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Record W2070837871 · doi:10.1175/2008jcli2611.1

Temporal Variability in the Expression of the Arctic Oscillation in the North Pacific

2008· article· en· W2070837871 on OpenAlexaff
Hongxu Zhao, G. W. K. Moore

Bibliographic record

VenueJournal of Climate · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNorth Atlantic oscillationClimatologyPacific decadal oscillationNorthern HemisphereArctic oscillationGeologyArcticArctic dipole anomalyOceanographyArctic ice packSea iceSea surface temperatureDrift ice

Abstract

fetched live from OpenAlex

Abstract Although the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) have been identified as important modes of climate variability during the Northern Hemisphere (NH) winter, whether the AO or the NAO is more fundamental to the description of this variability, especially in the North Pacific, is still an open question. An important contributor to this uncertainty is the lack of knowledge of the low-frequency linkages between the North Atlantic and North Pacific Oceans. This paper explores the linkage between the two oceanic basins on interdecadal time scales using the sea level pressure (SLP) field during the twentieth century. In particular, it is shown that the winter mean SLP in the North Pacific was positively correlated with the sign of the NAO during the periods of 1925–50 and 1980–98, which resulted in the classical AO pattern being the dominant mode in the NH. In contrast, during the period of 1951–79, the winter mean SLP in the two basins was decoupled, resulting in a dominant mode that more closely resembled the NAO. Using paleoclimate reconstructions, it is also shown that this interdecadal variability in the North Pacific climate began around 1850, which is nominally considered to be the end of the Little Ice Age.

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)0.004
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 score0.008
Threshold uncertainty score0.143

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 head0.026
GPT teacher head0.247
Teacher spread0.221 · 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

Citations22
Published2008
Admission routes1
Has abstractyes

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