Uncertainty estimation in geostationary ocean color imager (GOCI) bio-optical products for detecting diurnal variability in coastal water

ABSTRACT

Geostationary Ocean Colour Imager (GOCI) provides ocean colour products for monitoring ecosystem dynamics and assessing spatiotemporal changes. However, producing reliable satellite-based product estimates remains challenging in optically complex coastal waters, and bio-optics algorithms must be assessed. To date, assessments of satellite products have been analysed based on clear, natural waters. In this study, we assume stable waters that express little to no diurnal variability due to biological or physical processes in coastal water. Then, a suitable bio-optical algorithm with the lowest uncertainty is selected. The Tassan (MS) algorithm proposed in 2016 provided the appropriate representations of the temporal variation in chlorophyll in the results. The uncertainty of chlorophyll a estimated at the Mooring site located at the Yangtze River mouth and at the Ieodo site located off the coast of the Tsushima Strait were less than 14.5%, and the maximum uncertainty at the Socheongcho site, which was close to the Korean Peninsula, was 28.7%.

KEYWORDS:

• Uncertainty
• diurnal variability
• GOCI
• coastal water
• stable water

Acknowledgements

This research was funded by NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (Grant No. U1609202), and National Natural Science Foundation of China (Grant Nos. 42076216, 41376184, and 40976109), National Key Research and Development Program of China (Grant No. 2016YFC1400903). We sincerely thank Dr. Jiang and Dr. Fu for helping us improve the manuscript. We also thank the staff of the satellite ground station, satellite data processing and sharing center of the State Key Laboratory of Satellite Ocean EnvironmentDynamics, Second Institute of Oceanography, Ministry of Natural Resources (SOED/SIO/MNR), for their help with data collection and processing.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work was supported by NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization [U1609202]; the National Natural Science Foundation of China [40976109,41376184,42076216]; National Key Research and Development Program of China [2016YFC1400903].