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Record W2141533372 · doi:10.1029/2006jc003976

The path‐density distribution of oceanic surface‐to‐surface transport

2008· article· en· W2141533372 on OpenAlexaff
Mark Holzer, François Primeau

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsLangara CollegeUniversity of British Columbia
Fundersnot available
KeywordsResidence time (fluid dynamics)AdvectionSink (geography)Flux (metallurgy)GeologyLatitudeTRACERDiffusionEnvironmental scienceMeteorologyAtmospheric sciencesPhysicsGeodesyGeographyMaterials scienceCartography

Abstract

fetched live from OpenAlex

A novel diagnostic for advective‐diffusive surface‐to‐surface paths is developed and applied to a global ocean model. The diagnostic provides, for the first time, a rigorous quantitative assessment of the great ocean conveyor's deep branch. A new picture emerges of a diffusive conveyor in which the deep North Pacific is a holding pen of long‐residence‐time water. Our diagnostic is the joint density, η , per unit volume and interior residence time, τ , of paths connecting two specified surface patches. The spatially integrated η determines the residence‐time partitioned flux and volume of water in transit from entry to exit patch. We focus on interbasin paths from high‐latitude water mass formation regions to key regions of re‐exposure to the atmosphere. For non‐overlapping patches, a characteristic timescale is provided by the residence time, τ ϕ , for which the associated flux distribution, ϕ, has its maximum. Paths that are fast compared to τ ϕ are organized by the major current systems, while paths that are slow compared to τ ϕ are dominated by eddy diffusion. Because ϕ has substantial weight in its tail for τ > τ ϕ , the fast paths account for only a minority of the formation‐to‐re‐exposure flux. This conclusion is expected to apply to the real ocean based on recent tracer data analyses, which point to long eddy‐diffusive tails in the ocean's transit‐time distributions. The long‐ τ asymptotic path density is governed by two time‐invariant patterns. One pattern, which we call the Deep North Pacific pattern, ultimately dominates a secondary redistribution pattern.

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)0.001
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 score0.021
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.024
GPT teacher head0.267
Teacher spread0.242 · 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

Citations43
Published2008
Admission routes1
Has abstractyes

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