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Record W4388042354 · doi:10.3389/fmars.2023.1202299

Decadal variability of oxygen uptake, export, and storage in the Labrador Sea from observations and CMIP6 models

2023· article· en· W4388042354 on OpenAlexaffabout
Jannes Koelling, Dariia Atamanchuk, Douglas W.R. Wallace, Johannes Karstensen

Bibliographic record

VenueFrontiers in Marine Science · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsDalhousie University
Fundersnot available
KeywordsOxygenAnomaly (physics)Atmosphere (unit)Coupled model intercomparison projectEnvironmental scienceClimatologyClimate modelAtmospheric sciencesOceanographyClimate changeGeologyMeteorologyChemistryGeography

Abstract

fetched live from OpenAlex

The uptake of dissolved oxygen from the atmosphere via air-sea gas exchange and its physical transport away from the region of uptake are crucial for supplying oxygen to the deep ocean. This process takes place in a few key regions that feature intense oxygen uptake, deep water formation, and physical oxygen export. In this study we analyze one such region, the Labrador Sea, utilizing the World Ocean Database (WOD) to construct a 65–year oxygen content time series in the Labrador Sea Water (LSW) layer (0–2200 m). The data reveal decadal variability associated with the strength of deep convection, with a maximum anomaly of 27 mol m–2 in 1992. There is no long-term trend in the time series, suggesting that the mean oxygen uptake is balanced by oxygen export out of the region. We compared the time series with output from nine models of the Ocean Model Intercomparison Project phase 1 in the Climate Model Intercomparison Project phase 6, (CMIP6-OMIP1), and constructed a “model score” to evaluate how well they match oxygen observations. Most CMIP6-OMIP1 models score around 50/100 points and the highest score is 57/100 for the ensemble mean, suggesting that improvements are needed. All of the models underestimate the maximum oxygen content anomaly in the 1990s. One possible cause for this is the representation of air-sea gas exchange for oxygen, with all models underestimating the mean uptake by a factor of two or more. Unrealistically deep convection and biased mean oxygen profiles may also contribute to the mismatch. Refining the representation of these processes in climate models could be vital for enhanced predictions of deoxygenation. In the CMIP6-OMIP1 multi-model mean, oxygen uptake has its maximum in 1980–1992, followed by a decrease in 1994–2006. There is a concurrent decrease in export, but oxygen storage also changes between the two periods, with oxygen accumulated in the first period and drained out in the second. Consequently, the change in oxygen export (5%) is much less than that in uptake (28%), suggesting that newly ventilated LSW which remains in the formation region acts to buffer the linkage between air-sea gas exchange and oxygen export.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.072
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.208
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2023
Admission routes2
Has abstractyes

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