Articles | Volume 17, issue 9
https://doi.org/10.5194/amt-17-3029-2024
https://doi.org/10.5194/amt-17-3029-2024
Research article
 | 
17 May 2024
Research article |  | 17 May 2024

Deep-Pathfinder: a boundary layer height detection algorithm based on image segmentation

Jasper S. Wijnands, Arnoud Apituley, Diego Alves Gouveia, and Jan Willem Noteboom

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Cited articles

Allabakash, S., Yasodha, P., Bianco, L., Venkatramana Reddy, S., Srinivasulu, P., and Lim, S.: Improved boundary layer height measurement using a fuzzy logic method: Diurnal and seasonal variabilities of the convective boundary layer over a tropical station, J. Geophys. Res.-Atmos., 122, 9211–9232, https://doi.org/10.1002/2017JD027615, 2017. a
Bonin, T. A., Carroll, B. J., Hardesty, R. M., Brewer, W. A., Hajny, K., Salmon, O. E., and Shepson, P. B.: Doppler lidar observations of the mixing height in Indianapolis using an automated composite fuzzy logic approach, J. Atmos. Ocean. Tech., 35, 473–490, https://doi.org/10.1175/JTECH-D-17-0159.1, 2018. a
Bosveld, F. C.: The Cabauw in-situ observational program 2000 – present: instruments, calibrations and set-up, Technical Report TR-384, Royal Netherlands Meteorological Institute (KNMI), De Bilt, https://cdn.knmi.nl/knmi/pdf/bibliotheek/knmipubTR/TR384.pdf (last access: 30 August 2023), 2020. a
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Short summary
The mixing of air in the lower atmosphere influences the concentration of air pollutants and greenhouse gases. Our study developed a new method, Deep-Pathfinder, to estimate mixing layer height. Deep-Pathfinder analyses imagery with aerosol observations using artificial intelligence techniques for computer vision. Compared to existing methods, it improves temporal consistency and resolution and can be used in real time, which is valuable for aviation, forecasting, and air quality monitoring.