MétaCan
Menu
Back to cohort
Record W1915947104 · doi:10.5194/cp-12-543-2016

The effect of low ancient greenhouse climate temperature gradients on the ocean's overturning circulation

2016· article· en· W1915947104 on OpenAlexfundno aff
Willem P. Sijp, Matthew H. England

Bibliographic record

VenueClimate of the past · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersAustralian Research CouncilUniversity of New South WalesUniversity of Victoria
KeywordsClimatologyThermohaline circulationOcean currentEnvironmental scienceNorthern HemisphereAtmospheric sciencesOcean heat contentClimate changeShutdown of thermohaline circulationEquatorGeologyOceanographyNorth Atlantic Deep WaterLatitude

Abstract

fetched live from OpenAlex

Abstract. We examine whether the reduced meridional temperature gradients of past greenhouse climates might have reduced oceanic overturning, leading to a more quiescent subsurface ocean. A substantial reduction of the pole-to-Equator temperature difference is achieved in a coupled climate model via an altered radiative balance in the atmosphere. Contrary to expectations, we find that the meridional overturning circulation and deep ocean kinetic energy remain relatively unaffected. Reducing the wind strength also has remarkably little effect on the overturning. Instead, overturning strength depends on deep ocean density gradients, which remain relatively unaffected by the surface changes, despite an overall decrease in ocean density. Ocean poleward heat transport is significantly reduced only in the Northern Hemisphere, as now the circulation operates across a reduced temperature gradient, suggesting a sensitivity of Northern Hemisphere heat transport in greenhouse climates to the overturning circulation. These results indicate that climate models of the greenhouse climate during the Cretaceous and early Paleogene may yield a reasonable overturning circulation, despite failing to fully reproduce the extremely reduced temperature gradients of those time periods.

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)0.000
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 score0.004
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueClimate of the pastSame topicGeology and Paleoclimatology ResearchFrench-language works237,207