Open AccessTrends and interannual variability of the South China Sea surface winds, surface height, and surface temperature in the recent decade
Author(s) -
Fang Guohong,
Chen Haiying,
Wei Zexun,
Wang Yonggang,
Wang Xinyi,
Li Chunyan
Publication year - 2006
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2005jc003276
Subject(s) - empirical orthogonal functions , sea surface temperature , climatology , environmental science , anticyclone , lag , sea surface height , geology , computer network , computer science
Trends and interannual variability of the surface winds (SW), sea surface height (SSH), and sea surface temperature (SST) of the South China Sea (SCS) in 1993–2003 are analyzed using monthly products from satellite observations. Time series are smoothed with a 12‐month running mean filter. The east and north components of the SW, SSH, and SST have linear trends of 0.53 ± 0.35 ms −1 decade −1 , −0.04 ± 0.17 ms −1 decade −1 , 6.7 ± 2.7 cm decade −1 , and 0.50 ± 0.26 K decade −1 , respectively. The sea level rising rate and sea surface warming rate are significantly higher than the corresponding global rates. An Empirical Orthogonal Function (EOF) analysis is performed to evaluate the interannual variability. Results show that the first EOF of the SW is characterized by a basin‐wide anticyclonic pattern. The corresponding time coefficient function (TCF) correlates with the Nino3.4 index at the 99% confidence level, with a lag of 3 months. The first EOF of the SSH is characterized by a low sea level along the eastern boundary. The corresponding TCF correlates with the Nino3.4 at the 99% level, with a lag of 2 months. The first EOF of the SST is characterized by a basin‐wide warming with the highest anomalies in the north deep basin. The corresponding TCF correlates with the Nino3.4 index at the 95% level, with a lag of 8 months. Based on the EOF analysis, the ENSO‐associated correlation patterns of the SW, SSH, and SST are presented.