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Powerful computer simulations are revealing new insights into water exchanges between the Red Sea and the Gulf of Aden.

The generation and propagation of internal tides in the Andaman Sea are investigated using a three-dimensional high-resolution numerical model. Three categories of experiments, including driving the model with four main semidiurnal tides (M2, S2, N2, and K2), four main diurnal tides (K1, O1, P1, and Q1), and eight main tides (M2, S2, N2, K2, K1, O1, P1, and Q1), are designed to examine the effects of barotropic tides. The results show that the semidiurnal internal tides are dominant in the Andaman Sea, and the inclusion of diurnal barotropic tides negligibly modulates this result. That is partly due to the strength of the diurnal barotropic tides is generally one order smaller than that of the semidiurnal barotropic tides in this region. The sensitivity experiments put this on a firmer footing. In terms of the internal tidal energy, the experiments driven by the diurnal barotropic tides are three orders and one order smaller than those driven by the semidiurnal barotropic tides, respectively, during the spring and neap tides. In addition, the experiments result in total barotropic-to-baroclinic energy conversion rates over the Andaman Sea 29.15 GW (driven by the eight tides), 29.24 GW (driven by the four semidiurnal tides), and 0.05 GW (driven by the fourdiurnal tides) in the spring tidal period and 3.08 GW, 2.56 GW, and 0.31 GW in the neap tidal period, respectively. Four potential generation regions of internal tides are found, three of which are in the Andaman and Nicobar Islands and one in the northeastern Andaman Sea.

Oceanic dissolved oxygen (DO) decline in the Indian Ocean has profound implications for Earth's climate and human habitation in Eurasia and Africa. Owing to sparse observations, there is little research on DO variations, regional comparisons, and its relationship with marine environmental changes in the entire Indian Ocean. In this study, we applied different machine learning algorithms to fit regression models between measured DO, ocean reanalysis physical variables, and spatiotemporal variables. We utilized the Extremely Randomized Trees (ERT) model with the best performance, inputting complete reanalysis data and spatiotemporal information to reconstruct a four-dimensional DO dataset of the Indian Ocean during 1980-2019. The evaluation results showed that the ERT-based DO dataset was superior to the DO simulations in Earth System Models across different time and space. Furthermore, we assessed the spatiotemporal variations in reconstructed DO dataset. DO decline and oxygen-minimum zone (OMZ) expansion were prominent in the Arabian Sea, Bay of Bengal, and Equatorial Indian Ocean. Through correlation analysis, we found that temperature and salinity changes related to solubility primarily control the oxygen decrease in the middle and deep sea. However, the complicated factors with solubility change, vertical mixing, and circulation govern the oxygen increase in the upper and middle sea. Finally, we conducted a volume integral to estimate the oxygen content in the Indian Ocean. Overall, a deoxygenation trend of −141.5 ± 15.1 Tmol dec−1 was estimated over four decades, with a slowdown trend of −68.9 ± 31.3 Tmol dec−1 after 2000. Under global warming and climate change, OMZ expanding and deoxygenation in the Indian Ocean are gradually mitigating. This study enhances our understanding of DO dynamics of the Indian Ocean in response to deoxygenation.