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Record W2917910679 · doi:10.1175/jpo-d-18-0187.1

A Toy Model for the Response of the Residual Overturning Circulation to Surface Warming

2019· article· en· W2917910679 on OpenAlexaff
Malte F. Jansen, Louis-Philippe Nadeau

Bibliographic record

VenueJournal of Physical Oceanography · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsUniversité du Québec à Rimouski
FundersNational Science Foundation
KeywordsThermoclineBuoyancyClimatologyGeologyOcean currentShutdown of thermohaline circulationMixed layerThermohaline circulationResidualAdvectionEnvironmental scienceNorth Atlantic Deep WaterMechanics

Abstract

fetched live from OpenAlex

Abstract A simple model for the deep-ocean overturning circulation is presented and applied to study the ocean’s response to a sudden surface warming. The model combines one-dimensional predictive residual advection–diffusion equations for the buoyancy in the basin and Southern Ocean surface mixed layer with diagnostic relationships for the residual overturning circulation between these regions. Despite its simplicity, the model reproduces the results from idealized general circulation model simulations and provides theoretical insights into the mechanisms that govern the response of the overturning circulation to an abrupt surface warming. Specifically, the model reproduces a rapid shoaling and weakening of the Atlantic meridional overturning circulation (AMOC) in response to surface warming, followed by a partial recovery over the following decades to centuries, and a full recovery after multiple millennia. The rapid partial recovery is associated with adjustment of the lower thermocline, which itself is shown to be accelerated by the weakened AMOC. Full equilibration instead requires adjustment of the abyssal buoyancy, which is shown to be governed by diapycnal diffusion and surface fluxes around Antarctica.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.230

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.226
Teacher spread0.215 · 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 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

Citations20
Published2019
Admission routes1
Has abstractyes

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