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Record W2108107626 · doi:10.1002/qj.1889

Interdecadal variability of the ENSO–North Atlantic Oscillation connection in boreal summer

2012· article· en· W2108107626 on OpenAlexaffabout
Zhiwei Wu, Hai Lin

Bibliographic record

VenueQuarterly Journal of the Royal Meteorological Society · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsExtratropical cycloneClimatologyRossby waveNorth Atlantic oscillationBorealEnvironmental scienceAnomaly (physics)Sea surface temperatureEl Niño Southern OscillationAtlantic multidecadal oscillationPacific decadal oscillationSouthern oscillationGeologyOceanographyPhysics

Abstract

fetched live from OpenAlex

Abstract Understanding the combined effect of El Niño–Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO) is of great importance for climate seasonal prediction (extreme climate events in particular). Results in this study show that during the last hundred years (1900 to present), the ENSO–NAO connection experiences a notable interdecadal change in summer (June–August) according to a 21‐year sliding correlation between them, namely, from no significant correlation (uncoupling) before the mid‐1970s to a significant correlation (coupling) after the mid‐1970s. Comparison analysis between the coupling epoch (1977–1997) and the uncoupling epoch (1958–1976) shows that the most pronounced circulation anomalies take place over the extratropical North Pacific. Further analysis and numerical experiments suggest that a poleward‐propagating Rossby wave train, possibly enhanced by sea‐surface‐temperature anomalies in the extratropical North Pacific associated with the developing phases of ENSO during the later epoch, is responsible for connecting the ENSO signal with the NAO. © 2012 Crown in the right of Canada. Published by JohnWiley & Sons Ltd.

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)0.003
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 score0.003
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.240
Teacher spread0.220 · 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

Citations50
Published2012
Admission routes2
Has abstractyes

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