scholarly journals HF Radar Network Design for Remote Sensing of the South China Sea

10.5772/57599 ◽  
2014 ◽  
Author(s):  
Stuart J. Anderson
Keyword(s):  
Remote Sensing ◽  
South China Sea ◽  
Network Design ◽  
South China ◽  
The South China Sea ◽  
Hf Radar ◽  
The South ◽  
China Sea ◽  
Radar Network

scholarly journals Feasibility of reconstructing the basin–scale sea surface partial pressure of carbon dioxide from sparse in situ observations over the South China Sea

2020 ◽  
Author(s):  
Guizhi Wang ◽  
Samuel S. P. Shen ◽  
Yao Chen ◽  
Yan Bai ◽  
Huan Qin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
South China Sea ◽  
Partial Pressure ◽  
South China ◽  
The South China Sea ◽  
Sea Surface ◽  
High Pco2 ◽  
The South ◽  
China Sea ◽  
Basin Scale

Abstract. Sea surface partial pressure of CO2 (pCO2) data with high spatial-temporal resolution are important in studying the global carbon cycle and assessing the oceanic carbon uptake capacity. However, the observed sea surface pCO2 data are usually limited in spatial and temporal coverage, especially in marginal seas. This study provides an approach to reconstruct the complete sea surface pCO2 field in the South China Sea (SCS) with a grid resolution of 0.5º × 0.5º over the period of 2000–2017 using both remote-sensing derived pCO2 and observed pCO2. Empirical orthogonal functions (EOFs) were computed from the remote sensing derived pCO2. Then, a multilinear regression was applied to the observed pCO2 as the response variable with the EOFs as the explanatory variables. EOF1 explains the general spatial pattern of pCO2 in the SCS. EOF2 shows the pattern influenced by the Pearl River plume on the northern shelf and slope. EOF3 is consistent with the pattern influenced by coastal upwelling along the north coast of the SCS. The reconstructions always agree with observations. When pCO2 observations cover a sufficiently large area, the reconstructed fields successfully display a pattern of relatively high pCO2 in the mid-and-southern basin. The rate of sea surface pCO2 increase in the SCS is 2.383 μatm per year based on the spatial average of the reconstructed pCO2 over the period of 2000–2017. All the data for this paper are openly and freely available at PANGAEA under the link https://doi.pangaea.de/10.1594/PANGAEA.921210 (Wang et al., 2020).

scholarly journals Observed Near-Inertial Waves in the Northern South China Sea

2021 ◽  
Vol 13 (16) ◽  
pp. 3223
Author(s):  
Bing Yang ◽  
Po Hu ◽  
Yijun Hou
Keyword(s):  
Remote Sensing ◽  
South China Sea ◽  
South China ◽  
Mesoscale Eddies ◽  
Relative Vorticity ◽  
The South China Sea ◽  
Inertial Waves ◽  
The South ◽  
China Sea ◽  
Maximum Value

Characteristics of near-inertial waves (NIWs) induced by the tropical storm Noul in the South China Sea are analyzed based on in situ observations, remote sensing, and analysis data. Remote sensing sea level anomaly data suggests that the NIWs were influenced by a southwestward moving anticyclonic eddy. The NIWs had comparable spectral density with internal tides, with a horizontal velocity of 0.14–0.21 m/s. The near-inertial kinetic energy had a maximum value of 7.5 J/m3 and propagated downward with vertical group speed of 10 m/day. Downward propagation of near-inertial energy concentrated in smaller wavenumber bands overwhelmed upward propagation energy. The e-folding time of NIWs ranged from 4 to 11 days, and the larger e-folding time resulted from the mesoscale eddies with negative vorticity. Modified by background relative vorticity, the observed NIWs had both red-shifted and blue-shifted frequencies. The upward propagating NIWs had larger vertical phase speeds and wavelengths than downward propagating NIWs. There was energy transfer from the mesoscale field to NIWs with a maximum value of 8.5 × 10−9 m2 s−3 when total shear and relative vorticity of geostrophic currents were commensurate. Our results suggest that mesoscale eddies are a significant factor influencing the generation and propagation of NIWs in the South China Sea.

Detection of Internal Solitary Wave in the South China Sea Using Optical Remote Sensing

2015 ◽  
Vol 52 (4) ◽  
pp. 042801 ◽  
Author(s):  
张旭东 Zhang Xudong ◽  
王晶 Wang Jing ◽  
魏子章 Wei Zizhang ◽  
孙丽娜 Sun Lina ◽  
孟俊敏 Meng Junmin
Keyword(s):  
Remote Sensing ◽  
South China Sea ◽  
Solitary Wave ◽  
South China ◽  
The South China Sea ◽  
Internal Solitary Wave ◽  
Optical Remote Sensing ◽  
The South ◽  
China Sea
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