海洋环流与波动重点实验室知识库

黑潮入侵南海是一种发生于吕宋海峡附近的重要物理现象，它对于南海东北部各尺度的动力过程均有着很强的调制作用。本论文主要基于Regional Ocean Modeling System（ROMS）海洋模式以及条件非线性最优扰动（CNOP）方法，从最优前期征兆（OPR）和最快增长初始误差（OGIE）两个角度研究了黑潮入侵南海的可预报性问题。

研究结果表明，黑潮入侵南海的最优前期征兆位于吕宋海峡南部的海洋上层400米之内，其中海表面高度和海洋内部温度扰动为正值，速度扰动呈顺时针旋转，这些扰动特征均表现为反气旋式中尺度涡的结构。将这种反气旋式扰动叠加到参考态中之后，它可以通过正压不稳定过程从参考态吸收能量并且迅速发展。与此同时，它还会沿着黑潮路径向西北方向运动，并使得吕宋海峡处的黑潮持续向西移动，逐渐形成反气旋式弯曲，最终触发了黑潮入侵南海。这种反气旋式扰动对于黑潮入侵南海的触发作用在HYCOM再分析数据以及AVISO卫星遥感数据中得到了证实。

另一方面，我们计算得到了黑潮入侵南海预报中的两类最快增长初始误差，这两类初始误差同样位于吕宋海峡南部，在第一类误差中，海表面高度和海洋内部温度误差为负，海洋上层的速度误差呈逆时针旋转，此类误差具有气旋式结构，并最终使得预报的黑潮入侵南海幅度偏小，第二类误差的空间结构与第一类相反，具有反气旋式中尺度涡结构，并最终造成了预报的黑潮入侵南海幅度偏大。两类最快增长初始误差的发展机制与最优前期征兆相类似，这也决定了最快增长初始误差和最优前期征兆之间较高的相似性。

最后，我们依据这两类初始误差的空间结构识别了黑潮入侵南海预报的目标观测敏感区。并基于所识别的敏感区以及观测系统模拟试验对于目标观测的效果进行了评估。结果表明，在所识别的敏感区内进行目标观测，可以减小海洋初始场中的误差，进而有效的提高了黑潮入侵南海预报的准确性。

The Kuroshio Intrusion (KI) into the South China Sea (SCS) is a key process that greatly modulates multi-scale dynamics in the northeastern SCS. Using the Regional Ocean Modeling System (ROMS) and the Conditional Nonlinear Optimal Perturbation (CNOP) approach, the predictability of the KI is studied from the perspectives of optimal precursor (OPR) and optimally growing initial error (OGIE).

Our study found that the OPRs obtained by the CNOP approach are located in the southern part of the Luzon Strait and constrained in the upper 400 m. The OPRs exhibit the anticyclonic eddies (AEs) spatial pattern, with positive sea surface height (SSH) perturbations, positive temperature perturbations and clockwise-rotating velocity perturbations. After superimosimg the AE-like perturbation to the reference state, the perturbation grows rapidly and moves northwestward along the Kuroshio path. Simultaneously, this perturbation forces the Kuroshio to continuously move westward and trigger the occurrence of KI at last. The eddy-energetic analysis shows that the rapid growth of the AE-like perturbation is attributed to the barotropic instabilities. Additional examination with the HYCOM oceanic reanalysis and AVISO remote-sensing data further validate the importance of the AE-like perturbations in the KI triggering process.

On the other hand, we obtained two types of OGIEs by the CNOP approach. Both types of OGIEs are also localized in the southern part of the Luzon Strait. The first type of OGIE, with negative SSH, negative temperature and anticlockwise-rotating velocity error, leads to an underestimate of the KI amplitude. The second type of OGIE, manifesting the features of AEs, is nearly opposite the first type, leading to an overestimate of the KI amplitude. The growth mechanism of the OGIEs is similar to that of the OPRs, which determines the high similarity between them.

Finally, we identify the sensitive areas of KI used to implement targeted observations and evaluate the effects of targeted observations with observation system simulation experiment. The evaluation demonstrates that the implement of targeted observations in the sensitive areas could efficiently remove the initial errors and improve the accuracy of KI prediction.