Articles | Volume 18, issue 8
https://doi.org/10.5194/amt-18-1927-2025
https://doi.org/10.5194/amt-18-1927-2025
Research article
 | 
29 Apr 2025
Research article |  | 29 Apr 2025

Algorithm for continual monitoring of fog based on geostationary satellite imagery

Babak Jahani, Steffen Karalus, Julia Fuchs, Tobias Zech, Marina Zara, and Jan Cermak

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Cited articles

Aminou, D. M. A.: MSG's SEVIRI Instrument, ESA Bull., 15–17, https://www.esa.int/esapub/bulletin/bullet111/chapter4_bul111.pdf (last access: 22 April 2025), 2002. 
Andersen, H. and Cermak, J.: First fully diurnal fog and low cloud satellite detection reveals life cycle in the Namib, Atmos. Meas. Tech., 11, 5461–5470, https://doi.org/10.5194/amt-11-5461-2018, 2018. 
Cermak, J.: SOFOS – A New Satellite-based Operational Fog Observation Scheme, PhD Thesis, Philipps-Universität Marbg, https://archiv.ub.uni-marburg.de/diss/z2006/0149 (last access: 22 April 2025), 2006. 
Cermak, J.: Fog and Low Cloud Frequency and Properties from Active-Sensor Satellite Data, Remote Sens., 10, 1209, https://doi.org/10.3390/rs10081209, 2018. 
Cermak, J. and Bendix, J.: Dynamical nighttime fog/low stratus detection based on Meteosat SEVIRI data: A feasibility study, Pure Appl. Geophys., 164, 1179–1192, https://doi.org/10.1007/s00024-007-0213-8, 2007. 
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Short summary
Fog and low stratus (FLS) are both persistent clouds close to the Earth's surface. This study introduces a new machine-learning-based algorithm developed for the Meteosat Second Generation geostationary satellites that can provide a coherent and detailed view of FLS development over large areas over the 24 h day cycle.
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