MétaCan
Menu
Back to cohort
Record W1985888576 · doi:10.1029/2008jc005030

Impact of latitudinal variations in vertical diffusivity on climate simulations

2009· article· en· W1985888576 on OpenAlexaboutno aff
Markus Jochum

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
Fundersnot available
KeywordsThermoclineTeleconnectionThermal diffusivityClimatologyGeologyZonal and meridionalThermohaline circulationPrecipitationLead (geology)Sea surface temperatureAtmospheric sciencesOceanographyEnvironmental scienceMeteorologyEl Niño Southern OscillationGeographyGeomorphologyPhysics

Abstract

fetched live from OpenAlex

The currently available theoretical and observational evidence for a latitudinal structure of thermocline vertical diffusivity is synthesized and included in a state of the art coupled climate model. Compared to the standard background value of 0.1 cm2 s−1, the simulations with the latitudinal structure show only little change in the meridional overturning circulation or northward heat transport. However, two regions are identified which are sensitive to the value of vertical diffusivity: the equatorial band, where only small changes in sea surface temperature lead to precipitation responses with basin‐wide teleconnections, and the North Atlantic, where diffusivity affects the spiciness of Labrador Sea water and subsequently the Gulf Stream path.

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)0.007
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 score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.050
GPT teacher head0.383
Teacher spread0.333 · 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

Citations120
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Geophysical Research AtmospheresSame topicClimate variability and modelsFrench-language works237,207