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Comparisons of composite radar backscattering model and sea surface radar backscatter from synthetic aperture radar, scatterometer and altimeter
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Xiaomin Ye1, 2, Mingsen Lin1, 2, 5, Qingtao Song1, 2, *, Fei Liao3, Chao Liang1, 2, Xuan Zhou4
Haiyang Xuebao | 2019, 41(7) : 123 - 135
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Haiyang Xuebao | 2019, 41(7): 123-135
Marine Information Science
Comparisons of composite radar backscattering model and sea surface radar backscatter from synthetic aperture radar, scatterometer and altimeter
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Xiaomin Ye1, 2, Mingsen Lin1, 2, 5, Qingtao Song1, 2, *, Fei Liao3, Chao Liang1, 2, Xuan Zhou4
Affiliations
  • 1 National Satellite Ocean Application Service, Beijing 100081, China
  • 2 Key Laboratory of Space Ocean Remote Sensing and Application, State Oceanic Administration, Beijing 100081, China
  • 3 Guangzhou Meteorology Observatory, Guangzhou 511430, China
  • 4 Mailbox 5111, Beijing 100094, China
  • 5 Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technolog (Qingdao), Qingdao 266237, China
Published: 2019-07-25 doi: 10.3969/j.issn.0253-4193.2019.07.011
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Comparison with Geophysical Model Function (GMF) developed by methods of empirical statistics, ocean microwave scattering model works well at all microwave frequency. Composite radar backscattering model is comprised of Bragg scattering model and geometrical optics model. We calculated the normalized radar cross sections (NRCSs) from the composite scattering model by using the sea surface wind speeds and directions measured by buoys moored in the northern of South China Sea in the whole year of 2014, and then compared them with SAR on board RADARSAT-2 at C-band, microwave scatterometer on board HY-2A satellite (HSCAT) at Ku-band, respectively. The biases of comparison are (–0.22±1.88) dB ( for SAR), (0.33±2.71) dB (for HSCAT in VV polarization) and (–1.35±2.88) dB (for HSCAT in HH polarization), respectively. We also calculated the NRCSs from the model by using the sea surface wind speeds and directions measured by NDBC buoys in the time period from October 1, 2011 to September 30, 2014, and then compared them with radar altimeter on board Jason-2 and HY-2A both at Ku-band with the bias of (1.01±1.15) dB and (1.12±1.29) dB, respectively. Although the biases of NRCSs between space-borne sensors and composite scattering model in medium and normal incidence are different each other, the accuracies of their sea surface wind speed products are the same(i.e. the root mean square errors are all less than 1.71 m/s). The results show that we can simulate the sea surface radar NRCSs of satellite-borne SAR, microwave scatterometer, and altimeter by using the composite radar backscattering model, and the simulations are consistent with that of CMOD5, NSCAT-2 and the GMF of operational wind retrieval for altimeter. It also indicates that the composite radar backscattering model could be used in calibration and validation of microwave sensors and simulation of radar backscatter from sea surface.

radar backscattering model  /  synthetic aperture radar  /  scatterometer  /  altimeter
Xiaomin Ye, Mingsen Lin, Qingtao Song, Fei Liao, Chao Liang, Xuan Zhou. Comparisons of composite radar backscattering model and sea surface radar backscatter from synthetic aperture radar, scatterometer and altimeter[J]. Haiyang Xuebao, 2019 , 41 (7) : 123 -135 . DOI: 10.3969/j.issn.0253-4193.2019.07.011
Year 2019 volume 41 Issue 7
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Article Info
doi: 10.3969/j.issn.0253-4193.2019.07.011
  • Receive Date:2017-04-24
  • Online Date:2026-04-02
  • Published:2019-07-25
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  • Received:2017-04-24
  • Revised:2018-04-26
Funding
Affiliations
    1 National Satellite Ocean Application Service, Beijing 100081, China
    2 Key Laboratory of Space Ocean Remote Sensing and Application, State Oceanic Administration, Beijing 100081, China
    3 Guangzhou Meteorology Observatory, Guangzhou 511430, China
    4 Mailbox 5111, Beijing 100094, China
    5 Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technolog (Qingdao), Qingdao 266237, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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