Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 13, issue 10
Articles | Volume 13, issue 10
https://doi.org/10.5194/amt-13-5537-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-5537-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 13, issue 10
Research article
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16 Oct 2020
Research article | Highlight paper |  | 16 Oct 2020

A feasibility study to use machine learning as an inversion algorithm for aerosol profile and property retrieval from multi-axis differential absorption spectroscopy measurements

Yun Dong, Elena Spinei, and Anuj Karpatne

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Short summary
This paper is about a feasibility study of applying a machine learning technique to derive aerosol properties from a single MAX-DOAS sky scan, which detects sky-scattered UV–visible photons at multiple elevation angles. Evaluation of retrieved aerosol properties shows good performance of the ML algorithm, suggesting several advantages of a ML-based inversion algorithm such as fast data inversion, simple implementation and the ability to extract information not available using other algorithms.
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