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Record W4210474775 · doi:10.1007/s00382-022-06156-w

AMOC modes linked with distinct North Atlantic deep water formation sites

2022· article· en· W4210474775 on OpenAlexaboutno aff
Mihai Dima, Gerrit Lohmann, Monica Ioniță, Gregor Knorr, Patrick Scholz

Bibliographic record

VenueClimate Dynamics · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersAlfred Wegener Institute Helmholtz Centre for Polar and Marine ResearchAlexander von Humboldt-Stiftung
KeywordsAtlantic multidecadal oscillationNorth Atlantic Deep WaterNorth Atlantic oscillationClimatologyShutdown of thermohaline circulationThermohaline circulationOceanographyAtlantic Equatorial modeGeologyDeep waterGulf StreamOcean currentCentennialGeography

Abstract

fetched live from OpenAlex

Abstract The Atlantic Meridional Overturning Circulation (AMOC) is a tipping component of the climate system, with a quasi-global impact. Several numerical and observational studies emphasized two modes of AMOC variability, characterized by two distinct Atlantic sea surface temperature patterns. One is associated with centennial changes, the Trend Mode, and the other with the Atlantic Multidecadal Oscillation (AMO). The origin of the different manifestations of these modes it is not fully understood. Using observational data and an ocean general circulation model we present evidence that, whereas the Trend Mode is mainly linked with deep water formation in the Nordic Seas and with a North Atlantic AMOC cell centered at 50° N, AMO is related with deep water formation in the Labrador and Irminger Seas and with an overturning cell centered at 20° N. In combination with previous studies, these results imply that a main route of increasing atmospheric CO 2 concentration influence on AMOC passes through deep water formation in the Nordic Seas and it is reflected in a subpolar North Atlantic meridional cell.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.011
GPT teacher head0.199
Teacher spread0.189 · 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.

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

Citations13
Published2022
Admission routes1
Has abstractyes

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