Revised chlorophyll-a algorithms for satellite ocean color sensors in the East/Japan Sea

被引:3
作者
Ryu, Jongseong [1 ]
Son, SeungHyun [2 ,3 ]
Jo, Chun Ok [4 ]
Kim, Haecheol [5 ]
Kim, Yonghoon [6 ]
Lee, Sang Heon [7 ,8 ]
Joo, HuiTae [9 ]
机构
[1] Anyang Univ, Dept Marine Biotechnol, Incheon, South Korea
[2] NOAA, NESDIS Satellite Applicat & Res, College Pk, MD USA
[3] Colorado State Univ, CIRA, Ft Collins, CO 80523 USA
[4] OceanScitech Inc, Seoul, South Korea
[5] SAIC NOAA, NESDIS, EMC, Princeton, NJ USA
[6] West Chester Univ Penn, Dept Earth & Space Sci, W Chester, PA USA
[7] Pusan Natl Univ, Dept Oceanog, Pusan, South Korea
[8] Pusan Natl Univ, Marine Res Inst, Pusan, South Korea
[9] Natl Inst Fisheries Sci, Pusan, South Korea
关键词
Ocean color Remote Sensing; Chlorophyll-a; East; Japan Sea; SPATIAL-DISTRIBUTION; ULLEUNG BASIN; VARIABILITY;
D O I
10.1016/j.rsma.2023.102876
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The East/Japan Sea (hereafter, East Sea (ES)) is a semi-enclosed marginal sea and considered as a miniature ocean with oceanic features (e.g., currents, eddies, fronts, upwelling) and dynamic marine environments. The ES is significantly influenced by the global ocean warming with fast increases in sea surface temperature during the last several decades. The climate-induced environmental changes can affect marine ecosystem and food webs in the ES. Therefore, more accurate estimates in phytoplankton biomass in the ES with high spatial and temporal resolutions are necessary to investigate phytoplankton production, fisheries, and carbon budget as well as biological responses to the environmental and climate changes. The NASA ocean chlorophyll-type (OCx) chlorophyll -a (Chl-a) algorithms based on blue to green band ratio for the satellite ocean color data in the global ocean have been evaluated using the in situ radiometric and Chl-a measurements in the ES. The model-derived Chl-a data using the OC Chl-a algorithms present systematic overestimation in the lower Chl-a concentrations between about 0.1 and 1.0 mg/m3 in the ES (with similar to 40% uncertainties). New Chl-a algorithms for the ES has been derived from the 3rd polynomial regression fits of in situ Chl-a and maximum band ratios of remote sensing reflectance (Rrs). The revised Chl-a algorithms considerably improve the Chl-a data in the ES from the satellite ocean color data in the lower Chl-a concentrations. Thus, the new Chl-a algorithms can provide more accurate assessments in biological and biogeochemical processes such as primary productivity, phytoplankton phenology, phytoplankton dynamics, and carbon cycles.(c) 2023 Elsevier B.V. All rights reserved.
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页数:9
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