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Record W3035898414 · doi:10.1029/2020gl087207

Rapid Cooling and Increased Storminess Triggered by Freshwater in the North Atlantic

2020· article· en· W3035898414 on OpenAlexaff
Marilena Oltmanns, Johannes Karstensen, G. W. K. Moore, Simon A. Josey

Bibliographic record

VenueGeophysical Research Letters · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Toronto
FundersSeventh Framework ProgrammeNational Centre for Earth ObservationNatural Environment Research CouncilSight Research UK
KeywordsAnomaly (physics)North Atlantic oscillationClimatologyStormWinter stormEnvironmental scienceOceanographyGeology

Abstract

fetched live from OpenAlex

Abstract Recent winters have been unique due to the rapid and extreme cooling of the subpolar North Atlantic. Here, we present a novel view on its causes and consequences. Combining in‐situ observations with remote sensing and atmospheric reanalysis data, we show that increased freshening of the subpolar region gives rise to a faster surface cooling in fall and winter. Large freshwater events, in particular, result in pronounced cold anomalies with sharp temperature gradients that promote an enhanced storminess. The storms reinforce the cooling by driving stronger heat losses and modulating the surface flow. Consistent with this mechanism, past freshwater events have been followed by cold anomalies in winter of approximately −2°C and increases in the North Atlantic Oscillation index of up to ∼0.6 within 3 years. We expect that future freshwater discharges into the North Atlantic will amplify the cold anomaly and trigger an enhanced wintertime storminess with far‐reaching climatic implications.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.045
GPT teacher head0.276
Teacher spread0.231 · 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

Citations39
Published2020
Admission routes1
Has abstractyes

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