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Record W2802204971 · doi:10.1175/jcli-d-17-0629.1

The Effect of Arctic Freshwater Pathways on North Atlantic Convection and the Atlantic Meridional Overturning Circulation

2018· article· en· W2802204971 on OpenAlexaboutno aff
He Wang, Sonya Legg, Robert Hallberg

Bibliographic record

VenueJournal of Climate · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric Administration
KeywordsShutdown of thermohaline circulationNorth Atlantic Deep WaterOceanographyThermohaline circulationClimatologyGeologyArcticAtlantic multidecadal oscillationClimate modelDeep convectionGulf StreamOcean currentConvectionNorth Atlantic oscillationClimate changeGeographyMeteorology

Abstract

fetched live from OpenAlex

This study examines the relative roles of the Arctic freshwater exported via different pathways on deep convection in the North Atlantic and the Atlantic meridional overturning circulation (AMOC). Deep water feeding the lower branch of the AMOC is formed in several North Atlantic marginal seas, including the Labrador Sea, Irminger Sea, and the Nordic seas, where deep convection can potentially be inhibited by surface freshwater exported from the Arctic. The sensitivity of the AMOC and North Atlantic to two major freshwater pathways on either side of Greenland is studied using numerical experiments. Freshwater export is rerouted in global coupled climate models by blocking and expanding the channels along the two routes. The sensitivity experiments are performed in two sets of models (CM2G and CM2M) with different control simulation climatology for comparison. Freshwater via the route east of Greenland is found to have a larger direct impact on Labrador Sea convection. In response to the changes of freshwater route, North Atlantic convection outside of the Labrador Sea changes in the opposite sense to the Labrador Sea. The response of the AMOC is found to be sensitive to both the model formulation and mean-state climate.

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 score0.049
Threshold uncertainty score0.296

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.199
Teacher spread0.192 · 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

Citations34
Published2018
Admission routes1
Has abstractyes

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