Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 19, issue 9
Articles | Volume 19, issue 9
https://doi.org/10.5194/amt-19-3095-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-3095-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 9
Research article
 | 
11 May 2026
Research article |  | 11 May 2026

A hybrid optimal estimation and machine learning approach to predict atmospheric composition

Frank Werner, Kevin W. Bowman, Seungwon Lee, Joshua L. Laughner, Vivienne H. Payne, and James L. McDuffie

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Short summary
We developed a hybrid machine learning-optimal estimation retrieval system that efficiently and accurately mimics operational retrieval results. Crucially, this algorithm also predicts critical diagnostic variables including observation operators needed for comparison with independent data and ingestion into downstream chemical data assimilation models.
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