Articles | Volume 19, issue 9
https://doi.org/10.5194/amt-19-3095-2026
https://doi.org/10.5194/amt-19-3095-2026
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

Model code and software

Zenodo repository for A hybrid optimal estimation and machine learning approach to predict atmospheric composition Frank Werner et al. https://doi.org/10.5281/zenodo.16968703

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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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