Institutional Repository of Key Laboratory of Ocean Circulation and Wave Studies, Institute of Oceanology, Chinese Academy of Sciences
| Effects of Wind Stress Uncertainty on Short-Term Prediction of the Kuroshio Extension State Transition Process | |
Zhang, Hui1,2 ; Wang, Qiang3,4; Mu, Mu1,5,6; Zhang, Kun1; Geng, Yu7,8
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| 2023-12-01 | |
| 发表期刊 | JOURNAL OF PHYSICAL OCEANOGRAPHY
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| ISSN | 0022-3670 |
| 卷号 | 53期号:12页码:2751-2771 |
| 通讯作者 | Wang, Qiang(wangq@hhu.edu.cn) |
| 摘要 | Based on the conditional nonlinear optimal perturbation for boundary condition method and Regional Ocean Modeling System (ROMS), this study investigates the influence of wind stress uncertainty on predicting the short-term state transitions of the Kuroshio Extension (KE). The optimal time-dependent wind stress errors that lead to maximum prediction errors are obtained for two KE stable-to-unstable and two reverse transitions, which exhibit local multieddies structures with decreasing magnitude as the end time of prediction approaches. The optimal boundary errors initially induce small oceanic errors through Ekman pumping. Subsequently, these errors grow in magnitude as oceanic internal processes take effect, which exerts significant influences on the short-term prediction of the KE state transition process. Specifically, during stable -to-unstable (unstable-to-stable) transitions, the growing error induces an overestimation (underestimation) of the meridional sea surface height gradient across the KE axis, leading to the predicted KE state being more (less) stable. Furthermore, the dynamics mechanism analysis indicates that barotropic instability is crucial for the error growth in the prediction of both the stable-to-unstable and the reverse transition processes due to the horizontal shear of flow field. But work generated by wind stress error plays a more important role in the prediction of the unstable-to-stable transitions because of the synergistic effect of strong wind stress error and strong oceanic error. Eventually, the sensitive areas have been identified based on the optimal boundary errors. Reducing wind stress errors in sensitive areas can significantly improve prediction skills, offering theoretical guidance for devising observational strategies. |
| 关键词 | Wind Forecast verification/skill Numerical weather prediction/forecasting Mesoscale models |
| DOI | 10.1175/JPO-D-23-0047.1 |
| 收录类别 | SCI |
| 语种 | 英语 |
| 资助项目 | National Natural Science Foundation of China[42076017] ; National Key Scientific and Technological Infrastructure project Earth System Numerical Simulation Facility (EarthLab) ; Institute of Oceanology, Chinese Academy of Sciences ; Key Scientific Research Projects Plan in Henan Higher Education Institutions[24A170031] ; Oceanographic Data Center |
| WOS研究方向 | Oceanography |
| WOS类目 | Oceanography |
| WOS记录号 | WOS:001113301100002 |
| 出版者 | AMER METEOROLOGICAL SOC |
| WOS关键词 | NONLINEAR OPTIMAL PERTURBATION ; SEA-SURFACE WIND ; DECADAL VARIABILITY ; OYASHIO EXTENSION ; ATMOSPHERIC CIRCULATION ; ADJOINT SENSITIVITY ; INITIAL ERRORS ; GULF-STREAM ; OCEAN ; MODEL |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.qdio.ac.cn/handle/337002/184123 |
| 专题 | 海洋环流与波动重点实验室 |
| 通讯作者 | Wang, Qiang |
| 作者单位 | 1.Chinese Acad Sci, Inst Oceanol, CAS Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Hohai Univ, Key Lab Marine Hazards Forecasting, Minist Nat Resources, Nanjing, Peoples R China 4.Hohai Univ, Coll Oceanog, Nanjing, Peoples R China 5.Fudan Univ, Dept Atmospher & Ocean Sci, Shanghai, Peoples R China 6.Fudan Univ, Inst Atmospher Sci, Shanghai, Peoples R China 7.Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing, Peoples R China 8.Chinese Acad Meteorol Sci, Inst Tibetan Plateau Meteorol, Beijing, Peoples R China |
| 第一作者单位 | 中国科学院海洋研究所 |
| 推荐引用方式 GB/T 7714 | Zhang, Hui,Wang, Qiang,Mu, Mu,et al. Effects of Wind Stress Uncertainty on Short-Term Prediction of the Kuroshio Extension State Transition Process[J]. JOURNAL OF PHYSICAL OCEANOGRAPHY,2023,53(12):2751-2771. |
| APA | Zhang, Hui,Wang, Qiang,Mu, Mu,Zhang, Kun,&Geng, Yu.(2023).Effects of Wind Stress Uncertainty on Short-Term Prediction of the Kuroshio Extension State Transition Process.JOURNAL OF PHYSICAL OCEANOGRAPHY,53(12),2751-2771. |
| MLA | Zhang, Hui,et al."Effects of Wind Stress Uncertainty on Short-Term Prediction of the Kuroshio Extension State Transition Process".JOURNAL OF PHYSICAL OCEANOGRAPHY 53.12(2023):2751-2771. |
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