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遥感技术与应用  2012, Vol. 27 Issue (5): 671-679    DOI: 10.11873/j.issn.1004-0323.2012.5.671
综述     
海表面盐度卫星微波遥感研究进展
王新新1,2,赵冬至2,杨建洪2,王 祥1,2
(1.大连海事大学环境科学与工程学院,辽宁 大连 116026;2.国家海洋环境监测中心,辽宁 大连 116023)
Progress in SSS (Sea Surface Salinity) Microwave Remote Sensing by Satellite
Wang Xinxin1,2,Zhao Dongzhi2,Yang Jianhong2,Wang Xiang1,2
(1.College of Environmental Science and Engineering,Dalian Maritime University,Dalian 116026,China;2.National Marine Environmental Monitoring Center,Dalian 116023,China)
 全文: PDF(1110 KB)  
摘要:

海表面盐度SSS(Sea Surface Salinity)是研究大洋环流和海洋对全球气候影响的重要参量、是决定海水基本性质的重要因素之一。卫星微波遥感可以满足盐度研究过程中大范围、连续观测的需要,国际上统一的认识是选择频率为1.413 GHz的L波段作为盐度遥感的首选波段。目前,国外发展的海面盐度微波遥感反演算法主要有两种:基于海表发射率估算海表盐度的算法和基于贝叶斯定理提出的反演算法。影响盐度反演精度的因素主要有太空辐射、电离层法拉第旋转、大气、海面粗糙度等。其中,海面粗糙度对盐度反演影响很大,海面粗糙度处理模型可以分为3大类:理论算法(间接发射率模型、直接发射率模型)、经验算法、半经验半理论算法(Hollinger 半经验模型、WISE半经验模型、Gabarró模型)。SMOS卫星和Aquarius/SAC\|D卫星的成功发射,将海表面盐度遥感的反演精度控制在0.2 psu以内,通过改进反演算法,有望得到更高的反演精度。

关键词: 海表面盐度亮温表面发射率微波遥感反演算法    
Abstract:

The SSS(Sea Surface Salinity) is the important parameter of study ocean circulation and global climate and factors which determine the essential properties of seawater.Satellite microwave remote sensing satisfies the salinity research needs of extensiveness and continuous observations.International chose L-band,with a central frequency of 1.413 GHz is the band of the first choice for salinity remote sensing.At the moment,there are two main inversion algorithms of SSS remote sensing by microwave oversea:Algorithm of estimate SSS with sea surface emissivity and inversion algorithm based on Bayesian.Main factors affecting the accuracy of the salinity inversion are Space radiation,Faraday rotation in ionized layer,atmospheric and sea surface roughness,and the surface roughness have a great impact on the salinity inversion.The surface roughness model can be divided into three categories:theoretical algorithm,empirical algorithm,semiempirical algorithm.Because Aquarius/SAC-D satellite and SMOS satellite were successfully launched,salinity can be retrieved with an accuracy of 0.2 psu by the two satellites,the inversion accuracy is expected to be higher by improving the inversion algorithm.

Key words: SSS    Brightness temperature    Surface emissivity    Microwave remote sensing    Retrieval algorithm
收稿日期: 2011-11-22 出版日期: 2012-10-17
:  TP 722.6  
基金资助:

海洋公益性行业科研专项经费项目(20090592)。

作者简介: 王新新(1989-),男,辽宁盘锦人,硕士研究生,主要从事海洋表层盐度卫星微波遥感方面的研究。Email:gulf5136@sina.com。
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引用本文:

王新新,赵冬至,杨建洪,王 祥. 海表面盐度卫星微波遥感研究进展[J]. 遥感技术与应用, 2012, 27(5): 671-679.

Wang Xinxin,Zhao Dongzhi,Yang Jianhong,Wang Xiang. Progress in SSS (Sea Surface Salinity) Microwave Remote Sensing by Satellite. Remote Sensing Technology and Application, 2012, 27(5): 671-679.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2012.5.671        http://www.rsta.ac.cn/CN/Y2012/V27/I5/671

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