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Record W3161850908 · doi:10.1029/2020pa004095

Tracking Southern Ocean Sea Ice Extent With Winter Water: A New Method Based on the Oxygen Isotopic Signature of Foraminifera

2021· article· en· W3161850908 on OpenAlexaff
David C Lund, Zanna Chase, Karen E. Kohfeld, Earle Wilson

Bibliographic record

VenuePaleoceanography and Paleoclimatology · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsSimon Fraser University
FundersNational Science Foundation
KeywordsGeologyOceanographySea iceForaminiferaNorth Atlantic Deep WaterAntarctic sea iceArctic ice packBenthic zoneSea surface temperatureClimatologyThermohaline circulation

Abstract

fetched live from OpenAlex

Abstract Southern Ocean sea ice plays a central role in the oceanic meridional overturning circulation, transforming globally prevalent watermasses through surface buoyancy loss and gain. Buoyancy loss due to surface cooling and sea ice growth promotes the formation of bottom water that flows into the Atlantic, Indian, and Pacific basins, while buoyancy gain due to sea ice melt helps transform the returning deep flow into intermediate and mode waters. Because northward expansion of Southern Ocean sea ice during the Last Glacial Maximum (LGM; 19–23 kyr BP) may have enhanced deep ocean stratification and contributed to lower atmospheric CO 2 levels, reconstructions of sea ice extent are critical to understanding the LGM climate state. Here, we present a new sea ice proxy based on the 18 O/ 16 O ratio of foraminifera (δ 18 O c ). In the seasonal sea ice zone, sea ice formation during austral winter creates a cold surface mixed layer that persists in the sub‐surface during spring and summer. The cold sub‐surface layer, known as winter water, sits above relatively warm deep water, creating an inverted temperature profile. The unique surface‐to‐deep temperature contrast is reflected in estimates of equilibrium δ 18 O c , implying that paired analysis of planktonic and benthic foraminifera can be used to infer sea ice extent. To demonstrate the feasibility of the δ 18 O c method, we present a compilation of N. pachyderma and Cibicidoides spp. results from the Atlantic sector that yields an estimate of winter sea ice extent consistent with modern observations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.240
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.

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

Citations8
Published2021
Admission routes1
Has abstractyes

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