Guidard, V., Armante, R., Brunel, P., Crevoisier, C., and Tournier, B.: A simulated observation database to assess the impact of the IASI-NG hyperspectral infrared sounder, Atmos. Meas. Tech., 11, 803–818, https://doi.org/10.5194/amt-11-803-2018, 2018. a
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Short summary
The Complete Data Fusion is an a posteriori method used to combine remote sensing products from independent observations of the same or proximate air masses. In this study, we extend the algorithm’s applicability to two-dimensional products, testing it with simulated ozone datasets from nadir and limb measurements. Our results show that the exploitation of the tomographic capabilities of future atmospheric sensors maximizes the information extracted from complementary datasets.
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