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.

Data sets

Goddard Earth Sciences Data and Information Services Center (GES DISC) NASA https://earthdata.nasa.gov/eosdis/daacs/gesdisc

Retrieval of sulphur dioxide from the infrared atmospheric sounding interferometer (IASI) (https://iasi.aeris-data.fr/SO2/) L. Clarisse, D. Hurtmans, C. Clerbaux, J. Hadji-Lazaro, Y. Ngadi, and P.-F. Coheur https://doi.org/10.5194/amt-5-581-2012

CALIPSO Lidar Level 1B profile data, V4-10 NASA/LARC/SD/ASDC https://doi.org/10.5067/CALIOP/CALIPSO/LID_L1-STANDARD-V4-10

CALIPSO LIDAR BROWSE IMAGES NASA https://www-calipso.larc.nasa.gov/products/lidar/browse_images/production

Copernicus Sentinel-5P (processed by ESA, TROPOMI Level 2 Sulphur Dioxide Total Column. Version 02 European Space Agency https://doi.org/10.5270/S5P-74eidii

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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.