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Record W1982971602 · doi:10.1175/jcli-d-13-00374.1

An Objectively Determined Blocking Index and its Northern Hemisphere Climatology

2013· article· en· W1982971602 on OpenAlexafffund
David Small, Eyad H. Atallah, John R. Gyakum

Bibliographic record

VenueJournal of Climate · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaNational Center for Atmospheric Research
KeywordsClimatologyBlocking (statistics)Northern HemisphereAnticycloneEnvironmental scienceSouthern HemisphereGeologyMathematics

Abstract

fetched live from OpenAlex

Abstract A modified blocking index is defined based on vertically integrated potential vorticity. The application of this index identifies blocking activity over the Northern Hemisphere during all seasons. The index is developed by systematically identifying the magnitude and spatial scale that best characterizes persistent anticyclonic circulation anomalies in different seasons. By applying a systematic approach to the detection of blocking, the interannual, seasonal, and intraseasonal patterns of blocking frequency across the Northern Hemisphere are able to be characterized. The results are consistent with previous studies in finding that blocking is more frequent in the cold season months than in the warm season, although the results suggest that blocking occurs much more frequently in the summer and fall than many studies have previously reported. By examining blocking frequency monthly, interesting patterns of intraseasonal variability are found, especially over the central Pacific in August and the eastern Pacific in September and October, where blocking is nearly as frequent as in the winter. Possible explanations for this intraseasonal variability are discussed.

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 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 score0.151
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.247
Teacher spread0.236 · 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

Citations33
Published2013
Admission routes2
Has abstractyes

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