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Record W2998858885 · doi:10.1029/2019gl085455

Long‐Term SST Variability on the Northwest Atlantic Continental Shelf and Slope

2020· article· en· W2998858885 on OpenAlexaboutno aff
Zhuomin Chen, Young‐Oh Kwon, Ke Chen, Paula Fratantoni, Glen Gawarkiewicz, Terrence M. Joyce

Bibliographic record

VenueGeophysical Research Letters · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric Administration
KeywordsContinental shelfClimatologyGeologyCapeSea surface temperatureOceanographyStructural basinZonal and meridionalGeographyGeomorphology

Abstract

fetched live from OpenAlex

Abstract The meridional coherence, connectivity, and regional inhomogeneity in long‐term sea surface temperature (SST) variability over the Northwest Atlantic continental shelf and slope from 1982–2018 are investigated using observational data sets. A meridionally concurrent large SST warming trend is identified as the dominant signal over the length of the continental shelf and slope between Cape Hatteras in North Carolina and Cape Chidley, Newfoundland and Labrador, Canada. The linear trends are 0.37 ± 0.06 and 0.39 ± 0.06 °C/decade for the shelf and slope regions, respectively. These meridionally averaged SST time series over the shelf and slope are consistent with each other and across multiple longer observational data sets with records dating back to 1900. The coherence between the long‐term meridionally averaged time series over the shelf and slope and basin‐wide averaged SST in the North Atlantic implies approximately two thirds of the warming trend during 1982–2018 may be attributed to natural climate variability and the rest to externally forced change including anthropogenic warming.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.042
GPT teacher head0.285
Teacher spread0.243 · 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; both teacher heads agree on what is shown here.

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

Citations87
Published2020
Admission routes1
Has abstractyes

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