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Sea ice identification based on CFOSAT scatterometer
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Jianqiang Liu1, Siqi Liu2, Wenming Lin2, 3, *, Shuyan Lang1, Yijun He2, 3
Haiyang Xuebao | 2023, 45(6) : 134 - 140
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Haiyang Xuebao | 2023, 45(6): 134-140
• Article •
Sea ice identification based on CFOSAT scatterometer
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Jianqiang Liu1, Siqi Liu2, Wenming Lin2, 3, *, Shuyan Lang1, Yijun He2, 3
Affiliations
  • 1National Satellite Ocean Application Service, Beijing 100081, China
  • 2Nanjing University of Information Science and Technology, Nanjing 210044, China
  • 3Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources, Beijing 100081, China
Published: 2023-06-30 doi: 10.12284/hyxb2023069
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The scatterometer onboard China-France Oceanography Satellite (CFOSAT) observes sea surface with abundant viewing geometries, opening up new opportunities for sea ice detection. This paper proposes a Bayesian sea ice detection method for the CFOSAT satellite scatterometer (CSCAT), which only uses the minimal inversion residual derived from the wind inversion procedure, hence it does not need to develop a sea ice geophysical model function (GMF) and to calculate the distance between CSCAT backscatters and sea ice GMF. The results are compared with the sea ice edge data from European Organisation for the Exploitation of Meteorological Satellites, which shows that the normalized standard deviation error of CSCAT daily sea ice extent is about 1% and 7% in the Antarctic and the Arctic, respectively, agreeing well with the prior scatterometers. In summary, the proposed method is advanced in terms of model input parameters, processing speed and detection accuracy, so it is of great significance to the operational ice detection in the satellite ground segment.

China-France Oceanography Satellite (CFOSAT)  /  scatterometer  /  sea ice detection  /  Bayesian theory  /  maximum likelihood estimator
Jianqiang Liu, Siqi Liu, Wenming Lin, Shuyan Lang, Yijun He. Sea ice identification based on CFOSAT scatterometer[J]. Haiyang Xuebao, 2023 , 45 (6) : 134 -140 . DOI: 10.12284/hyxb2023069
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Year 2023 volume 45 Issue 6
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Article Info
doi: 10.12284/hyxb2023069
  • Receive Date：2022-08-18
  • Online Date：2025-12-26
  • Published：2023-06-30
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  • Received：2022-08-18
  • Revised：2022-12-03
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Affiliations
    1National Satellite Ocean Application Service, Beijing 100081, China
    2Nanjing University of Information Science and Technology, Nanjing 210044, China
    3Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources, Beijing 100081, China
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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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