Articles | Volume 14, issue 5
Atmos. Meas. Tech., 14, 3673–3691, 2021
https://doi.org/10.5194/amt-14-3673-2021
Atmos. Meas. Tech., 14, 3673–3691, 2021
https://doi.org/10.5194/amt-14-3673-2021
Research article
20 May 2021
Research article | 20 May 2021

Volcanic SO2 effective layer height retrieval for the Ozone Monitoring Instrument (OMI) using a machine-learning approach

Nikita M. Fedkin et al.

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Cited articles

Bhartia, P. K.: OMI Algorithm Theoretical Basis Document Volume II, OMI Ozone Products, ATBD-OMI-02, 2002. 
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Carn, S. A., Fioletov, V. E., McLinden, C. A., Li, C., and Krotkov, N. A.: A decade of global volcanic SO2 emissions measured from space, Sci. Rep.-UK, 7, 44095, https://doi.org/10.1038/srep44095, 2017. 
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Short summary
This study presents a new volcanic sulfur dioxide (SO2) layer height retrieval algorithm for the Ozone Monitoring Instrument (OMI). We generated a large spectral dataset with a radiative transfer model and used it to train neural networks to predict SO2 height from OMI radiance data. The algorithm is fast and takes less than 10 min for a single orbit. Retrievals were tested on four eruption cases, and results had reasonable agreement (within 2 km) with other retrievals and previous studies.