MétaCan
Menu
Back to cohort
Record W2093562782 · doi:10.1029/2006jc003642

Water properties and circulation in Arctic Ocean models

2007· article· en· W2093562782 on OpenAlexaff
Greg Holloway, Frédéric Dupont, Elena Golubeva, Sirpa Häkkinen, Elizabeth Hunke, Meibing Jin, Michael Kärcher, Frank Kauker, Mathew Maltrud, M. Á. Morales Maqueda, Wieslaw Maslowski, G. A. Platov, Donald Stark, Michael Steele, Tatsuo Suzuki, Jia Wang, J. Zhang

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversité LavalFisheries and Oceans Canada
FundersNatural Environment Research CouncilSight Research UK
KeywordsHaloclineGeologyArcticEddyClimatologyThe arcticOcean currentTemperature salinity diagramsLatitudeOceanographySalinityMeteorologyGeodesyTurbulenceGeography

Abstract

fetched live from OpenAlex

As a part of the Arctic Ocean Model Intercomparison Project, results from 10 Arctic ocean/ice models are intercompared over the period 1970 through 1999. Models' monthly mean outputs are laterally integrated over two subdomains (Amerasian and Eurasian basins), then examined as functions of depth and time. Differences in such fields as averaged temperature and salinity arise from models' differences in parameterizations and numerical methods and from different domain sizes, with anomalies that develop at lower latitudes carried into the Arctic. A systematic deficiency is seen as AOMIP models tend to produce thermally stratified upper layers rather than the “cold halocline”, suggesting missing physics perhaps related to vertical mixing or to shelf‐basin exchanges. Flow fields pose a challenge for intercomparison. We introduce topostrophy, the vertical component of V × ∇ D where V is monthly mean velocity and ∇ D is the gradient of total depth, characterizing the tendency to follow topographic slopes. Positive topostrophy expresses a tendency for cyclonic “rim currents”. Systematic differences of models' circulations are found to depend strongly upon assumed roles of unresolved eddies.

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)0.002
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 score0.063
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.272
Teacher spread0.225 · 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

Citations141
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Geophysical Research AtmospheresSame topicArctic and Antarctic ice dynamicsFrench-language works237,207