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Record W3178524297 · doi:10.1088/1748-9326/ac1375

Modeling evidence for large, ENSO-driven interannual wintertime AMOC variability

2021· article· en· W3178524297 on OpenAlexaff
Karen L. Smith, Lorenzo M. Polvani

Bibliographic record

VenueEnvironmental Research Letters · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNational Science Foundation
KeywordsClimatologyEl Niño Southern OscillationEnvironmental scienceClimate modelMode (computer interface)General Circulation ModelNorth Atlantic oscillationClimate changeGeologyOceanography

Abstract

fetched live from OpenAlex

Abstract Recently established North Atlantic ocean observing arrays, such as RAPID/MOCHA, have revealed a large degree of high-frequency variability in the Atlantic Meridional Overturning Circulation (AMOC). Climate modeling studies of the AMOC, however, have traditionally focused on the low-frequency variability of the annual mean AMOC, with an emphasis on multi-decadal and longer time-scale variability. Thus, little is known about the sources of interannual wintertime, wind-driven AMOC variability. Analyzing the Community Earth System Model, we here show the existence of a robust leading mode of interannual variability in the wintertime AMOC that is distinct from the leading mode of the annual mean. We further show that this mode of variability is significantly linked to the El Niño-Southern Oscillation via the North Atlantic Oscillation.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.097
GPT teacher head0.360
Teacher spread0.263 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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