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Record W4224293338 · doi:10.21203/rs.3.rs-1549156/v1

A new perspective on increased emergence of Central Pacific ENSO in the recent two decades

2022· preprint· en· W4224293338 on OpenAlexaff
Shangfeng Chen, Wen Chen, Bin Yu, Renguang Wu, H.-F. Graf, Lin Chen

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change Canada
FundersJiangsu Collaborative Innovation Center for Climate ChangeNational Natural Science Foundation of ChinaNational Oceanic and Atmospheric AdministrationNational Center for Atmospheric Research
KeywordsPerspective (graphical)El Niño Southern OscillationOceanographyClimatologyGeographyEconomic geographyGeologyComputer science

Abstract

fetched live from OpenAlex

Abstract In this study, we provide a new perspective on the recent increased emergence of the central Pacific type of El Niño and Southern Oscillation (ENSO). Our results indicate that early-spring Aleutian Low (AL) intensity has a remarkable impact on the following winter ENSO especially after the late-1990s. Decrease (increase) in the early-spring AL strength tends to induce an anomalous cyclone (anticyclone) over subtropical North Pacific via wave-mean flow interaction. The anomalous cyclone (anticyclone) leads to sea surface temperature (SST) increase (decrease) in the equatorial Pacific in the following summer via wind-evaporation-SST feedback and trade wind charging mechanism, which further contributes to succeeding central Pacific-like El Niño (La Niña). This remarkable AL’s impact on ENSO is attributable to enhancement of the background trade winds, which is related to changes of both the AMO and NPGO from positive to negative phases around the late-1990s. In contrast, global warming is suggested to have a negative effect on the recent increased connection of the early-spring AL with the following winter ENSO. The results offer the potential to advance our understanding of the factors that explain decrease of the prediction skill of ENSO since the late-1990s.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.088
GPT teacher head0.409
Teacher spread0.321 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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