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首页> 外文期刊>Journal of Geophysical Research, C. Oceans: JGR >Trends and interannual variability of the South China Sea surface winds, surface height, and surface temperature in the recent decade
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Trends and interannual variability of the South China Sea surface winds, surface height, and surface temperature in the recent decade

机译：近十年来南海地表风，地表高度和地表温度的趋势和年际变化

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摘要

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.
机译：使用卫星观测的月度产品，分析了1993-2003年南海（SCS）的地表风（SW），海面高度（SSH）和海面温度（SST）的趋势和年际变化。时间序列通过12个月的运行均值过滤器进行了平滑处理。 SW，SSH和SST的东部和北部分量具有线性趋势，分别为0.53±0.35 ms-1个十进位-1，-0.04±0.17 ms-1个十进位1,1、6.7±2.7厘米十进位1和0.50±0.26 K十年？1。海平面上升率和海面变暖率显着高于相应的全球率。进行经验正交函数（EOF）分析以评估年际变化。结果表明，西南部的第一个EOF具有盆地范围的反气旋特征。相应的时间系数函数（TCF）在99％置信度下与Nino3.4指数相关，滞后3个月。 SSH的第一个EOF的特征是沿东部边界的海平面较低。相应的TCF在99％的水平上与Nino3.4相关，滞后2个月。 SST的第一个EOF的特征是盆地深部北部全盆地范围内变暖程度最高。相应的TCF与Nino3.4指数在95％的水平上相关，滞后8个月。基于EOF分析，提出了与ENSO相关的SW，SSH和SST相关模式。

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