Sea ice identification based on CFOSAT scatterometer

Liu Jianqiang; Liu Siqi; Lin Wenming; Lang Shuyan; He Yijun

doi:10.12284/hyxb2023069

Volume 45 Issue 6

Jun. 2023

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Liu Jianqiang，Liu Siqi，Lin Wenming, et al. Sea ice identification based on CFOSAT scatterometer[J]. Haiyang Xuebao，2023, 45(6)：134–140 doi: 10.12284/hyxb2023069

Citation:

Liu Jianqiang，Liu Siqi，Lin Wenming, et al. Sea ice identification based on CFOSAT scatterometer[J]. Haiyang Xuebao，2023, 45(6)：134–140 doi: 10.12284/hyxb2023069

Citation:

Liu Jianqiang，Liu Siqi，Lin Wenming, et al. Sea ice identification based on CFOSAT scatterometer[J]. Haiyang Xuebao，2023, 45(6)：134–140 doi: 10.12284/hyxb2023069

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Sea ice identification based on CFOSAT scatterometer

doi: 10.12284/hyxb2023069

Liu Jianqiang^1
,,
Liu Siqi²,
Lin Wenming^{2, 3
,
,},
Lang Shuyan¹,
He Yijun^{2, 3}

1.
National Satellite Ocean Application Service, Beijing 100081, China
2.
Nanjing University of Information Science and Technology, Nanjing 210044, China
3.
Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources, Beijing 100081, China

Received Date: 2022-08-18
Rev Recd Date: 2022-12-03

Available Online: 2023-06-15

Publish Date: 2023-06-30

Abstract

Abstract

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

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References(17)

References

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