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Record W2601231088 · doi:10.1175/mwr-d-16-0467.1

Upper-Tropospheric Jet Axis Detection and Application to the Boreal Winter 2013/14

2017· article· en· W2601231088 on OpenAlexaboutno aff
Clemens Spensberger, Thomas Spengler, Camille Li

Bibliographic record

VenueMonthly Weather Review · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersNorges Forskningsråd
KeywordsTropopauseJet streamClimatologyGeologyTroposphereWind shearBorealJet (fluid)Atmospheric sciencesRidgeThermal windTrough (economics)Environmental scienceWind speedPhysicsOceanographyMechanics

Abstract

fetched live from OpenAlex

Abstract This study presents a detection scheme for upper-tropospheric jets. The scheme identifies locations on the dynamical tropopause where the wind shear perpendicular to the wind direction vanishes, and subsequently uses a masking criterion to filter out zero-shear locations that do not belong to jets. The scheme reliably detects jet axes in ERA-Interim data with instantaneous, weekly, or monthly averaged wind fields. The dynamical implications of the detected jet axes and their relation to objectively detected wave breaking and blocking are demonstrated for the synoptic evolution during the boreal winter 2013/14. This winter featured a remarkable episode with a stationary ridge–trough couplet over the American continent leading to anomalously cold conditions from central Canada to the eastern United States. The mean synoptic situation during this episode resembles the climatological winter mean, but featured a more spatially focused jet axis distribution in the northeastern Pacific. The tight distribution suggests that a sequence of similar weather events lead to the mean synoptic conditions. Although the distribution of jet axes and wave breaking events together with the persistence of the anomalous ridge over the northeastern Pacific indicate a blocked situation, the block is not detected with common conventional methods due to the lack of a persistent gradient reversal of potential temperature on the dynamical tropopause. In addition, the importance of subseasonal variations in this winter is demonstrated by pointing out a period in which the jet configuration deviated considerably from the seasonal mean.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.950
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.013
GPT teacher head0.254
Teacher spread0.241 · 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 designOther design
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

Citations52
Published2017
Admission routes1
Has abstractyes

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