Evaluation of SAR wind speed retrieved based on C-2PO model and CMOD5.N geophysical model functions

Fang He; Xie Tao; Zhou Yufeng; Yang Jingsong; Zhao Li; He Yijun; William. Perrie

doi:10.3969/j.issn.0253-4193.2018.09.009

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Article Navigation > Haiyang Xuebao > 2018 > 40(9): 103-112

Fang He, Xie Tao, Zhou Yufeng, Yang Jingsong, Zhao Li, He Yijun, William. Perrie. Evaluation of SAR wind speed retrieved based on C-2PO model and CMOD5.N geophysical model functions[J]. Haiyang Xuebao, 2018, 40(9): 103-112. doi: 10.3969/j.issn.0253-4193.2018.09.009

Citation:

Fang He, Xie Tao, Zhou Yufeng, Yang Jingsong, Zhao Li, He Yijun, William. Perrie. Evaluation of SAR wind speed retrieved based on C-2PO model and CMOD5.N geophysical model functions[J]. Haiyang Xuebao, 2018, 40(9): 103-112. doi: 10.3969/j.issn.0253-4193.2018.09.009

Citation:

Fang He, Xie Tao, Zhou Yufeng, Yang Jingsong, Zhao Li, He Yijun, William. Perrie. Evaluation of SAR wind speed retrieved based on C-2PO model and CMOD5.N geophysical model functions[J]. Haiyang Xuebao, 2018, 40(9): 103-112. doi: 10.3969/j.issn.0253-4193.2018.09.009

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Evaluation of SAR wind speed retrieved based on C-2PO model and CMOD5.N geophysical model functions

doi: 10.3969/j.issn.0253-4193.2018.09.009

1.
School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
2.
Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology(Qingdao), Qingdao 266237, China;School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
3.
Beijing Institute of Applied Meteorology, Beijing 100029, China
4.
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China
5.
Fisheries & Oceans Canada, Bedford Institute of Oceanography, Dartmouth, Nova Scotia, B2Y 4A2, Canada

Received Date: 2017-09-10
Rev Recd Date: 2018-02-20

Abstract

Abstract

In this paper, we first retrieve ocean surface wind speed from C-2PO model without incidence angle input using selected 142 quad-polarized synthetic aperture radar (SAR) images. Subsequently, wind speed computed from geophysical function model (GMF) CMOD5.N with incidence angle measured from the advanced scatterometer (ASCAT) using the same SAR images. Compared with national data buoy center (NDBC) buoy-measured wind speed, the results show that the ocean surface wind speed retrieve from CMOD5.N GMF and C-2PO model both have a high accuracy, and with the root-mean-square (RMS) error are1.68 m/s and 1.74 m/s, respectively. In addition, the wind speeds retrieval RMS error of CMOD5.N GMF is perform better than C-2PO model at low wind speed section (0-10 m/s). After that, taken one SAR image with low wind speed, three reasons of this phenomenon are presented in this paper based on SAR system imaging mechanism.
- full polarimetric SAR,
- ocean surface wind speed,
- cross-polarization,
- geophysical model function,

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References(18)

References

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