Abstract
The first geostationary ocean color data from the Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) have been accumulating for more than ten years from 2010. This study performs a multi-year quality assessment of GOCI chlorophyll-a (Chl-a) and radiometric data for 2012–2021 with an advanced atmospheric correction technique and a regionally specialized Chl-a algorithm. We examine the consistency and stability of GOCI, Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) level 2 products in terms of annual and seasonal climatology, two-dimensional frequency distribution, and multi-year time series. Overall, the GOCI agrees well with MODIS and VIIRS on annual and seasonal variability in Chl-a, as the central biological pattern of the most transparent waters over the western North Pacific, productive waters over the East Sea, and turbid waters over the Yellow Sea are reasonably represented. Overall, an excellent agreement is remarkable for western North Pacific oligotrophic waters (with a correlation higher than 0.91 for Chl-a and 0.96 for band-ratio). However, the sporadic springtime overestimation of MODIS Chl-a values compared with others is notable over the Yellow Sea and East Sea due to the underestimation of MODIS blue-green band ratios for moderate-high aerosol optical depth. The persistent underestimation of VIIRS Chl-a values compared with GOCI and MODIS occurs due to inherent sensor calibration differences. In addition, the artificially increasing trends in GOCI Chl-a (+0.48 mg m−3 per 9 years) arise by the decreasing trends in the band ratios. However, decreasing Chl-a trends in MODIS and VIIRS (−0.09 and −0.08 mg m−3, respectively) are reasonable in response to increasing sea surface temperature. The results indicate GOCI sensor degradation in the late mission period. The long-term application of the GOCI data should be done with a caveat, however; planned adjustments to GOCI calibration (2022) in the following GOCI-II satellite will essentially eliminate the bias in Chl-a trends.
Highlights
Introduction iationsMarine phytoplankton are tiny but ubiquitous throughout Earth’s global oceans, which control approximately half of the net primary production in the Earth’s biosphere [1,2]
This comparison demonstrates the advantage of the geostationary ocean color sensor, as the Geostationary Ocean Color Imager (GOCI) data obtained at only 03 UTC include a more extensive and more continuous Chl-a observation area than the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS)
2012 (Figure 1a–c) widely capture the world’s most turbid and dynamic ocean waters interacting with river discharge over the East China Sea (Figure 1a–c) and the Yellow Sea (Figure 1d–f), spring blooms over the East Sea (Figure 1a–c,g–i), and the most transparent water over the subtropical Northwestern Pacific (Figure 1a–c)
Summary
Marine phytoplankton are tiny but ubiquitous throughout Earth’s global oceans, which control approximately half of the net primary production in the Earth’s biosphere [1,2]. Phytoplankton are one of the significant modulators of climate change. Phytoplankton fix atmospheric carbon dioxide into organic material through photosynthesis and transfer organic carbon in the marine ecosystem into the deep ocean [3]. Algal blooms occur when phytoplankton rapidly increase and accumulate, which has a negative impact on the marine ecosystem and fishery industry. Under global warming, quantifying changes in phytoplankton biomass over a longer time scale, the response of marine ecosystems, and climate feedback processes are all significant issues [4]. Due to the absolute scarcity of in situ measurements, ocean color remote sensing is an essential
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