Optimal Precursors Triggering the Kuroshio Intrusion Into the South China Sea Obtained by the Conditional Nonlinear Optimal Perturbation Approach

Abstract

The Kuroshio Intrusion (KI) into the South China Sea (SCS) is a key process that greatly modulates the variability of dominant phenomena in the northern SCS. Using the Regional Ocean Modeling System, the optimal precursor (OPR) triggering the KI is obtained by the Conditional Nonlinear Optimal Perturbation (CNOP) approach. The OPRs exhibit the anticyclonic eddies (AEs) spatial pattern in the southern region (19°N–20.3°N, 119°E–122°E) of the Luzon Strait. The evolution processes of the OPRs indicate that the northwestward movement and rapid growth of AEs force the Kuroshio to bend westward continuously, which leads to the transition of the Kuroshio path from leaping state to intruding state. Eddy‐energetic analyses suggested that the barotropic instabilities are responsible for the evolution of the OPRs and thus triggering the KI, while the local wind stress plays a minor role in the triggering process. Additional examinations based on satellite altimeter data and ocean reanalysis data further confirm that the AE‐like perturbation similar to the obtained OPR indeed plays a key role in the KI triggering process.

Improving the thermal structure predictions in the Yellow Sea by conducting targeted observations in the CNOP-identified sensitive areas

“…To investigate the utility of targeted observation in improving the prediction of thermal structures in the shallow YS, the Regional Ocean Modeling System (ROMS) was used to solve the three-dimensional Reynolds-averaged hydrostatic Navier–Stokes equation with the Boussinesq approximation 23 . The ROMS utilizes a nonlinear terrain-following vertical coordinate and has been proven to be suitable for regional ocean modeling by a large number of studies 24 – 27 . The K-profile parameterization scheme is used to calculate the vertical eddy viscosity and diffusivity 28 .…”

“…Utilizing the CNOP approach, the optimal initial errors that cause the largest nonlinear forecast uncertainty can be calculated, and their spatial patterns help to locate the sensitive areas. To date, CNOP-identified sensitive areas have been proven to be quite effective in a number of oceanic applications, such as the prediction of the ENSO 33 , upstream Kuroshio transport 27 , Kuroshio intrusion into the SCS 24 , Kuroshio large meander 12 and the ocean state in the SCS western boundary current region 10 .…”

“…Generally, CNOP computation relies on the adjoint technique to calculate the gradient of the objective function. However, directly calculating CNOP in a complicated model requires a considerable amount of coding and is computationally expensive 24 , 27 , 35 . Alternatively, in this study, we use an Empirical Orthogonal Function (EOF) based algorithm proposed by Wang and Tan 35 to approximate the CNOP without using the adjoint technique (hereafter referred to as the EOF-CNOP algorithm).…”

Increasingly important role of numerical modeling in oceanic observation design strategy: A review

“…In the upstream region, the Kuroshio intrusion into the South China Sea is another important event worth investigating. With the ROMS simulation, Liang et al (2019) found that the CNOPs triggering the Kuroshio intrusion into the South China Sea to be localized in the southern part of the Luzon Strait. Additional observations in this area can achieve more than 40.0% improvement for predicting the intrusion process (Liang, 2019).…”

“…Using the particle-filtering approach, Kramer et al (2012) provided insight into the optimal observation locations for more effectively predicting the decadal path transitions of the Kuroshio Extension (KE). During the past decade, our group has focused on the optimal observation designs for improved prediction of large-scale variations of the Kuroshio (Wang et al, 2013;Liu et al, 2018;Liang et al, 2019; Zhang et al, 2019). We will introduce the details of these studies in the following section.…”