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Record W1742193183 · doi:10.1029/2012gl052810

Observed and simulated changes in the Southern Hemisphere surface westerly wind‐stress

2012· article· en· W1742193183 on OpenAlexafffund
Neil C. Swart, John C. Fyfe

Bibliographic record

VenueGeophysical Research Letters · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCoupled model intercomparison projectWesterliesClimatologySouthern HemisphereClimate modelNorthern HemisphereEnvironmental scienceWind stressAtmospheric sciencesForcing (mathematics)Annual cycleClimate changeGeologyOceanography

Abstract

fetched live from OpenAlex

Changes in the position and strength of the Southern Hemisphere surface westerlies have significant implications for ocean circulation and the global carbon cycle. Here we compare the climatologies, as well as the trends, in the position and strength of the surface westerly wind‐stress jet in reanalyses with the Coupled Model Intercomparison Project (CMIP) phase 3 and phase 5 models over the historical period from 1979–2010. We show that both the CMIP3 and CMIP5 models exhibit an equatorward biased climatological jet position. The reanalyses and climate models both show significant trends in annual mean jet strength, though the climate models underestimate the strengthening. Neither reanalyses nor models show a robust trend in annual mean jet position over the historical period, though significant trends do occur in the Austral summer position. We also compare the response of the CMIP3 and CMIP5 model wind‐stresses to a range of anthropogenic forcing scenarios for the 21st century.

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 score0.024
Threshold uncertainty score0.048

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 head0.077
GPT teacher head0.307
Teacher spread0.229 · 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

Citations368
Published2012
Admission routes2
Has abstractyes

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