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Record W2030730746 · doi:10.1002/2014jc010322

Oceanic responses to <scp>H</scp>urricane <scp>I</scp>gor over the <scp>G</scp>rand <scp>B</scp>anks: A modeling study

2015· article· en· W2030730746 on OpenAlexafffundabout
Zhimin Ma, Guoqi Han, Brad de Young

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsFisheries and Oceans CanadaMemorial University of Newfoundland
FundersFisheries and Oceans Canada
KeywordsBaroclinityStorm surgeUpwellingSurgeBarotropic fluidSeicheGeologyOceanographyStormSea surface temperatureClimatologyTurbulenceMeteorologyAtmospheric sciencesPhysicsGeomorphology

Abstract

fetched live from OpenAlex

Abstract A three‐dimensional (3‐D) baroclinic finite‐volume ocean model (FVCOM) was developed to examine the oceanic response to Hurricane Igor over the Grand Banks of Newfoundland. Hurricane Igor generated a storm surge of almost 1 m at St. John's and about 0.8 m at three nearby coastal tide gauge stations (Bonavista, Argentia and St. Lawrence). The surge magnitude from the 3‐D baroclinic model agrees approximately with tide‐gauge observations at all four stations, slightly better than that from an alternative 3‐D barotropic case. The sudden drop of sea surface temperature caused by the storm, approximately as observed by buoys, is well simulated by the baroclinic model with a k‐ε turbulence closure. A sensitivity simulation with the Mellor‐Yamada turbulence closure significantly underestimates sea surface cooling. It is shown that the sea surface cooling is mainly associated with turbulent mixing, and to a lesser degree with Ekman upwelling. The model solution shows that the largest surge occurred between Bonavista and St. John's. Further analysis suggests the generation of a free continental shelf wave after the storm made landfall, with the peak surge propagating from St. John's to St. Lawrence.

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)0.006
metaresearch head score (Gemma)0.054
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient 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 score0.276
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.054
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0040.001
Research integrity0.0000.006
Insufficient payload (model declined to judge)0.0000.002

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 head0.077
GPT teacher head0.339
Teacher spread0.262 · 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

Citations20
Published2015
Admission routes3
Has abstractyes

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