Variability of Indonesian Throughflow Transport in the Indonesian Seas during Triple-Dip La Niña

Abstract

Abstract The Indonesian seas serve as an important conduit for the Indonesian Throughflow (ITF), a critical system of warm water and freshwater transport connecting the Pacific and Indian Oceans. El Niño-Southern Oscillation (ENSO) significantly impacts the regional variability in the Pacific and exerts a profound influence on water mass transport from the Pacific to the Indian Oceans. This study focuses on the influence of triple-dip La Niña events during two distinct periods (1998 – 2001 and 2020 – 2023) on the variability of ITF transport in key areas of the Indonesian seas, including the Makassar, Lombok, and Ombai Straits, Flores and Banda Seas, and Timor Passage. Using forecast and reanalysis data from the Copernicus Marine Environment Monitoring Service (CMEMS), transport calculations are conducted across cross-sectional profiles representing the study areas. The results reveal that the volume transport is significantly higher at depths ranging from ∼50 – 300 m. It also shows seasonal fluctuations in volume transport across all regions, with lower transport during winter (DJF) and higher transport during summer (JJA) and transition period (SON) in the Makassar and Lombok Straits. In the Flores and Banda Seas, Ombai Strait, and Timor Passage, the surface volume transport follows seasonal patterns, while at deeper depths (∼50 – 300 m and 300 – 800 m) exhibits distinct fluctuations compared to the surface. Triple-dip La Niña events lead to an overall increase in volume transport during both periods, with the 2019 – 2023 period showing larger values (∼19 Sv) compared to the 1997 – 2001 period (∼14 Sv). The strengthened ocean current during triple-dip La Niña events results in more significant variations in total transport, leading to larger differences between minimum and maximum transport during these periods. The volume transport in Makassar Strait is further analyzed using the Empirical Orthogonal Function (EOF) that identifies three dominant modes (86.4%), revealing the influence of semi-annual, interannual, and decadal factors on the observed variability.