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Record W3016446540 · doi:10.1029/2019pa003832

The Impact of Astronomical Forcing on Surface and Thermocline Variability Within the Western Pacific Warm Pool Over the Past 160 kyr

2020· article· en· W3016446540 on OpenAlexaff
Martina Hollstein, Mahyar Mohtadi, Markus Kienast, Yair Rosenthal, Jeroen Groeneveld, Delia W Oppo, John Southon, Andreas Lückge

Bibliographic record

VenuePaleoceanography and Paleoclimatology · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsDalhousie University
FundersBundesministerium für Bildung und ForschungDeutsche Forschungsgemeinschaft
KeywordsWestern Hemisphere Warm PoolThermoclineOceanographyGeologyClimatologyEquatorSea surface temperaturePacific decadal oscillationLatitude

Abstract

fetched live from OpenAlex

Abstract The Western Pacific Warm Pool (WPWP) constitutes an important component within the global climate system by providing an enormous amount of heat and moisture to the global atmosphere. Nevertheless, past variability of oceanography and climate across the WPWP is still debated. Here, we compile newly generated and published surface and thermocline temperature and seawater stable oxygen isotope (δ 18 O SW ) records from the WPWP north and south of the equator to monitor its variability, particularly in response to astronomical forcing, over the last glacial‐interglacial cycle. We find a coherent first‐order variability in all records from the northern and southern WPWP sites over the past 160 kyr indicating a relatively stable WPWP spatial structure. The second‐order variability is modulated by regionally varying influences. Precipitation varied uniformly across the WPWP marine realm. Thermocline records illustrate the influence of both northern and southern Pacific waters on the WPWP. Differences between the thermocline temperature records are attributed to the differing effect of obliquity on the thermocline water masses influencing the individual sites. Precession exerts an influence on the thermocline at both northern and southern WPWP sites. Variations in thermocline conditions in the precession band are attributed to a combination of modifications in the thermocline source waters, changes in the regional atmospheric circulation and the El Niño‐Southern Oscillation regime.

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)0.002
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 score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.250
Teacher spread0.233 · 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

Citations27
Published2020
Admission routes1
Has abstractyes

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