5:15 PM - 6:45 PM
[MIS10-P06] Ice contamination threshold for an appropriate use of the SGLI/GCOM-C data in the Southern Ocean
Keywords:Ocean color remote sensing, Adjacency effect, Sea ice
The Southern Ocean (SO) comprises ~10% of the global ocean. Phytoplankton living in the SO plays an important role in the global carbon cycle and supports the Antarctic marine ecosystems, including fishery resources such as krill, toothfish, and ice fish. Satellite ocean color sensors effectively measure phytoplankton chlorophyll a (chl.a) and primary production in harsh SO environments. The second-generation global imager (SGLI) aboard the global change observation mission-climate (GCOM-C) satellite has 250 m spatial resolution in coastal regions, including waters in the Antarctic sea ice zone. Thus, SGLI can increase opportunities to detect chl.a in the SO, whose optical properties are known to be unique. However, cloud cover and sea ice, which induce noises by inter-channel sub-pixel misalignment, adjacent effect and stray light, interfere with ocean color observations in the SO. In this study, we validated chl.a concentration from the SGLI, and attempted to apply an index of ice contamination using a band-ratio threshold to acquire more accurate chl.a data.
In-situ chl.a concentrations (n=169) determined with ultra-high performance liquid chromatography (UHPLC) were used for the validation of the SGLI data. We obtained eight match-up data within six hours of a time window, and two out of them showed large errors: the relative and absolute errors were >70% and >0.2 mg m-3, respectively. The anomalous data were found at the edges of clouds and sea ice. The level-2 flags of the SGLI data indicated that the failures were caused by atmospheric correction and/or ice contamination. An ice contamination threshold using in-situ water-leaving reflectance in the SO was consistent with the evidence that the absorption coefficient of colored organic matter (CDOM) was lower than that in the Arctic Ocean. Although we need a further collection of such match-up data, our results suggest that the SGLI can accurately estimate chl.a in the SO with 250 m spatial resolution, excluding erroneous data near ice edges using the band-ratio threshold.
In-situ chl.a concentrations (n=169) determined with ultra-high performance liquid chromatography (UHPLC) were used for the validation of the SGLI data. We obtained eight match-up data within six hours of a time window, and two out of them showed large errors: the relative and absolute errors were >70% and >0.2 mg m-3, respectively. The anomalous data were found at the edges of clouds and sea ice. The level-2 flags of the SGLI data indicated that the failures were caused by atmospheric correction and/or ice contamination. An ice contamination threshold using in-situ water-leaving reflectance in the SO was consistent with the evidence that the absorption coefficient of colored organic matter (CDOM) was lower than that in the Arctic Ocean. Although we need a further collection of such match-up data, our results suggest that the SGLI can accurately estimate chl.a in the SO with 250 m spatial resolution, excluding erroneous data near ice edges using the band-ratio threshold.