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Estimation of wind speeds inside Super Typhoon Nepartak from AMSR2 low-frequency brightness temperatures

  • Lei Zhang
  • Xiaobin Yin
  • Hanqing Shi
  • Zhenzhan Wang
  • Qing Xu
Research Article

Abstract

Accurate estimations of typhoon-level winds are highly desired over the western Pacific Ocean. A wind speed retrieval algorithm is used to retrieve the wind speeds within Super Typhoon Nepartak (2016) using 6.9- and 10.7-GHz brightness temperatures from the Japanese Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor on board the Global Change Observation Mission-Water 1 (GCOM-W1) satellite. The results show that the retrieved wind speeds clearly represent the intensification process of Super Typhoon Nepartak. A good agreement is found between the retrieved wind speeds and the Soil Moisture Active Passive wind speed product. The mean bias is 0.51 m/s, and the root-mean-square difference is 1.93 m/s between them. The retrieved maximum wind speeds are 59.6 m/s at 04:45 UTC on July 6 and 71.3 m/s at 16:58 UTC on July 6. The two results demonstrate good agreement with the results reported by the China Meteorological Administration and the Joint Typhoon Warning Center. In addition, Feng-Yun 2G (FY-2G) satellite infrared images, Feng-Yun 3C (FY-3C) microwave atmospheric sounder data, and AMSR2 brightness temperature images are also used to describe the development and structure of Super Typhoon Nepartak.

Keywords

microwave radiometer sea surface wind retrieval AMSR2 Nepartak SMAP 

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Notes

Acknowledgements

This work was funded by the National Natural Science Foundation of China (Grant No. 61501433). The authors would like to thank the National Snow and Ice Data Center and the Japan Aerospace Exploration Agency for providing the AMSR2 brightness temperature data. The authors would like to thank the Hurricane Research Division for providing the SFMR data. SMAP data are produced by Remote Sensing Systems and sponsored by the NASA Earth Science funding. The authors declare that they have no conflict of interests regarding the publication of this paper.

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Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Lei Zhang
    • 1
  • Xiaobin Yin
    • 2
  • Hanqing Shi
    • 1
  • Zhenzhan Wang
    • 3
  • Qing Xu
    • 4
  1. 1.Institute of Meteorology and OceanographyNational University of Defense TechnologyNanjingChina
  2. 2.Beijing Piesat Information Technology Co. LtdBeijingChina
  3. 3.National Space Science CenterChinese Academy of SciencesBeijingChina
  4. 4.College of OceanographyHohai UniversityNanjingChina

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