scholarly journals Validation and Variation of Upper Layer Thickness in South China Sea from Satellite Altimeter Data

Sensors ◽  
2008 ◽  
Vol 8 (6) ◽  
pp. 3802-3818 ◽  
Author(s):  
Chun-Yi Lin ◽  
Chung-Ru Ho ◽  
Zhe-Wen Zheng ◽  
Nan-Jung Kuo
Keyword(s):  
South China Sea ◽  
Layer Thickness ◽  
South China ◽  
Altimeter Data ◽  
Satellite Altimeter ◽  
China Sea ◽  
Satellite Altimeter Data

scholarly journals A simple predictive model for the eddy propagation trajectory in the northern South China Sea

Ocean Science ◽  
2019 ◽  
Vol 15 (2) ◽  
pp. 401-412 ◽  
Author(s):  
Jiaxun Li ◽  
Guihua Wang ◽  
Huijie Xue ◽  
Huizan Wang
Keyword(s):  
South China Sea ◽  
Predictive Model ◽  
South China ◽  
Northern South China Sea ◽  
Altimeter Data ◽  
Linear Regression Method ◽  
Mean Flow ◽  
China Sea ◽  
Proposed Model ◽  
Satellite Altimeter Data

Abstract. A novel predictive model was built for eddy propagation trajectory using the multiple linear regression method. This simple model relates various oceanic parameters to eddy propagation position changes in the northern South China Sea (NSCS). These oceanic parameters mainly represent the effects of β and mean flow advection on the eddy propagation. The performance of the proposed model has been examined in the NSCS based on five years of satellite altimeter data and demonstrates its significant forecasting skills over a 4-week forecast window compared to the traditional persistence method. It was also found that the model forecasting accuracy is sensitive to eddy polarity and the forecast season.

scholarly journals A simple predictive model for the eddy propagation trajectory in the South China Sea

2018 ◽  
Author(s):  
Jiaxun Li ◽  
Guihua Wang ◽  
Huijie Xue ◽  
Huizan Wang
Keyword(s):  
South China Sea ◽  
Predictive Model ◽  
South China ◽  
Forecast Accuracy ◽  
The South China Sea ◽  
Altimeter Data ◽  
Linear Regression Method ◽  
Mean Flow ◽  
The South ◽  
China Sea

Abstract. A novel predictive model is built for eddy propagation trajectory using the multiple linear regression method. This simple model has related various oceanic parameters to eddy propagation position changes in the South China Sea (SCS). These oceanic parameters mainly represent the effects of planetary β and mean flow advection on the eddy propagation. The performance of the proposed model is examined in the SCS based on twenty years of satellite altimeter data, and demonstrates its significant forecast skills over a 4-week forecast window comparing to the traditional persistence method. It is also found that the model forecast accuracy is sensitive to eddy polarity and forecast season.

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