An investigation of potential roles of the South China Sea Throughflow on the Indonesian Throughflow seasonal and interannual variability
An investigation of potential roles of the South China Sea Throughflow on the Indonesian Throughflow seasonal and interannual variability
Abstract:
Based on a high-resolution (0.1° × 0.1°) regional ocean model, this study investigates the role of the South China Sea Throughflow (SCSTF) on modulating seasonal and interannual variability of the Indonesian Throughflow (ITF) through two paths: Karimata Strait and Mindoro-Sibutu passages. The model effectiveness in simulating the general circulation and throughflow transports at major straits was first validated against observations, SODA re-analysis and previous results. The model results showed that although the ITF total transport is primarily contributed by the Mindanao Current leaking into the Sulawesi Sea (up to 83%), its seasonal variability is determined jointly by the Mindanao-Sulawesi flow and the SCSTF through the Karimata Strait and the Mindoro-Sibutu passages. The Mindanao-Sulawesi flow reaches a maximum westward transport during summer with a seasonal cycle of 5.6 Sv, while the Mindoro-Sibutu flow has maximum southward transport into the Sulawesi Sea during winter with a seasonal cycle of 3.6 Sv, resulting in a subdued seasonality of 2.8 Sv within Makassar Strait. ENSO signal, transmitted into the SCS and Indonesian seas, play an important role in regulating the SCSTF/ITF interannual variability. The Mindoro-Sibutu flow is enhanced during El Niño as more Pacific water intruded into the SCS via Luzon Strait. This flow forces more buoyant SCS water into the Sulawesi Sea, producing a positive sea surface height (SSH) gradient anomaly against the Mindanao-Sulawesi flow, thus inhibiting Mindanao Current leakage into the Sulawesi Sea. The situation is absent during La Niña years. In contrast, the SCSTF through the Karimata Strait is mostly driven by seasonal monsoons and therefore plays an insignificant role on ITF’s interannual variability.