Articles | Volume 18, issue 22
https://doi.org/10.5194/gmd-18-8777-2025
https://doi.org/10.5194/gmd-18-8777-2025
Review and perspective paper
 | Highlight paper
 | 
20 Nov 2025
Review and perspective paper | Highlight paper |  | 20 Nov 2025

Applications of Machine Learning and Artificial Intelligence in Tropospheric Ozone Research

Sebastian H. M. Hickman, Makoto M. Kelp, Paul T. Griffiths, Kelsey Doerksen, Kazuyuki Miyazaki, Elyse A. Pennington, Gerbrand Koren, Fernando Iglesias-Suarez, Martin G. Schultz, Kai-Lan Chang, Owen R. Cooper, Alex Archibald, Roberto Sommariva, David Carlson, Hantao Wang, J. Jason West, and Zhenze Liu

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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary

Cited articles

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Executive editor
I agree on publishing this manuscript as a Review and perspective paper.
Short summary
Machine learning is being more widely used across environmental and climate science. This work reviews the use of machine learning in tropospheric ozone research, focusing on three main application areas in which significant progress has been made. Common challenges in using machine learning across the three areas are highlighted, and future directions for the field are indicated.
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