Hypoxia is increasing in coastal oceans. This is because eutrophication has increased oxygen consumption, while less oxygen is replenished to the bottom under stronger stratification. Quantifying these biogeochemical and physical drivers is important for management and predicting future trends. By using observations from the Pearl River Estuary (PRE) region (10-70 m deep) and similar coastal systems, this paper introduces a simple analysis to quantify both the biogeochemical and physical drivers of hypoxia. We show that in the PRE region, sediment respires >60% of organic matter produced in the water column, leading to high sediment oxygen uptake (average 41.1±16.3 mmol m-2 d-1) and shallow oxygen penetrations (2-7 mm). The sediment’s effect on the bottom oxygen loss becomes stronger with the reducing thickness of the bottom boundary layer. We then construct a generic mass-balance model to quantify oxygen loss, determine timescales of hypoxia formation, and explain within- and cross-system variabilities.

Forecasting rapid intensification (RI) of tropical cyclones (TC) is a mission known for large errors. One under-researched factor that affects TC intensification is sea surface salinity (SSS), which is an important proxy for density stratification in certain ocean regions and can affect the surface enthalpy flux under a strengthening hurricane. To investigate the effects of SSS on TC RI, we use a previously built statistical model consisting of a variety of machine learning (ML) methods. A calibrator was trained on top of the ML models to correct probability forecasts. The ML model performance is improved with the addition of SSS in the Eastern North Pacific and the Caribbean subregion of the North Atlantic. Limited improvement is found in the Western North Pacific. In the Indian Ocean, SSS is also notably correlated with RI occurrence, but the TC samples are not sufficient to train ML models.