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Record W4386617443 · doi:10.1080/07055900.2023.2251426

High-Resolution Lead–Lag Relations Between Barents Sea Temperatures, the AMOC and the AMO During 1971–2018

2023· article· en· W4386617443 on OpenAlexvenueno aff
Knut Lehre Seip, Hui Wang

Bibliographic record

VenueATMOSPHERE-OCEAN · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
Fundersstorbyuniversitetet
KeywordsLagLead (geology)Environmental scienceOceanographyClimatologyGeologyComputer sciencePaleontology

Abstract

fetched live from OpenAlex

The direction of heat transport from the atmosphere to the Barents Sea, and between the Barents Sea and the North Atlantic is important for understanding the interplay between Greenland ice melting and anthropogenic forcing.Here, we show how heat has been transported between water bodies by using a high-resolution lead-lag technique that identifies leading relations between cyclic temperature series.The results demonstrate that near-surface ocean temperature (0-30 m) in the Barents Sea led the temperature changes in its intermediate waters (100-200 m) during the period 1971 to 2018 inferring that heat transport is from the atmosphere to the intermediate waters.The Barents Sea's temperatures lagged the Atlantic meridional overturning circulation (AMOC) and the Atlantic multidecadal oscillation (AMO) from 1971 to 2000.The AMOC was leading the Barents Sea near-bottom temperatures in the West (the Bear Island Through) during 1980-2018 but was both leading and lagging in the Barents Sea Northeast.RSUM [Traduit par la rdaction] La direction du transport de chaleur de l'atmosphre vers la mer de Barents, et entre la mer de Barents et l'Atlantique Nord, est importante pour comprendre l'interaction entre la fonte des glaces du Groenland et le forage anthropique.Nous montrons ici comment la chaleur a t transporte entre les masses d'eau en utilisant une technique de trane haute rsolution qui dtermine les relations principales entre les sries de tempratures cycliques.Les rsultats montrent que la temprature de l'ocan proche de la surface (0-30 m) dans la mer de Barents prcde les changements de temprature dans ses eaux intermdiaires (100-200 m) au cours de la priode 1971-2018, ce qui permet de dduire que le transport de chaleur s'effectue de l'atmosphre vers les eaux intermdiaires.Les tempratures de la mer de Barents sont en retard par rapport la circulation mridienne de retournement de l'Atlantique (AMOC) et l'oscillation multidcennale de l'Atlantique (AMO) de 1971 2000.L'AMOC tait en avance sur les tempratures prs du fond de la mer de Barents l'ouest (le Bear) pendant la priode 1980-2018, mais tait la fois en avance et en retard dans le nord-est de la mer de Barents.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
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 head0.011
GPT teacher head0.202
Teacher spread0.191 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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