Spatiotemporal characteristics and mechanisms of upper water exchange between the Arabian Sea and the Bay of Bengal in the North Indian Ocean - Zheng, Defu; Guo, Junru; Fu, Yanzhao; Song, Jun; Cai, Yu (Frontiers in Marine Science, 2025)
The distribution of upper water masses and water exchange processes in the Arabian Sea and Bay of Bengal have important implications for the dynamics, thermal structure, and associated air-sea interactions in the North Indian Ocean. In this study, we apply the spectral clustering method to investigate the distribution patterns and exchange characteristics of Arabian Sea Water (ASW) and Bay of Bengal Water (BBW) under seasonal and interannual variability, with emphasis on the analysis of the spatiotemporal variations and control mechanisms of water fluxes in two main channel sections: the mouth of the Bay of Bengal (6° N) and the central equatorial seas (81° E). The results indicate that the eastward water flux driven by the Southwest Monsoon Current and Wyrtki jets averages 13.93±2.50 Sv (1 Sv = 106/m3) in summer and autumn, and the distribution range of ASW can be extended to the north of 10° N in the Bay of Bengal during this period. The winter–spring BBW incursion into the region west of 73° E in the Arabian Sea and the transport of the Northeast Monsoon Current reach 16.43±1.48 Sv, showing distinct seasonal changes. From 2001 to 2020, water fluxes across the Bay mouth and equatorial channels generally show a positive correlation. Affected by the monsoon transition process and the equatorial half-year Kelvin wave, water flux changes exhibit distinct half-year and one-year cycles. The time series of low salinity water transport anomalies and Dipole Mode Index (DMI) in the Bay mouth and equatorial region are negatively correlated (–0.30 and –0.42), indicating that water exchange is also moderated by Indian Ocean Dipole (IOD) events on the interannual scale. The equatorial region exhibits greater sensitivity to IOD events, reflecting a more complex 2–3 year cycle in water flux variations. These findings highlight the effectiveness of the spectral clustering method in revealing the spatiotemporal patterns of water masses, which is important for understanding the ocean circulation system and associated climate variability in the North Indian Ocean.