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Record W1990849815 · doi:10.1029/2001jd000681

Synoptic scale study of the Arctic polar vortex's influence on the middle atmosphere, 1, Observations

2002· article· en· W1990849815 on OpenAlexaff
A. J. Gerrard, Timothy J. Kane, J. P. Thayer, T. J. Duck, J. A. Whiteway, Jens Fiedler

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPolar vortexStratosphereAtmosphere (unit)Atmospheric sciencesVortexTroposphereArcticClimatologyGeologyMiddle latitudesSudden stratospheric warmingEnvironmental scienceMeteorologyPhysicsOceanography

Abstract

fetched live from OpenAlex

We present nightly Rayleigh lidar temperature measurements of the high‐latitude middle atmosphere taken at three Arctic sites over similar time periods in midwinter. The four reported case studies depict changes in the thermal structure of the stratosphere and lower mesosphere over a period of days to weeks that can be attributed to movement and interaction of the polar vortex, the Aleutian High, and planetary waves as evidenced from the National Center for Environmental Prediction tropospheric and stratospheric analyses. In cases where substantial (i.e., large horizontal scale) movement of the vortex is observed, it is noted that regional middle atmospheric Arctic temperatures can change by tens of degrees. In other cases, we show that even very subtle (i.e., small horizontal scale) movement of the vortex system over similar timescales can result in notable temperature changes in the regional middle atmosphere. It appears that the observed events are dependant on the location, strength, and structure of the polar vortex and Aleutian High. All of these synoptic scale measurements indicate a change in the local dynamical structure of the middle atmosphere and are discussed in regards to this issue.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.078
GPT teacher head0.279
Teacher spread0.201 · 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.

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

Citations35
Published2002
Admission routes1
Has abstractyes

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