Articles | Volume 14, issue 5
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, Can Li, Nickolay A. Krotkov, Pascal Hedelt, Diego G. Loyola, Russell R. Dickerson, and Robert Spurr

Data sets

Goddard Earth Sciences Data and Information Services Center (GES DISC) NASA

Retrieval of sulphur dioxide from the infrared atmospheric sounding interferometer (IASI) ( L. Clarisse, D. Hurtmans, C. Clerbaux, J. Hadji-Lazaro, Y. Ngadi, and P.-F. Coheur

CALIPSO Lidar Level 1B profile data, V4-10 NASA/LARC/SD/ASDC


Copernicus Sentinel-5P (processed by ESA, TROPOMI Level 2 Sulphur Dioxide Total Column. Version 02 European Space Agency

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.