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Record W2416278938 · doi:10.1002/2016gl067862

Austral winter external and internal atmospheric variability between 1980 and 2014

2016· article· en· W2416278938 on OpenAlexaff
Hui Ding, Richard J. Greatbatch, Hai Lin, Felicitas Hansen, Gereon Gollan, Thomas Jung

Bibliographic record

VenueGeophysical Research Letters · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change Canada
FundersBundesministerium für Bildung und Forschung
KeywordsEmpirical orthogonal functionsPredictabilityClimatologySouthern HemisphereAtmospheric circulationMonsoonNorthern HemisphereMode (computer interface)Environmental scienceSea surface temperatureAtmospheric dynamicsAtmospheric researchAtmospheric sciencesGeologyGeographyAtmosphere (unit)Meteorology

Abstract

fetched live from OpenAlex

Abstract We examine the interannual variability of the seasonal mean atmospheric circulation in the Southern Hemisphere during austral winter. The three major modes are identified by rotated empirical orthogonal function (REOF) analysis. As expected, REOF1 is associated with the Southern Annular Mode which is dominated by internal atmospheric dynamics. REOF2 displays a wave train, linked to the western North Pacific monsoon and the Pacific‐Japan pattern in East Asia in the same season; REOF3 resembles the Pacific‐South American pattern. Externally forced variability strongly projects on both REOF2 and REOF3 so that in the ensemble mean, an atmospheric model with prescribed observed sea surface temperature captures considerable parts of the time evolution of REOF2 (50%) and REOF3 (25%), suggesting a potential predictability for the two modes.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.031
GPT teacher head0.304
Teacher spread0.272 · 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 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

Citations7
Published2016
Admission routes1
Has abstractyes

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