MétaCan
Menu
Back to cohort
Record W2045123563 · doi:10.1175/2007jcli1480.1

The Enhanced PNA-Like Climate Response to Pacific Interannual and Decadal Variability

2007· article· en· W2045123563 on OpenAlexaff
Bin Yu, Amir Shabbar, Francis W. Zwiers

Bibliographic record

VenueJournal of Climate · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsClimatologyPacific decadal oscillationMiddle latitudesTroposphereEnvironmental scienceAtmospheric circulationEl Niño Southern OscillationTeleconnectionTropicsAnomaly (physics)LatitudeWalker circulationOceanographyGeology

Abstract

fetched live from OpenAlex

Abstract This study provides further evidence of the impacts of tropical Pacific interannual [El Niño–Southern Oscillation (ENSO)] and Northern Pacific decadal–interdecadal [North Pacific index (NPI)] variability on the Pacific–North American (PNA) sector. Both the tropospheric circulation and the North American temperature suggest an enhanced PNA-like climate response and impacts on North America when ENSO and NPI variability are out of phase. In association with this variability, large stationary wave activity fluxes appear in the mid- to high latitudes originating from the North Pacific and flowing downstream toward North America. Atmospheric heating anomalies associated with ENSO variability are confined to the Tropics, and generally have the same sign throughout the troposphere with maximum anomalies at 400 hPa. The heating anomalies that correspond to the NPI variability exhibit a center over the midlatitude North Pacific in which the heating changes sign with height, along with tropical anomalies of comparable magnitudes. Atmospheric heating anomalies of the same sign appear in both the tropical Pacific and the North Pacific with the out-of-phase combination of ENSO and NPI. Both sources of variability provide energy transports toward North America and tend to favor the occurrence of stationary wave anomalies.

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)0.014
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.629
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.001
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)0.0000.000

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 head0.008
GPT teacher head0.269
Teacher spread0.261 · 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

Citations53
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of ClimateSame topicClimate variability and modelsFrench-language works237,207