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Journal of Ocean University of China

, Volume 19, Issue 1, pp 23–35 | Cite as

Semi-Empirical Algorithm for Wind Speed Retrieval from Gaofen-3 Quad-Polarization Strip Mode SAR Data

  • Shuai Zhu
  • Weizeng ShaoEmail author
  • Armando Marino
  • Jian Sun
  • Xinzhe Yuan
Article
  • 14 Downloads

Abstract

Synthetic aperture radar (SAR) is a suitable tool to obtain reliable wind retrievals with high spatial resolution. The geophysical model function (GMF), which is widely employed for wind speed retrieval from SAR data, describes the relationship between the SAR normalized radar cross-section (NRCS) at the copolarization channel (vertical-vertical and horizontal-horizontal) and a wind vector. SAR-measured NRCS at cross-polarization channels (horizontal-vertical and vertical-horizontal) correlates with wind speed. In this study, a semi-empirical algorithm is presented to retrieve wind speed from the noisy Chinese Gaofen-3 (GF-3) SAR data with noise-equivalent sigma zero correction using an empirical function. GF-3 SAR can acquire data in a quad-polarization strip mode, which includes cross-polarization channels. The semi-empirical algorithm is tuned using acquisitions collocated with winds from the European Center for Medium-Range Weather Forecasts. In particular, the proposed algorithm includes the dependences of wind speed and incidence angle on cross-polarized NRCS. The accuracy of SAR-derived wind speed is around 2.10 m s-1 root mean square error, which is validated against measurements from the Advanced Scatterometer onboard the Metop-A/B and the buoys from the National Data Buoy Center of the National Oceanic and Atmospheric Administration. The results obtained by the proposed algorithm considering the incidence angle in a GMF are relatively more accurate than those achieved by other algorithms. This work provides an alternative method to generate operational wind products for GF-3 SAR without relying on ancillary data for wind direction.

Key words

wind Gaofen-3 synthetic aperture radar cross-polarization 

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Notes

Acknowledgements

GF-3 SAR images were accessed from http://ds.nsoas.org.cn as an authorized account issued by NSOAS. The updated calibration constants were collected from http://dds.nsoas.org.cn/business/document (in Chinese). We also thank ECMWF for providing wind data, which were downloaded from http://www.ecmwf.int. ASCAT winds were downloaded online from http://archive.eumetsat.int using an authorized account. Buoy data were downloaded from http://www.ndbc.noaa.gov.

The research is partly supported by the Fundamental Research Funds for Zhejiang Provincial Universities and Research Institutes (No. 2019J00010), the National Key Research and Development Program of China (No. 2017 YFA0604901), the National Natural Science Foundation of China (Nos. 41806005 and 41776183), the Public Welfare Technical Applied Research Project of Zhejiang Province of China (No. LGF19D060003), the New-Shoot Talented Man Plan Project of Zhejiang Province (No. 2018R 411065), and the Science and Technology Project of Zhoushan City (No. 2019C21008).

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Copyright information

© Ocean University of China, Science Press and Springer-Verlag GmbH Germany 2019

Authors and Affiliations

  • Shuai Zhu
    • 1
  • Weizeng Shao
    • 1
    Email author
  • Armando Marino
    • 2
  • Jian Sun
    • 3
  • Xinzhe Yuan
    • 4
  1. 1.Marine Science and Technology CollegeZhejiang Ocean UniversityZhoushanChina
  2. 2.Natural SciencesUniversity of StirlingStirlingUK
  3. 3.Physical Oceanography LaboratoryOcean University of ChinaQingdaoChina
  4. 4.Key Laboratory of Space Ocean Remote Sensing and ApplicationNational Satellite Ocean Application ServiceBeijingChina

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