Intensification and deepening of the Arabian Sea oxygen minimum zone in response to increase in Indian monsoon wind intensity
Bibliographic record
Abstract
Abstract. The decline in oxygen supply to the ocean associated with global warming is expected to expand oxygen minimum zones (OMZs). This global trend can be attenuated or amplified by regional processes. In the Arabian Sea, the world's thickest OMZ is highly vulnerable to changes in the Indian monsoon wind. Evidence from paleo-records and future climate projections indicates strong variations of the Indian monsoon wind intensity over climatic timescales. Yet, the response of the OMZ to these wind changes remains poorly understood and its amplitude and timescale unexplored. Here, we investigate the impacts of perturbations in Indian monsoon wind intensity (from −50 to +50 %) on the size and intensity of the Arabian Sea OMZ, and examine the biogeochemical and ecological implications of these changes. To this end, we conducted a series of eddy-resolving simulations of the Arabian Sea using the Regional Ocean Modeling System (ROMS) coupled to a nitrogen-based nutrient–phytoplankton–zooplankton–detritus (NPZD) ecosystem model that includes a representation of the O2 cycle. We show that the Arabian Sea productivity increases and its OMZ expands and deepens in response to monsoon wind intensification. These responses are dominated by the perturbation of the summer monsoon wind, whereas the changes in the winter monsoon wind play a secondary role. While the productivity responds quickly and nearly linearly to wind increase (i.e., on a timescale of years), the OMZ response is much slower (i.e., a timescale of decades). Our analysis reveals that the OMZ expansion at depth is driven by increased oxygen biological consumption, whereas its surface weakening is induced by increased ventilation. The enhanced ventilation favors episodic intrusions of oxic waters in the lower epipelagic zone (100–200 m) of the western and central Arabian Sea, leading to intermittent expansions of marine habitats and a more frequent alternation of hypoxic and oxic conditions there. The increased productivity and deepening of the OMZ also lead to a strong intensification of denitrification at depth, resulting in a substantial amplification of fixed nitrogen depletion in the Arabian Sea. We conclude that changes in the Indian monsoon can affect, on longer timescales, the large-scale biogeochemical cycles of nitrogen and carbon, with a positive feedback on climate change in the case of stronger winds. Additional potential changes in large-scale ocean ventilation and stratification may affect the sensitivity of the Arabian Sea OMZ to monsoon intensification.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".