Hourly changes in sea surface salinity in coastal waters recorded by Geostationary Ocean Color Imager
Hourly changes in sea surface salinity in coastal waters recorded by Geostationary Ocean Color Imager
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对地静止海洋颜色成像仪记录的沿海水域海面盐度每小时变化
DOI：
10.1016/j.ecss.2017.07.004
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发表时间：
2017-09
期刊：
影响因子：
--
通讯作者：
Liu RJ
中科院分区：
文献类型：
--
作者：
Liu Rongjie;An Jubai;Liu Rongjie;Zhang Jie;Cui Tingwei;Yao Haiyan;Wang Ning;Zhang Yi;Wu Lingjuan;Liu RJ
本文首次利用地球同步卫星海洋彩色图像对浑浊近岸海域的海水表面盐度（SSS）逐时变化进行了监测，并以渤海为例进行了研究。我们建立了一个简单的多元线性统计回归模型来检索地球同步海洋彩色成像仪（GOCI）的SSS数据（R2= 0.795, N = 41，范围：26.4 ~ 31.9 psμ）。然后使用浮标的独立连续SSS测量对模型进行验证，平均百分比差异为0.65%。将该模型应用于枯季天文潮汐期间的GOCI图像，以表征渤海SSS的逐时变化。我们发现，该模型对SSS的小时变化提供了合理的估计，并且模型和测量数据的趋势在量级和方向上相似（0.43 vs 0.33 psμ, R2= 0.51）。渤海SSS的日变化明显，区域平均值为0.455±0.079 (0.02 ~ 3.77)psμ。SSS的日变化幅度在空间上存在差异，近岸尤其是河口区日变化较大，近海区日变化较小。河滨地区的模型基于SSS与CDOM吸收的负相关关系。近海以高SSS、低CDOM的北黄海水团为主。驱动机制分析表明，潮流是控制渤海海温逐时变化的主要因素。
In this study, we monitored hourly changes in sea surface salinity (SSS) in turbid coastal waters from geostationary satellite ocean color images for the first time, using the Bohai Sea as a case study. We developed a simple multi-linear statistical regression model to retrieve SSS data from Geostationary Ocean Color Imager (GOCI) based on anin situsatellite matched-up dataset (R2= 0.795; N = 41; Range: 26.4 to 31.9 psμ). The model was then validated using independent continuous SSS measurements from buoys, with the average percentage difference of 0.65%. The model was applied to GOCI images from the dry season during an astronomical tide to characterize hourly changes in SSS in the Bohai Sea. We found that the model provided reasonable estimates of the hourly changes in SSS and that trends in the modeled and measured data were similar in magnitude and direction (0.43 vs 0.33 psμ, R2= 0.51). There were clear diurnal variations in the SSS of the Bohai Sea, with a regional average of 0.455 ± 0.079 psμ (0.02–3.77 psμ). The magnitude of the diurnal variations in SSS varied spatially, with large diurnal variability in the nearshore, particularly in the estuary, and small variability in the offshore area. The model for the riverine area was based on the inverse correlation between SSS and CDOM absorption. In the offshore area, the water mass of the North Yellow Sea, characterized by high SSS and low CDOM concentrations, dominated. Analysis of the driving mechanisms showed that the tidal current was the main control on hourly changes in SSS in the Bohai Sea.
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影响因子：
5.2
作者：
Gabarró, C;Font, J;Julià, A
通讯作者：
Julià, A
DOI：
--
发表时间：
2007
期刊：
Periodical of Ocean University of China
影响因子：
--
作者：
Wang Qiao
通讯作者：
Wang Qiao
DOI：
10.1117/12.2030969
发表时间：
2013-10
期刊：
--
影响因子：
--
作者：
X. Lou;A. Shi;Huaguo Zhang
通讯作者：
X. Lou;A. Shi;Huaguo Zhang
影响因子：
13.5
作者：
S. Khorram
通讯作者：
S. Khorram
影响因子：
2.8
作者：
Binding, CE;Bowers, DG
通讯作者：
Bowers, DG