中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Impact of rain-induced sea surface roughness variations on salinity retrieval from the Aquarius/SAC-D satellite

文献类型:期刊论文

作者Ma Wentao1; Yang Xiaofeng1; Yu Yang1; Liu Guihong1; Li Ziwei1; Jing Cheng1
刊名ACTA OCEANOLOGICA SINICA
出版日期2015
卷号34期号:7页码:124-132
关键词Aquarius salinity remote sensing rain L-band emissivity
通讯作者Yang, XF (reprint author), Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China.
英文摘要Rainfall has two significant effects on the sea surface, including salinity decreasing and surface becoming rougher, which have further influence on L-band sea surface emissivity. Investigations using the Aquarius and TRMM 3B42 matchup dataset indicate that the retrieved sea surface salinity (SSS) is underestimated by the present Aquarius algorithm compared to numerical model outputs, especially in cases of a high rain rate. For example, the bias between satellite-observed SSS and numerical model SSS is approximately 2 when the rain rate is 25 mm/h. The bias can be eliminated by accounting for rain-induced roughness, which is usually modeled by rain-generated ring-wave spectrum. The rain spectrum will be input into the Small Slope Approximation (SSA) model for the simulation of sea surface emissivity influenced by rain. The comparison with theoretical model indicated that the empirical model of rain spectrumis more suitable to be used in the simulation. Further, the coefficients of the rain spectrum are modified by fitting the simulations with the observations of the 2-year Aquarius and TRMM matchup dataset. The calculations confirm that the sea surface emissivity increases with the wind speed and rain rate. The increase induced by the rain rate is rapid in the case of low rain rate and low wind speed. Finally, a modified model of sea surface emissivity including the rain spectrum is proposed and validated by using the matchup dataset in May 2014. Compared with observations, the bias of the rain-induced sea surface emissivity simulated by the modified modelis approximately 1e(-4), and the RMSE is slightly larger than 1e(-3). With using more matchup data, thebias between model retrieved sea surface salinities and observationsmay be further corrected, and the RMSE may be reduced to less than 1 in the cases of low rain rate and low wind speed.
研究领域[WOS]Oceanography
收录类别SCI
语种英语
WOS记录号WOS:000358256500009
源URL[http://ir.ceode.ac.cn/handle/183411/38416]  
专题遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位1.[Ma Wentao] Ocean Univ China, Coll Phys & Environm Oceanog, Qingdao 266100, Peoples R China
2.[Ma Wentao
3.Yang Xiaofeng
4.Yu Yang
5.Liu Guihong
6.Li Ziwei
7.Jing Cheng] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714
Ma Wentao,Yang Xiaofeng,Yu Yang,et al. Impact of rain-induced sea surface roughness variations on salinity retrieval from the Aquarius/SAC-D satellite[J]. ACTA OCEANOLOGICA SINICA,2015,34(7):124-132.
APA Ma Wentao,Yang Xiaofeng,Yu Yang,Liu Guihong,Li Ziwei,&Jing Cheng.(2015).Impact of rain-induced sea surface roughness variations on salinity retrieval from the Aquarius/SAC-D satellite.ACTA OCEANOLOGICA SINICA,34(7),124-132.
MLA Ma Wentao,et al."Impact of rain-induced sea surface roughness variations on salinity retrieval from the Aquarius/SAC-D satellite".ACTA OCEANOLOGICA SINICA 34.7(2015):124-132.

入库方式: OAI收割

来源:遥感与数字地球研究所

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