Abstract
Fog degrades horizontal visibility causing significant adverse impacts on transport systems. The detection of fog from satellite data remains challenging especially in the presence of higher clouds, dust, mist, or unknown underlying soil conditions. Observations from Meteosat second generation Spinning-Enhanced Visible and Infrared Imager (MSG SEVIRI) over the United Arab Emirates (UAE), an arid area on the Arabian Peninsula, from 2016 to 2018 (two fog seasons) are used in this study. We implement an adaptive threshold-based technique using pseudo-emissivity values to detect nocturnal fog from SEVIRI. The method allows the threshold to vary spatially and temporally. Low clouds are detected with the analysis of the vertical temperature gradient. Fog classification was verified against four stations in the UAE, namely Abu Dhabi, Dubai, Al Ain, and Al Maktoum, where visibility and meteorological observations are available. The probability of detection (POD) (false alarm ratio (FAR)) was 0.81 (0.40), 0.83 (0.50), 0.83 (0.33), and 0.77 (0.44) at Abu Dhabi, Dubai, Al Ain, and Al Maktoum, respectively. In addition, the spatial frequency of fog is presented, which provides new insights into the fog dynamics in the region.
Highlights
The detection of fog and low cloud (FLC) from satellite data remains challenging despite advances in methodologies and technology
In this paper we present the assessment of the pseudo-emissivity method for nighttime fog detection using the Spinning-Enhanced Visible and Infrared Imager (SEVIRI) instrument from Meteosat-10
The method is similar to the one proposed for the GOES-R Advanced Baseline Imager (ABI) which is largely untested with SEVIRI data
Summary
The detection of fog and low cloud (FLC) from satellite data remains challenging despite advances in methodologies and technology. Satellite products remain beneficial and informative in areas where there is a low density of observations, which is often the case in desert areas [1]. In the case of dense ground observation networks, fog detection could rely on surface observations. A combination of satellite- and ground-based observation is possible to enhance fog detection and tracking. In such contexts, ground observations could be invaluable in the case of obstruction by higher clouds [2] or in the presence of mist or haze, which could lead to false alarms in the satellite products
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