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Record W2888543415 · doi:10.1029/2018jc014037

Partitioning of Kinetic Energy in the Arctic Ocean's Beaufort Gyre

2018· article· en· W2888543415 on OpenAlexfundno aff
Mengnan Zhao, Mary‐Louise Timmermans, Richard Krishfield, Georgy E. Manucharyan

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersDivision of Polar ProgramsDivision of Ocean SciencesOffice of Polar ProgramsFisheries and Oceans CanadaWoods Hole Oceanographic InstitutionNational Science Foundation
KeywordsOcean gyreBarotropic fluidBaroclinityGeologyOceanographyClimatologyEddyOcean currentArcticSea iceMesoscale meteorologyAtmospheric sciencesEnvironmental scienceMeteorologyPhysics

Abstract

fetched live from OpenAlex

Abstract Kinetic energy (KE) in the Arctic Ocean's Beaufort Gyre is dominated by the mesoscale eddy field that plays a central role in the transport of freshwater, heat, and biogeochemical tracers. Understanding Beaufort Gyre KE variability sheds light on how this freshwater reservoir responds to wind forcing and sea ice and ocean changes. The evolution and fate of mesoscale eddies relate to energy pathways in the ocean (e.g., the exchange of energy between barotropic and baroclinic modes). Mooring measurements of horizontal velocities in the Beaufort Gyre are analyzed to partition KE into barotropic and baroclinic modes and explore their evolution. We find that a significant fraction of water column KE is in the barotropic and the first two baroclinic modes. We explain this energy partitioning by quantifying the energy transfer coefficients between the vertical modes using the quasi‐geostrophic potential vorticity conservation equations with a specific background stratification observed in the Beaufort Gyre. We find that the quasi‐geostrophic vertical mode interactions uphold the persistence of KE in the first two baroclinic modes, consistent with observations. Our results explain the specific role of halocline structure on KE evolution in the gyre and suggest depressed transfer to the barotropic mode. This limits the capacity for frictional dissipation at the sea floor and suggests that energy dissipation via sea ice‐ocean drag may be prominent.

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)0.001
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 score0.050
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.028
GPT teacher head0.292
Teacher spread0.264 · 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

Citations42
Published2018
Admission routes1
Has abstractyes

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