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Record W2944715505 · doi:10.1029/2018gl081631

Strong Intensification of the Arabian Sea Oxygen Minimum Zone in Response to Arabian Gulf Warming

2019· article· en· W2944715505 on OpenAlexfundno aff
Zouhair Lachkar, Marina Lévy, K. Shafer Smith

Bibliographic record

VenueGeophysical Research Letters · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
FundersYork UniversityNew York University Abu Dhabi
KeywordsOxygen minimum zoneOceanographySink (geography)SalinityBiogeochemistryClimate changeHypoxia (environmental)Global warmingEnvironmental scienceGeologyClimatologyUpwellingOxygenGeography

Abstract

fetched live from OpenAlex

Abstract The highly saline, oxygen‐saturated waters of the Arabian Gulf (hereafter the Gulf) sink to intermediate depths (200–300 m) when they enter the Arabian Sea, ventilating the World's thickest oxygen minimum zone (OMZ). Here, we investigate the impacts of a warming of the Gulf consistent with climate change projections on the intensity of this OMZ. Using a series of eddy‐resolving model simulations, we show that the warming of the Gulf waters increases their buoyancy and hence limits their contribution to the ventilation of intermediate depths. This leads to an intensification of the OMZ and an increase in denitrification that depletes subsurface nitrate and limits deoxygenation at depth. The projected future concomitant increase of Gulf salinity only partially reduces the OMZ intensification. Our findings highlight the importance of the Arabian marginal seas for the biogeochemistry of the North Indian Ocean and stress the need for improving their representation in global climate models.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.269
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations100
Published2019
Admission routes1
Has abstractyes

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