A combined semi-analytical algorithm for retrieving total suspended sediment concentration from multiple missions: a case study of the China Eastern Coastal Zone

ABSTRACT

A new semi-analytical algorithm that retrieves the total concentration of suspended matter (TSM) was derived from the China Eastern Coastal Zone using multiple ocean colour instruments including the Visible Infrared Imaging Radiometer (VIIRS), the Moderate-resolution Imaging Spectroradiometer (MODIS), and the Medium Resolution Spectral Imager II (MERSI II). The algorithm in one model derives TSM concentration (C_TSM) from satellite inherent optical properties products for clear and moderately turbid water. For turbid waters, a second model with a four-band approach was used. The two model algorithms were combined into one algorithm using a linking weighted function to generate a smooth C_TSM for clear and turbid water and for water with intermediate transparency. Compared to eight existing algorithms, our new algorithm performed better with a wide dynamic range for the C_TSM retrievals. The mean absolute percent difference was 28.22% for the CECZ data and the C_TSM varied from 0.5 mg l⁻¹ to 2435.4 mg l⁻¹. New algorithm decreased the MAPD by >11% for the C_TSM retrievals compared to the eight existing algorithms. Furthermore, when new algorithm was tested with a synthetic data set that had been contaminated with residual error, it exhibited more residual error tolerance than the other algorithms when retrieving C_TSM, which agreed well with the results provided by a multi-mission consistency analysis. These results indicate that new algorithm could provide accurate and consistent multi-mission C_TSM from turbid coastal water with a widely varying range of C_TSM.

Acknowledgements

Financial support was provided by the National Natural Science Foundation of China (Grant 42022045, Chen), International Cooperation in Science and Technology Innovation among Governments (Grant SQ2019YFE012389, Chen), Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies (Grant 2020B1212060025), National Natural Science Foundation of China (Grant 41876206), the Dragon-4 project (Grant 32405), and China-Korea Joint Ocean Research Center through project (PI-2019-1-01). We thank the First Institute of Oceanography State Oceanic Administration and National Marine Environmental Monitoring Center State Oceanic Administration for sharing the in situ data.

Data availability statement

The VIIRS and MODIS data can be downloaded from https://ladsweb.modaps.eosdis.nasa.gov and the MERSI II data can be downloaded from http://www.nsmc.org.cn.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [41876206]; International Cooperation in Science and Technology Innovation among Governments [SQ2019YFE012389, Chen]; the Dragon-4 project [32405]; Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies [2020B1212060025]; China-Korea Joint Ocean Research Center through project [PI-2019-1-01]; the National Natural Science Foundation of China [42022045,Chen].