Application of satellite data in monsoon and circulation of South China Sea

2003 ◽  
Author(s):  
Mingsen Lin ◽  
Dewei Xu ◽  
Xiaosun Li
Keyword(s):  
South China Sea ◽  
South China ◽  
Satellite Data ◽  
China Sea

scholarly journals Spatiotemporal Variability of Surface Phytoplankton Carbon and Carbon-to-Chlorophyll a Ratio in the South China Sea Based on Satellite Data

2020 ◽  
Vol 13 (1) ◽  
pp. 30
Author(s):  
Wenlong Xu ◽  
Guifen Wang ◽  
Long Jiang ◽  
Xuhua Cheng ◽  
Wen Zhou ◽  
...  
Keyword(s):  
South China Sea ◽  
Chlorophyll A ◽  
South China ◽  
Satellite Data ◽  
Phytoplankton Biomass ◽  
The South China Sea ◽  
Spatiotemporal Variability ◽  
The South ◽  
Chl A ◽  
China Sea

The spatiotemporal variability of phytoplankton biomass has been widely studied because of its importance in biogeochemical cycles. Chlorophyll a (Chl-a)—an essential pigment present in photoautotrophic organisms—is widely used as an indicator for oceanic phytoplankton biomass because it could be easily measured with calibrated optical sensors. However, the intracellular Chl-a content varies with light, nutrient levels, and temperature and could misrepresent phytoplankton biomass. In this study, we estimated the concentration of phytoplankton carbon—a more suitable indicator for phytoplankton biomass—using a regionally adjusted bio-optical algorithm with satellite data in the South China Sea (SCS). Phytoplankton carbon and the carbon-to-Chl-a ratio (θ) exhibited considerable variability spatially and seasonally. Generally, phytoplankton carbon in the northern SCS was higher than that in the western and central parts. The regional monthly mean phytoplankton carbon in the northern SCS showed a prominent peak during December and January. A similar pattern was shown in the central part of SCS, but its peak was weaker. Besides the winter peak, the western part of SCS had a secondary maximum of phytoplankton carbon during summer. θ exhibited significant seasonal variability in the northern SCS, but a relatively weak seasonal change in the western and central parts. θ had a peak in September and a trough in January in the northern and central parts of SCS, whereas in the western SCS the minimum and maximum θ was found in August and during October–April of the following year, respectively. Overall, θ ranged from 26.06 to 123.99 in the SCS, which implies that the carbon content could vary up to four times given a specific Chl-a value. The variations in θ were found to be related to changing phytoplankton community composition, as well as dynamic phytoplankton physiological activities in response to environmental influences; which also exhibit much spatial differences in the SCS. Our results imply that the spatiotemporal variability of θ should be considered, rather than simply used a single value when converting Chl-a to phytoplankton carbon biomass in the SCS, especially, when verifying the simulation results of biogeochemical models.

scholarly journals Satellite data lift the veil on offshore platforms in the South China Sea

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Yongxue Liu ◽  
Chao Sun ◽  
Jiaqi Sun ◽  
Hongyi Li ◽  
Wenfeng Zhan ◽  
...  
Keyword(s):  
South China Sea ◽  
South China ◽  
Satellite Data ◽  
The South China Sea ◽  
Offshore Platforms ◽  
The South ◽  
China Sea ◽  
The Veil

scholarly journals Offshore Wind Resources Assessment from Multiple Satellite Data and WRF Modeling over South China Sea

2015 ◽  
Vol 7 (1) ◽  
pp. 467-487 ◽  
Author(s):  
Rui Chang ◽  
Rong Zhu ◽  
Merete Badger ◽  
Charlotte Hasager ◽  
Xuhuang Xing ◽  
...  
Keyword(s):  
South China Sea ◽  
South China ◽  
Satellite Data ◽  
Offshore Wind ◽  
China Sea ◽  
Wrf Modeling ◽  
Wind Resources ◽  
Resources Assessment

scholarly journals Internal Solitary Waves Observed on the Continental Shelf in the Northern South China Sea From Acoustic Backscatter Data

2021 ◽  
Vol 8 ◽  
Author(s):  
Yingci Feng ◽  
Qunshu Tang ◽  
Jian Li ◽  
Jie Sun ◽  
Wenhuan Zhan
Keyword(s):  
South China Sea ◽  
Shallow Water ◽  
Solitary Waves ◽  
South China ◽  
Satellite Data ◽  
Northern South China Sea ◽  
Acoustic Backscatter ◽  
Internal Solitary Waves ◽  
Study Region ◽  
China Sea

Internal solitary waves (ISWs) are investigated offshore of Guangdong in the northern South China Sea (SCS) using high-frequency acoustic backscatter data of 100 kHz acquired in July 2020. Simultaneous XBT profiles and satellite images are incorporated to understand their propagation, evolution, and dissipation processes in shallow water at depths less than 50 m. The water column structures revealed by acoustic backscatter data and XBT profiles are consistent with a small difference of less than 3 m. A soliton train with apparent vertical and horizontal scales of ∼7 and 100 m, respectively, is captured three times in 20 h in the repeated acoustic sections, which provides spatiotemporal constraints to the solitons. The characteristics of ISW phase speeds are estimated from acoustic backscatter data and satellite data and using theoretical two-layer Korteweg-de Vries (KdV) and extended KdV (eKdV) models. The acoustically observed phase speed of ISWs is approximately 0.4–0.5 m/s, in agreement with the estimates from both satellite data and model results. The shallow solar-heated water in summer (∼10–20 m) lying on the bottom cold water is responsible for the extensive occurrence of ISWs in the study region. ISWs are dissipated at the transition zone between the heated surface water and the upwelled water, forming a wide ISW dissipation zone in the coastal area, as observed from satellites. The acoustic backscatter method could be an effective way to observe ISWs with high resolution in shallow water and thus a potential compensatory technique for imaging the shallow blind zone of so-called seismic oceanography.

Characterization of Wind-Sea and Swell in the South China Sea based on HY-2 Satellite Data

2018 ◽  
Vol 84 ◽  
pp. 58-62
Author(s):  
Shuiqing Li ◽  
Fan Bi ◽  
Yijun Hou ◽  
Hongwei Yang
Keyword(s):  
South China Sea ◽  
South China ◽  
Satellite Data ◽  
The South China Sea ◽  
The South ◽  
China Sea ◽  
Wind Sea
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