EGU General Assembly 2020
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Application of nighttime fog detection method using MSG8 SEVIRI in an arid environment

Michael Weston1,2 and Marouane Temimi1
Michael Weston and Marouane Temimi
  • 1Khalifa University, Department of Civil Infrastructure and Environmental Engineering, Abu Dhabi, United Arab Emirates
  • 2North-West University, School of Geo- and Spatial Science, South Africa

The detection of fog and low cloud (FLC) from satellite data remains challenging despite advances in methodologies and technology. Current methods make use of one or a combination of channel differencing from satellite instruments, surface observations, model data or artificial intelligence. An alternative to the brightness temperature difference method was developed for the GOES-R advanced baseline imager (ABI) which makes use of a channel ratio instead of a channel difference. We apply this method, the so called pseudo emissivity of the 3.9 µm channel, to SEVIRI MSG8 data over the United Arab Emirates, a desert region of the Arabian Peninsula. Low cloud is removed using temperature difference between ERA5 land surface temperature and 10.8 µm channel brightness temperature. Visual inspection of the final fog only mask shows that this method works well over this region. Verification at three sites where METAR data is available returned POD (FAR) of 0.77 (0.27), 0.50 (0.65) and 0.83 (0.26) respectively. Application of this method can be further developed to represent seasonal fog distribution and frequency across the United Arab Emirates.

How to cite: Weston, M. and Temimi, M.: Application of nighttime fog detection method using MSG8 SEVIRI in an arid environment , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4677,, 2020.


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