A parametric model of estimating sea state bias based on JASON-1 altimetry

Shu Guang Li; Yun Hai Wang; Hong Li Miao; Xiao Guang Zhou; Hao Ran Ren; Gui Zhong Wang; Jie Zhang

doi:10.3969/j.issn.1673-5005.2013.02.030

A parametric model of estimating sea state bias based on JASON-1 altimetry

Shu Guang Li, Yun Hai Wang, Hong Li Miao, Xiao Guang Zhou, Hao Ran Ren, Gui Zhong Wang, Jie Zhang

Research output: Contribution to journal › Article › Research › peer-review

4 Citations (Scopus)

Abstract

Based on the data of JASON-1 altimetry, the parametric model of estimating the sea state bias (SSB) was studied. Non-SSB signals within the altimeter data were eliminated by means of forming differences between measurements taken at crossover points. According to Taylor expansion, 32 parametric models of SSB were developed as the function of both the significant wave height and wave speed. The estimation values of each parametric model were derived from the linear regression, and then the optimal model was obtained via the process of evaluation and selection. Finally, the effectiveness of the parametric model was validated through comparing the SSB estimation of the model with the geophysical data records (GDR) of JASON-1. The results show that the parametric model is effective, and can be used for JASON-1 SSB correction.

Original language	English
Pages (from-to)	181-185+196
Number of pages	6
Journal	Zhongguo Shiyou Daxue Xuebao (Ziran Kexue Ban)/Journal of China University of Petroleum (Edition of Natural Science)
Volume	37
Issue number	2
DOIs	https://doi.org/10.3969/j.issn.1673-5005.2013.02.030
Publication status	Published - Apr 2013
Externally published	Yes

Keywords

Difference at crossover points
JASON-1 altimetry
Linear regression
Parametric model
Sea state bias

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10.3969/j.issn.1673-5005.2013.02.030

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title = "A parametric model of estimating sea state bias based on JASON-1 altimetry",

abstract = "Based on the data of JASON-1 altimetry, the parametric model of estimating the sea state bias (SSB) was studied. Non-SSB signals within the altimeter data were eliminated by means of forming differences between measurements taken at crossover points. According to Taylor expansion, 32 parametric models of SSB were developed as the function of both the significant wave height and wave speed. The estimation values of each parametric model were derived from the linear regression, and then the optimal model was obtained via the process of evaluation and selection. Finally, the effectiveness of the parametric model was validated through comparing the SSB estimation of the model with the geophysical data records (GDR) of JASON-1. The results show that the parametric model is effective, and can be used for JASON-1 SSB correction.",

keywords = "Difference at crossover points, JASON-1 altimetry, Linear regression, Parametric model, Sea state bias",

author = "Li, {Shu Guang} and Wang, {Yun Hai} and Miao, {Hong Li} and Zhou, {Xiao Guang} and Ren, {Hao Ran} and Wang, {Gui Zhong} and Jie Zhang",

year = "2013",

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doi = "10.3969/j.issn.1673-5005.2013.02.030",

language = "English",

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journal = "Zhongguo Shiyou Daxue Xuebao (Ziran Kexue Ban)/Journal of China University of Petroleum (Edition of Natural Science)",

issn = "1673-5005",

publisher = "Zhongguo Shiyou Daxue Qikanshe / Periodical Office of China University of Petroleum",

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A parametric model of estimating sea state bias based on JASON-1 altimetry. / Li, Shu Guang; Wang, Yun Hai; Miao, Hong Li et al.
In: Zhongguo Shiyou Daxue Xuebao (Ziran Kexue Ban)/Journal of China University of Petroleum (Edition of Natural Science), Vol. 37, No. 2, 04.2013, p. 181-185+196.

Research output: Contribution to journal › Article › Research › peer-review

TY - JOUR

T1 - A parametric model of estimating sea state bias based on JASON-1 altimetry

AU - Li, Shu Guang

AU - Wang, Yun Hai

AU - Miao, Hong Li

AU - Zhou, Xiao Guang

AU - Ren, Hao Ran

AU - Wang, Gui Zhong

AU - Zhang, Jie

PY - 2013/4

Y1 - 2013/4

N2 - Based on the data of JASON-1 altimetry, the parametric model of estimating the sea state bias (SSB) was studied. Non-SSB signals within the altimeter data were eliminated by means of forming differences between measurements taken at crossover points. According to Taylor expansion, 32 parametric models of SSB were developed as the function of both the significant wave height and wave speed. The estimation values of each parametric model were derived from the linear regression, and then the optimal model was obtained via the process of evaluation and selection. Finally, the effectiveness of the parametric model was validated through comparing the SSB estimation of the model with the geophysical data records (GDR) of JASON-1. The results show that the parametric model is effective, and can be used for JASON-1 SSB correction.

AB - Based on the data of JASON-1 altimetry, the parametric model of estimating the sea state bias (SSB) was studied. Non-SSB signals within the altimeter data were eliminated by means of forming differences between measurements taken at crossover points. According to Taylor expansion, 32 parametric models of SSB were developed as the function of both the significant wave height and wave speed. The estimation values of each parametric model were derived from the linear regression, and then the optimal model was obtained via the process of evaluation and selection. Finally, the effectiveness of the parametric model was validated through comparing the SSB estimation of the model with the geophysical data records (GDR) of JASON-1. The results show that the parametric model is effective, and can be used for JASON-1 SSB correction.

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KW - Parametric model

KW - Sea state bias

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A parametric model of estimating sea state bias based on JASON-1 altimetry

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Keywords

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