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Record W2094893282 · doi:10.1175/jcli4022.1

Steric Sea Level Change in the Northern Seas

2007· article· en· W2094893282 on OpenAlexaboutno aff
Michael Steele, Wendy Ermold

Bibliographic record

VenueJournal of Climate · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsOceanographyArcticThermohaline circulationClimatologyArctic dipole anomalyGeologySalinityTemperature salinity diagramsArctic sea ice declineOcean currentOcean heat contentEnvironmental scienceArctic ice packAntarctic sea ice

Abstract

fetched live from OpenAlex

Abstract Ocean temperature and salinity data over the period 1950–2000 in the Northern Seas, defined here as the North Atlantic Ocean (north of 50°N), North Pacific Ocean (north of 40°N), and Arctic Oceans, are combined to diagnose the steric (i.e., density) contribution to sea level variation. The individual contributions to steric height from temperature (thermosteric height) and salinity (halosteric height) are also analyzed. It is found that during 1950–2000, steric height rose over the study’s domain, mostly as a result of halosteric increases (i.e., freshening). Over a shorter time period (late 1960s to early 1990s) during which climate indices changed dramatically, steric height gradients near the Nordic Seas minimum were reduced by 18%–32%. It is speculated that this may be associated with a local slowing of both the Meridional Overturning Circulation and the southward flow through Fram Strait. However, steric height increases in the North Pacific Ocean during this time imply a possible acceleration of flow through the poorly measured Canadian Arctic. Evidence that the Great Salinity Anomaly of the late 1960s and 1970s had two distinct Arctic Ocean sources is also found: a late 1960s export of sea ice, and a delayed but more sustained 1970s export of liquid (ocean) freshwater. A simple calculation indicates that these Arctic Ocean freshwater sources were not sufficient to create the 1970s freshening observed in the North Atlantic Ocean.

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 score0.078
Threshold uncertainty score0.461

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 head0.043
GPT teacher head0.267
Teacher spread0.224 · 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

Citations54
Published2007
Admission routes1
Has abstractyes

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