基于OC-CCI数据的南海高叶绿素a浓度水域面积的时空变化研究*

doi:10.11978/2021048

Abstract

Abstract:

Phytoplankton are the basis of the marine ecosystem food chain, and affect the variation of CO₂ flux through photosynthesis. In this study, an estimation system of phytoplankton biomass in the South China Sea was established based on an area indicator. We used the empirical orthogonal function decomposition interpolation method (DINEOF) to reconstruct the chlorophyll a concentration field in the South China Sea from long time series of remote sensing data. We studied the space-time distribution of the high biomass water area of the South China Sea and found that the changes of water area with high chlorophyll a concentration had significant seasonal characteristics. The area of waters with high chlorophyll concentration reached the maximum in winter, and the minimum in summer. Conversely, the chlorophyll concentration reached the minimum in winter, and maximum in summer. This feature may be due to the wind-driven dynamic processes that redistribute the chlorophyll concentration near the surface. Moreover, waters with high chlorophyll concentration were found near the coast year round, especially in coastal waters of China, along the coast of Vietnam, the Gulf of Thailand, and near Borneo Island. In the Sunda Shelf and the central basin east of the Mekong estuary, the area of high biomass water showed interannual variation. The East Asian monsoon modulated by the El Niño and Southern Oscillation led to different degrees of cold water invasion from the north to the southeast of the Mekong Estuary in different years, which may be the reason for the increase and decrease of local phytoplankton biomass.

Key words: South China Sea, phytoplankton, area of high chlorophyll concentration, spatial and temporal distribution characteristics, Data Interpolating Empirical Orthogonal Functions

CLC Number:

P735.52

LI Ao, FENG Yang, WANG Yuntao, XUE Huijie. Spatiotemporal variation of water area with high chlorophyll a concentration in the South China Sea based on OC-CCI data*[J].Journal of Tropical Oceanography, 2022, 41(2): 77-89.

Figures/Tables 14

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