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Record W2056945987 · doi:10.1029/2001jd900207

A regional climate model coupled to ocean waves: Synoptic to multimonthly simulations

2001· article· en· W2056945987 on OpenAlexaboutno aff
William Perrie, Yaocun Zhang

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
Fundersnot available
KeywordsClimate modelClimatologyStormConvectionCoupling (piping)Wave modelAtmospheric sciencesEnvironmental scienceAtmospheric modelMeteorologyGeologyGeophysicsPhysicsClimate changeOceanography

Abstract

fetched live from OpenAlex

The NCAR regional climate model RegCM is coupled to the WAM ocean model, using the sea‐state‐dependent roughness parameterization derived in the HEXOS experiment. Coupled model simulations are shown to give reduced wind speeds U10 compared to uncoupled simulations. This is in accord with other recent studies. However, the wave‐atmosphere coupling is effected through the friction velocity field u*, rather than through the wind field U10. Thus because the coupling gives enhanced resistive friction, U10 is weakened, whereas u* is enhanced. Wave heights, driven by u*, are also increased in our coupled model simulations compared to uncoupled model simulations. Coupled model outputs are shown to compare favorably with air‐sea observations collected during the recent Labrador Sea Deep Convection Experiment in 1997, both for synoptic storm timescales and for seasonal timescales.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.046
GPT teacher head0.318
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2001
Admission routes1
Has abstractyes

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