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Record W2130741037 · doi:10.1080/07055900.2015.1013438

Synoptic Climatology of the Southern Beaufort Sea Troposphere with Comparisons to Surface Winds

2015· article· en· W2130741037 on OpenAlexaffvenue
M. G. Asplin, David B. Fissel, Tim Papakyriakou, David G. Barber

Bibliographic record

VenueATMOSPHERE-OCEAN · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of ManitobaASL Environmental Sciences (Canada)
FundersNational Oceanic and Atmospheric Administration
KeywordsClimatologyAtmospheric circulationGlobal wind patternsSea iceArctic ice packForcing (mathematics)TroposphereArcticSynoptic scale meteorologyGeologyEnvironmental scienceBeaufort scaleAtmospheric sciencesOceanography

Abstract

fetched live from OpenAlex

Synoptic-scale atmospheric circulation patterns drive wind forcing of dynamic and thermodynamic processes in Arctic sea ice. Synoptic typing and compositing are common techniques used to identify a limited number of prevailing weather classifications that govern a region's climate. This work investigates atmospheric circulation patterns (surface to 250 hPa) for the southern Beaufort Sea and corresponding surface wind regimes within each synoptic type. Significant changes (p < 0.05) in relative frequencies of a number of synoptic types were attributed to declining summer sea ice. Corresponding upper-level circulation anomalies show increasingly meridional atmospheric circulation. Synoptic Types 9 and 11 were identified as key October-November-December circulation features that represent deepening of the Aleutian low with concomitant strengthening of pressure gradients over the southern Beaufort Sea. Classification of coastal-based wind observations shows a shift towards increased easterly wind forcing. A case study of surface wind data from the CCGS Amundsen (2009–2011) provided a direct example of the surface wind regime within the marginal ice zone within each synoptic type during a period of reduced Arctic sea-ice cover.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.771

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)0.0010.000

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 head0.012
GPT teacher head0.208
Teacher spread0.196 · 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

Citations7
Published2015
Admission routes2
Has abstractyes

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Same venueATMOSPHERE-OCEANSame topicArctic and Antarctic ice dynamicsFrench-language works237,207