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Record W4403980707 · doi:10.1029/2024gl109746

Opposite Trends in the Northern Hemisphere Stratosphere Between Mid‐Winter and Early Spring Linked to Surface Temperature Anomalies

2024· article· en· W4403980707 on OpenAlexaboutno aff
Gwendal Rivière, Fabio D’Andrea, Daniela I. V. Domeisen, Alice Portal

Bibliographic record

VenueGeophysical Research Letters · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
Fundersnot available
KeywordsStratospherePolar vortexNorthern HemisphereTroposphereClimatologyAtmospheric sciencesSudden stratospheric warmingSouthern HemispherePolarAnomaly (physics)GeologyPolar nightEnvironmental scienceVortexMeteorologyGeographyPhysics

Abstract

fetched live from OpenAlex

Abstract Trends in the coupled stratosphere‐troposphere system during the 1979–2022 period are investigated in the Northern Hemisphere using reanalysis datasets. More upward planetary wave propagation in December is shown to precede the deceleration of the stratospheric polar vortex in January. This deceleration prevents the waves from continuing to propagate upward in February and favors an acceleration of the stratospheric polar vortex in March. This is associated with an increased Northern Hemisphere annular mode in March in the stratosphere and the troposphere. Trends show a moderate significance level because of strong interannual variability. Recent seasons whose anomalies project onto the trends are those for which wave‐1 anomaly constructively interferes with wave‐1 climatology in December, which occurs when there is warming in an area extending from Eastern Canada to Greenland and slight cooling over Eurasia. It shows the potential for predicting the springtime stratospheric polar vortex from wintertime wave‐1 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 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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.302
Teacher spread0.270 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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