Articles | Volume 19, issue 13
https://doi.org/10.5194/amt-19-4415-2026
https://doi.org/10.5194/amt-19-4415-2026
Research article
 | 
03 Jul 2026
Research article |  | 03 Jul 2026

Cloud fields and aerosol classification with lidar using advanced AI approach

Yonatan Peleg, Lior Zeida-Cohen, Imri Tzror, Johannes Bühl, Albert Ansmann, Alexandra Chudnovsky, and Zohar Yakhini

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Cited articles

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Ansmann, A., Bühl, J., and Peleg, Y.: Cloud Fields Identification with Lidar using advanced AI approach – CloudNet/PollyXT, Limassol 2016–2018, Zenodo [data set], https://doi.org/10.5281/zenodo.17424878, 2025. a
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Short summary
Mapping the vertical structure of aerosols and clouds is vital for climate science. We developed an AI model that reconstructs full atmospheric profiles from standard lidar data, even above signal attenuation. It accurately classifies aerosol and cloud types, capturing key atmospheric features. This cost-effective approach extends beyond sparse Cloudnet sites, enhancing monitoring and supporting improved weather and climate models.
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