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Applicability of Synthetic Aperture Radar Wind Retrievals on Offshore Wind Resources Assessment in Hangzhou Bay, China

Author

Listed:
  • Rui Chang

    (Public Meteorological Service Center of China Meteorological Administration (CMA), Beijing 10081, China)

  • Rong Zhu

    (National Climate Center, Beijing 10081, China)

  • Merete Badger

    (Department of Wind Energy, Technical University of Denmark (DTU), Frederiksborgvej 339, 4000 Roskilde, Denmark)

  • Charlotte Bay Hasager

    (Department of Wind Energy, Technical University of Denmark (DTU), Frederiksborgvej 339, 4000 Roskilde, Denmark)

  • Rongwei Zhou

    (Public Meteorological Service Center of China Meteorological Administration (CMA), Beijing 10081, China)

  • Dong Ye

    (Public Meteorological Service Center of China Meteorological Administration (CMA), Beijing 10081, China)

  • Xiaowei Zhang

    (Climate Center of the Zhejiang Meteorological Bureau, Hangzhou 310000, China)

Abstract

In view of the high cost and sparse spatial resolution of offshore meteorological observations, ocean winds retrieved from satellites are valuable in offshore wind resource assessment as a supplement to in situ measurements. This study examines satellite synthetic aperture radar (SAR) images from ENVISAT advanced SAR (ASAR) for mapping wind resources with high spatial resolution. Around 181 collected pairs of wind data from SAR wind maps and from 13 meteorological stations in Hangzhou Bay are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a standard deviation ( SD ) of 1.99 m/s and correlation coefficient of R = 0.67. The model wind directions, which are used as input for the SAR wind speed retrieval, show a high correlation coefficient ( R = 0.89) but a large standard deviation ( SD = 42.3°) compared to in situ observations. The Weibull probability density functions are compared at one meteorological station. The SAR-based results appear not to estimate the mean wind speed, Weibull scale and shape parameters and wind power density from the full in situ data set so well due to the lower number of satellite samples. Distributions calculated from the concurrent 81 SAR and in situ samples agree well.

Suggested Citation

  • Rui Chang & Rong Zhu & Merete Badger & Charlotte Bay Hasager & Rongwei Zhou & Dong Ye & Xiaowei Zhang, 2014. "Applicability of Synthetic Aperture Radar Wind Retrievals on Offshore Wind Resources Assessment in Hangzhou Bay, China," Energies, MDPI, vol. 7(5), pages 1-16, May.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:5:p:3339-3354:d:36243
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    Citations

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    Cited by:

    1. Merete Badger & Aito Fujita & Krzysztof Orzel & Daniel Hatfield & Mark Kelly, 2023. "Wind Retrieval from Constellations of Small SAR Satellites: Potential for Offshore Wind Resource Assessment," Energies, MDPI, vol. 16(9), pages 1-19, April.
    2. Li, Delei & Geyer, Beate & Bisling, Peter, 2016. "A model-based climatology analysis of wind power resources at 100-m height over the Bohai Sea and the Yellow Sea," Applied Energy, Elsevier, vol. 179(C), pages 575-589.
    3. Mattar, Cristian & Borvarán, Dager, 2016. "Offshore wind power simulation by using WRF in the central coast of Chile," Renewable Energy, Elsevier, vol. 94(C), pages 22-31.
    4. Li, Jiangxia & Pan, Shunqi & Chen, Yongping & Yao, Yu & Xu, Conghao, 2022. "Assessment of combined wind and wave energy in the tropical cyclone affected region:An application in China seas," Energy, Elsevier, vol. 260(C).
    5. Hadjipetrou, Stylianos & Liodakis, Stelios & Sykioti, Anastasia & Katikas, Loukas & Park, No-Wook & Kalogirou, Soteris & Akylas, Evangelos & Kyriakidis, Phaedon, 2022. "Evaluating the suitability of Sentinel-1 SAR data for offshore wind resource assessment around Cyprus," Renewable Energy, Elsevier, vol. 182(C), pages 1228-1239.
    6. de Assis Tavares, Luiz Filipe & Shadman, Milad & de Freitas Assad, Luiz Paulo & Silva, Corbiniano & Landau, Luiz & Estefen, Segen F., 2020. "Assessment of the offshore wind technical potential for the Brazilian Southeast and South regions," Energy, Elsevier, vol. 196(C).
    7. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren, 2019. "Characterization of wind resource in China from a new perspective," Energy, Elsevier, vol. 167(C), pages 994-1010.
    8. Nie, Bingchuan & Li, Jiachun, 2018. "Technical potential assessment of offshore wind energy over shallow continent shelf along China coast," Renewable Energy, Elsevier, vol. 128(PA), pages 391-399.

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