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Record W2077040264 · doi:10.1175/jcli3623.1

Impact of Great Salinity Anomalies on the Low-Frequency Variability of the North Atlantic Climate

2006· article· en· W2077040264 on OpenAlexaboutno aff
Rong Zhang, Geoffrey K. Vallis

Bibliographic record

VenueJournal of Climate · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric AdministrationMet OfficeNational Science Foundation
KeywordsThermohaline circulationOcean gyreAnomaly (physics)ClimatologyBoundary currentGeologyNorth Atlantic oscillationAtlantic multidecadal oscillationOceanographyGulf StreamSea surface temperatureAtlantic Equatorial modeNorth Atlantic Deep WaterSalinityTemperature salinity diagramsOcean current

Abstract

fetched live from OpenAlex

Abstract In this paper, it is shown that coherent large-scale low-frequency variabilities in the North Atlantic Ocean—that is, the variations of thermohaline circulation, deep western boundary current, northern recirculation gyre, and Gulf Stream path—are associated with high-latitude oceanic Great Salinity Anomaly events. In particular, a dipolar sea surface temperature anomaly (warming off the U.S. east coast and cooling south of Greenland) can be triggered by the Great Salinity Anomaly events several years in advance, thus providing a degree of long-term predictability to the system. Diagnosed phase relationships among an observed proxy for Great Salinity Anomaly events, the Labrador Sea sea surface temperature anomaly, and the North Atlantic Oscillation are also discussed.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.015
GPT teacher head0.251
Teacher spread0.236 · 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 designSimulation or modeling
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

Citations74
Published2006
Admission routes1
Has abstractyes

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