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Record W3131345561 · doi:10.3389/feart.2021.626244

The North American Spring Coldness Response to the Persistent Weak Stratospheric Vortex Induced by Extreme El Niño Events

2021· article· en· W3131345561 on OpenAlexaboutno aff
Xin Zhou, Quanliang Chen, Yang Li, Yawei Yang, Shaobo Zhang, Yong Zhao, Yulei Qi, Jingtao Zhou

Bibliographic record

VenueFrontiers in Earth Science · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaMet Office
KeywordsPolar vortexStratosphereClimatologyTroposphereAtmospheric sciencesEnvironmental scienceMiddle latitudesRidgeAdvectionArctic oscillationPeninsulaOzone layerVortexTrough (economics)GeologyGeographyMeteorologyNorthern HemispherePhysics

Abstract

fetched live from OpenAlex

The stratospheric pathway is a major driver of El Niño–Southern Oscillation (ENSO) impacts on mid-latitude tropospheric circulation and winter weather. The weak vortex induced by El Niño conditions has been shown to increase the risk of cold spells, especially over Eurasia, but its role for North American winters is less clear. This study involved idealized experiments with the Whole Atmosphere Community Climate Model to examine how the weak winter vortex induced by extreme El Niño events is linked to North American coldness in spring. Contrary to the expected mid-latitude cooling associated with a weak vortex, extreme El Niño events do not lead to North American cooling overall, with daily cold extremes actually decreasing, especially in Canada. The expected cooling is absent in most of North America because of the advection of warmer air masses guided by an enhanced ridge over Canada and a trough over the Aleutian Peninsula. This pattern persists in spring as a result of the trapping of stationary waves from the polar stratosphere and troposphere, implying that the stratospheric influence on North America is sensitive to regional downward wave activities.

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 score0.049
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.017
GPT teacher head0.230
Teacher spread0.213 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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