Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 18, issue 15
Articles | Volume 18, issue 15
https://doi.org/10.5194/amt-18-3747-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-3747-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 15
Research article
 | 
11 Aug 2025
Research article |  | 11 Aug 2025

Hourly surface nitrogen dioxide retrieval from GEMS tropospheric vertical column densities: benefit of using time-contiguous input features for machine learning models

Janek Gödeke, Andreas Richter, Kezia Lange, Peter Maaß, Hyunkee Hong, Hanlim Lee, and Junsung Park

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Short summary
The Korean Geostationary Environmental Monitoring Spectrometer (GEMS) monitors trace gases over Asia, e.g., NO2. GEMS provides hourly data, improving the time resolution compared to the daily overpasses by other satellites. For the prediction of hourly surface NO2 over South Korea from GEMS observations and meteorological data, this study shows that machine learning models benefit from this higher time resolution. This is achieved by using observations from previous hours as additional inputs.
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