In this study, we investigated different optical properties between severe versus moderate visibility marine fog using Geostationary Ocean Color Imager (GOCI) visible band measurements. Severe and moderate visibility marine fogs are best distinguishable with the criteria of visibility as 500 m. Using this, we developed an algorithm that classifies severe visibility marine fog based on Decision Tree (DT) method. Calibration and validation data were constructed for 2016 and 2017 marine fog cases, respectively, through match-up between satellite and in-situ data. In general, marine fog region has differences of textural and optical properties with cloud. The GOCI 412 nm Rayleigh Corrected Reflectance (Rrc) reveals small spatial variability in fog than in cloud. Also, it is notable that some distinction exists in Rrc magnitude between severe and moderate visibility marine fog region. Using this feature, we have developed a satellite marine fog detection algorithm with severe/moderate visibility classification. Rrc and Normalized Local Standard Deviation (NLSD) of Rrc were determined as primary input. However, visible channel alone cannot completely distinguish marine fog from cloud because it does not provide cloud height information. Here, we used cloud top height data from Himawari-8 as a supplementary data to remove cloud that was miss-classified as fog. Hit Rate (HR) and False Alarm Rate (FAR) for moderate (severe) visibility marine fog were 0.96 (0.86) and 0.31 (0.12), respectively.
Using the world’s first ocean color sensor at a geostationary orbit (Geostationary Ocean Color Imager; GOCI), we examine the relationship between satellite-derived chlorophyll-a concentration and MH events over the East China Sea during recent summers from 2016 to 2018. MH events usually arise in July and August over the study domain. When compared with the average of three days before and after MH events, the chlorophyll-a concentration since MH event occurrence tends to decrease from GOCI satellite images. Previous studies mentioned that the increased sea surface temperature (SST) enhances the stratification in upper ocean surface layer. Strong stratification derives the weak upwelling and the limited supply of nutrients from the deep to surface. These preliminary results show a possibility of real-time application of the geostationary ocean color satellite images for an immediate change in marine ecosystem caused by the extreme ocean warming event.
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