Assimilation of combining satellite remote sensing and <i>in-situ</i> observation based on space-time four-dimensional multi-scale analysis method

Liu Hanyu; Li Wei; Han Guijun; Shao Qi; Liang Kangzhuang; Hu Yan; Wang Ru; Hu Song

doi:10.12284/hyxb2023111

Volume 45 Issue 7

Jul. 2023

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Liu Hanyu，Li Wei，Han Guijun, et al. Assimilation of combining satellite remote sensing and in-situ observation based on space-time four-dimensional multi-scale analysis method[J]. Haiyang Xuebao，2023, 45(7)：110–125 doi: 10.12284/hyxb2023111

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Liu Hanyu，Li Wei，Han Guijun, et al. Assimilation of combining satellite remote sensing and in-situ observation based on space-time four-dimensional multi-scale analysis method[J]. Haiyang Xuebao，2023, 45(7)：110–125 doi: 10.12284/hyxb2023111

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Assimilation of combining satellite remote sensing and in-situ observation based on space-time four-dimensional multi-scale analysis method

doi: 10.12284/hyxb2023111

Liu Hanyu^1
,,
Li Wei^{1, 2
,
,},
Han Guijun^{1
,
,},
Shao Qi¹,
Liang Kangzhuang²,
Hu Yan¹,
Wang Ru¹,
Hu Song¹

1.
Tianjin Key Laboratory for Marine Environmental Research and Service, School of Marine Science and Technology, Tianjin University, Tianjin 300072, China
2.
Tianjin Key Laboratory for Oceanic Meteorology, Tianjin 300074, China

Received Date: 2022-10-01
Rev Recd Date: 2022-12-03

Available Online: 2023-09-20

Publish Date: 2023-07-01

Abstract

Abstract

Fully integrating the use of satellite remote sensing and in-situ observation information to build a high-quality underwater temperature and salinity fields is a frontier topic in the development of marine scientific research. Currently, the vast majority of assimilation systems use assimilation schemes that require the assumption that elements have some artificially predetermined relationship between the surface and underwater. As a result, the temperature and salinity analysis field was more man-made and could not objectively reflect the real state of the ocean. This paper proposed a scheme that did not make any relationship assumptions, only relied on the complementary effects of different types of observation data in time and space, and combined the satellite remote sensing and in-situ observations for spatio-temporal four-dimensional multiscale objective analysis. Compared with the experimental results of assimilating these two types of observation data separately, it was found that the method could not only obtain more accurate temperature and salinity profile structure characteristics, but also reflect the detailed information of the mesoscale changes in the sea surface, the multi-scale information in the observation data was extracted to the maximum, and the effect of “1 + 1 > 2” was realized, and constructed a completely objective temperature and salinity analysis field. The results also showed that assimilating satellite remote sensing sea surface salinity data can effectively improve the analysis of temperature and salinity, which proved that the role of satellite remote sensing sea surface salinity observation on temperature and salinity assimilation could not be ignored.
- multi-scale analysis,
- satellite remote sensing,
- field observation,
- multi-grid four-dimensional variational method

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References(27)

References

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