TY - JOUR
T1 - Satellite Observations of the Diurnal Dynamics of Particulate Organic Carbon in Optically Complex Coastal Oceans
T2 - The Continental Shelf Seas of China
AU - Wei, Xiaodao
AU - Shen, Fang
AU - Pan, Yanqun
AU - Chen, Shuguo
AU - Sun, Xuerong
AU - Wang, Yongchao
N1 - Publisher Copyright:
© 2019. American Geophysical Union. All Rights Reserved.
PY - 2019
Y1 - 2019
N2 - The continental shelf seas of China (CSSC) broadly encompass the Bohai Sea, the Yellow Sea, and the East China Sea and exhibit highly variable optical properties. Accurate satellite estimates of particulate organic carbon (POC) remain challenging because optimal proxies for remotely sensed POC are largely obscure in these optically complex coastal waters. In this study, optical and biogeochemical data, including the particulate beam attenuation coefficient (cp), particulate backscattering coefficient (bbp), remote sensing reflectance (Rrs), POC, total suspended matter (TSM), and chlorophyll-a (Chla), were collected over multiple seasons and years in the CSSC. We first classified the study area into three different water types with three different POC retrieval proxies: the TSM for high-TSM waters, Chla for low-TSM waters, and Rrs ratio (Rrs(490)/Rrs(555)) for moderate-TSM waters. A composite POC algorithm using these three optimal proxies was then developed for Geostationary Ocean Color Imager (GOCI) satellite data (hereafter called the POC_CSSC algorithm). The validation results indicated that the accuracy of GOCI-derived POC was greatly improved with a mean relative error of 32.08%. Application of the POC_CSSC algorithm to GOCI data over a tidally impacted estuary demonstrated the robustness of the algorithm and that tides play different roles in the broad CSSC. More specifically, tides have the strongest influence on nearshore estuarine waters, regulating the progression of high-POC water masses from estuary to offshore environments, while offshore waters were the least influenced by tides with less variable, low POC concentrations.
AB - The continental shelf seas of China (CSSC) broadly encompass the Bohai Sea, the Yellow Sea, and the East China Sea and exhibit highly variable optical properties. Accurate satellite estimates of particulate organic carbon (POC) remain challenging because optimal proxies for remotely sensed POC are largely obscure in these optically complex coastal waters. In this study, optical and biogeochemical data, including the particulate beam attenuation coefficient (cp), particulate backscattering coefficient (bbp), remote sensing reflectance (Rrs), POC, total suspended matter (TSM), and chlorophyll-a (Chla), were collected over multiple seasons and years in the CSSC. We first classified the study area into three different water types with three different POC retrieval proxies: the TSM for high-TSM waters, Chla for low-TSM waters, and Rrs ratio (Rrs(490)/Rrs(555)) for moderate-TSM waters. A composite POC algorithm using these three optimal proxies was then developed for Geostationary Ocean Color Imager (GOCI) satellite data (hereafter called the POC_CSSC algorithm). The validation results indicated that the accuracy of GOCI-derived POC was greatly improved with a mean relative error of 32.08%. Application of the POC_CSSC algorithm to GOCI data over a tidally impacted estuary demonstrated the robustness of the algorithm and that tides play different roles in the broad CSSC. More specifically, tides have the strongest influence on nearshore estuarine waters, regulating the progression of high-POC water masses from estuary to offshore environments, while offshore waters were the least influenced by tides with less variable, low POC concentrations.
KW - GOCI
KW - POC algorithm
KW - optical classification
KW - particulate organic carbon
KW - remote sensing
KW - the continental shelf seas of China
UR - https://www.scopus.com/pages/publications/85068663222
U2 - 10.1029/2018JC014715
DO - 10.1029/2018JC014715
M3 - 文章
AN - SCOPUS:85068663222
SN - 2169-9275
VL - 124
SP - 4710
EP - 4726
JO - Journal of Geophysical Research: Oceans
JF - Journal of Geophysical Research: Oceans
IS - 7
ER -