COMS/GOCI Marine Fog Detection Algorithm Combined with Himawari-8/AHI

Abstract

Marine fog is one of the most dangerous weather hazards that threaten coastal and marine areas. However, marine fog monitoring is difficult because of the lack of in-situ observation data. Accordingly, satellite data has been considered a valuable information for monitoring fog above the ocean. In this study, COMS/GOCI marine fog detection algorithm combined with Himawari-8/AHI was developed based on Decision Tree technique. Hourly available and fine visible channel measurement of GOCI and spatial pattern index were mainly used to detect marine fog in the daytime. In addition, cloud top height data from Himawari-8 was used as a supplementary data because visible channel alone is not enough to remove clouds. Decision Tree method was selected for developing our algorithm because the result is easy to interpret marine fog detection process. The resulting algorithm consists of main marine fog detection process and two post-processing including cloud removal and marine fog boundary detection. Post-processing could provide more stable performance than GOCI-only algorithm. Validation was performed for 2107 and 2018 by comparing the detection results with in-situ visibility data and CALIPSO Vertical Feature Mask(VFM) data. Results show that marine fog can be well detected with this algorithm when there is no cloud above the marine fog.