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Record W2580027604 · doi:10.1002/2016gl071895

Gyre‐scale deep convection in the subpolar North Atlantic Ocean during winter 2014–2015

2017· article· en· W2580027604 on OpenAlexaboutno aff
Anne Piron, Virginie Thierry, Herlé Mercier, Guy Caniaux

Bibliographic record

VenueGeophysical Research Letters · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
FundersInstitut national des sciences de l'UniversEuropean Regional Development FundHorizon 2020 Framework ProgrammeMinisterio de Economía y CompetitividadCentre National de la Recherche ScientifiqueEquipexAgence Nationale de la RechercheInstitut Français de Recherche pour l'Exploitation de la Mer
KeywordsOcean gyreThermoclineArgoGeologyMixed layerOceanographyDeep seaConvectionThermohaline circulationClimatologyConvective mixingStructural basinDeep convectionOceanic basinDeep waterNorth Atlantic Deep WaterSubtropicsMeteorologyGeographyGeomorphology

Abstract

fetched live from OpenAlex

Abstract Using Argo floats, we show that a major deep convective activity occurred simultaneously in the Labrador Sea (LAB), south of Cape Farewell (SCF), and the Irminger Sea (IRM) during winter 2014 – 2015. Convection was driven by exceptional heat loss to the atmosphere (up to 50% higher than the climatological mean). This is the first observation of deep convection over such a widespread area. Mixed layer depths exceptionally reached 1700 m in SCF and 1400 m in IRM. The deep thermocline density gradient limited the mixed layer deepening in the Labrador Sea to 1800 m. Potential densities of deep waters were similar in the three basins (27.73 – 27.74 kg m −3 ) but warmer by 0.3°C and saltier by 0.04 in IRM than in LAB and SCF, meaning that each basin formed locally its own deep water. The cold anomaly that developed recently in the North Atlantic Ocean favored and was enhanced by this exceptional convection.

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 score0.007
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.018
GPT teacher head0.267
Teacher spread0.248 · 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
Published2017
Admission routes1
Has abstractyes

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