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Record W3193194209 · doi:10.1080/07055900.2021.1958741

Dynamic Characteristics of a Submesoscale Front and Associated Heat Fluxes Over the Northeastern South China Sea Shelf

2021· article· en· W3193194209 on OpenAlexvenueno aff
Jihai Dong

Bibliographic record

VenueATMOSPHERE-OCEAN · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
FundersChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsBaroclinityFront (military)Barotropic fluidStratification (seeds)GeologyContinental shelfHeat fluxOceanographyClimatologyThermalAtmospheric sciencesHeat transferMeteorologyMechanicsGeography

Abstract

fetched live from OpenAlex

Submesoscale fronts, which are ubiquitous phenomena in the ocean, contribute considerably to oceanic material transports and energy cascades because of their ageostrophy. The dynamic characteristics of a thermal front over the northeastern continental shelf of the South China Sea (SCS) in winter are investigated using a two-layer nested high-resolution regional ocean model system. Results show that a strong thermal front is generated over the slope of the SCS area in winter with a cross-front temperature difference of 5°C and a spatial scale of 6 km. The calculated Rossby number reaches O(1) at the front and is accompanied by strong secondary circulation; the vertical velocity can reach 40 m d−1. The calculated barotropic and baroclinic energy conversion reveals that background kinetic and potential energies provide the energy generation of a submesoscale front. Meanwhile, the submesoscale front induces strong horizontal and vertical heat fluxes of up to 8×105 and 1.7×103 W m−2, respectively. The heat flux promotes not only the cross-shelf exchange of heat in the horizontal direction but also the re-stratification of seawater in the vertical direction.

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 score0.025
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 communication0.0000.000
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 head0.004
GPT teacher head0.179
Teacher spread0.175 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueATMOSPHERE-OCEANSame topicOceanographic and Atmospheric ProcessesFrench-language works237,207