Identifying the sensitive areas in targeted observation for predicting the Kuroshio large meander path in a regional ocean model

Xia Liu; Qiang Wang; Mu Mu

doi:doi:10.1007/s13131-021-1838-7

Volume 41 Issue 2

Feb. 2022

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Xia Liu, Qiang Wang, Mu Mu. Identifying the sensitive areas in targeted observation for predicting the Kuroshio large meander path in a regional ocean model[J]. Acta Oceanologica Sinica, 2022, 41(2): 3-14. doi: doi:10.1007/s13131-021-1838-7

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Xia Liu, Qiang Wang, Mu Mu. Identifying the sensitive areas in targeted observation for predicting the Kuroshio large meander path in a regional ocean model[J]. Acta Oceanologica Sinica, 2022, 41(2): 3-14. doi: doi:10.1007/s13131-021-1838-7

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Identifying the sensitive areas in targeted observation for predicting the Kuroshio large meander path in a regional ocean model

doi: doi:10.1007/s13131-021-1838-7

Xia Liu¹,
Qiang Wang^{2, 3
,
,},
Mu Mu⁴

1.
School of Mathematics, Zhengzhou University of Aeronautics, Zhengzhou 450046, China
2.
Key Laboratory of Marine Hazards Forecasting of Ministry of Natural Resources, Hohai University, Nanjing 210098, China
3.
College of Oceanography, Hohai University, Nanjing 210098, China
4.
Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China

Funds: The National Natural Science Foundation of China under contract Nos 41906003 and 41906022; the Strategic Priority Research Program of Chinese Academy of Sciences under contract No. XDA20060502; the Fundamental Research Funds for the Central Universities under contract No. B200201011; the Basic Research Projects of Key Scientific Research Projects Plan in Henan Higher Education Institutions under contract No. 20zx003.

More Information

Corresponding author: E-mail: wangq@hhu.edu.cn
Received Date: 2021-01-15
Accepted Date: 2021-03-30

Available Online: 2021-11-25

Publish Date: 2022-02-01

Abstract

Abstract

With the Regional Ocean Modeling System (ROMS), this paper investigates the sensitive areas in targeted observation for predicting the Kuroshio large meander (LM) path using the conditional nonlinear optimal perturbation approach. To identify the sensitive areas, the optimal initial errors (OIEs) featuring the largest nonlinear evolution in the LM prediction are first calculated; the resulting OIEs are localized mainly in the upper 2 500 m over the LM upstream region, and their spatial structure has certain similarities with that of the optimal triggering perturbation. Based on this spatial structure, the sensitive areas are successfully identified, located southeast of Kyushu in the region (29°–32°N, 131°–134°E). A series of sensitivity experiments indicate that both the positions and the spatial structure of initial errors have important effects on the LM prediction, verifying the validity of the sensitive areas. Then, the effect of targeted observation in the sensitive areas is evaluated through observing system simulation experiments. When targeted observation is implemented in the identified sensitive areas, the prediction errors are effectively reduced, and the prediction skill of the LM event is improved significantly. This provides scientific guidance for ocean observations related to enhancing the prediction skill of the LM event.
- Kuroshio large meander,
- targeted observation,
- sensitive areas,
- ROMS

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References(35)

References

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