Abstract
Fog is a hazardous weather event that can endanger navigation, aviation, and transportation. While human has several limitations in detecting and forecasting offshore fog, satellite remote sensing offers cost-effective images. In this study, a probability-based daytime sea fog detection algorithm, applied to geostationary operational environmental satellite (GOES) 16 satellite data over the Grand Banks offshore Eastern Canada, is presented and compared with the National Oceanographic and Atmospheric Administration (NOAA)'s Low Instrument Flight Rules (LIFR) probability map. Initially, clear-sky and ice cloud classes were delineated in the GOES-16 image and then the remaining pixels were assigned a fog probability by conducting small droplet proxy, spatial homogeneity, and temperature difference tests. Moreover, a green band was linearly interpolated using the first three bands of GOES-16 images to generate pseudotrue color composites. The resulting maps were evaluated both during an extended sea fog event and using several statistical measures. The average detection probability for the observed advection fog events was 66% for the proposed method, while that for NOAA's LIFR map was 38%. Furthermore, by thresholding the generated maps at the probability of 60%, the false alarm rate, probability of detection, hit rate, and Hanssen–Kuiper skill score were 0.09, 0.77, 0.83, and 0.68, respectively. The proposed method is operationally being used in this region to detect and monitor sea fog, facilitating safe navigation and aviation. This is the first study that uses GOES-16 for daytime fog detection and discusses a satellite-based solution for fog modeling in Grand Banks, NL.
Highlights
F OG is a hazardous weather phenomenon that appears when water vapor near the surface is condensed to form suspended water droplets [1]
A probability-based algorithm was introduced for daytime sea fog detection that utilizes geostationary operational environmental satellite (GOES)-16 images and modeled sea surface temperature (SST) data
Pseudocolor composites were generated by interpolating green band using the first three bands of GOES-16
Summary
F OG is a hazardous weather phenomenon that appears when water vapor near the surface is condensed to form suspended water droplets [1]. Considering the difference between the brightness temperature of clouds and clear sky or between two bands of a satellite sensor is another method for sea fog and low stratus (FLS) detection. National Oceanographic and Atmospheric Administration (NOAA) has developed a comprehensive approach for global fog detection using geostationary operational environmental satellite (GOES) 16 imagery that has been fully described in [19]. In this method, several physical characteristics of fog, such as spatial uniformity and the brightness temperature difference between the cloud and surface and between the bands centered at 3.9 and 11.2 μm, have been considered.
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