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Record W4321481906 · doi:10.5194/egusphere-egu23-6249

Bipolar deep-water formation during the climatic warmth of the early-middle Eocene

2023· preprint· en· W4321481906 on OpenAlexaboutno aff
Andrew McIntyre, Philip F. Sexton, Pallavi Anand

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersNatural Environment Research CouncilSight Research UK
KeywordsWater massGeologyClimatologyOcean currentTransectOceanographyδ18ONorth Atlantic Deep WaterHolocene climatic optimumDeep ocean waterDeep seaStable isotope ratioClimate changePaleontologyThermohaline circulation

Abstract

fetched live from OpenAlex

The Atlantic meridional overturning circulation (AMOC) is a major component of global ocean circulation and through the distribution of heat, salt, and nutrients exerts a fundamental influence on global and regional climates. However, there is limited understanding of AMOC stability or its sensitivity, under acute climatic warmth that is marked for Earth’s future. To tackle this important gap in our understanding, the climatic warmth of the Eocene (~34-56 Ma) offers a unique opportunity and setting to investigate existence, structure, stability, and operation of AMOC. These fundamental gaps in our knowledge and understanding limit the ability to ground-truth ocean model simulations of past warm climates, and thus also diminish our confidence in the capabilities of these models to predict ongoing changes to our oceans.Here, we present the first reconstruction of the early-middle Eocene AMOC using a meridional transect of Atlantic and Southern Ocean drill sites. Across sites, detailed chemostratigraphic correlations provide a common, high resolution age model spanning a 500 kyr interval (46.7-47.2 Ma). During this interval, high-resolution (~10 ka) carbon (δ13C), oxygen (δ18O), and neodymium (εNd) proxies were used to determine ocean ventilation state, temperature and salinity, and deep-water mass flow pathways. We find an early-middle Eocene AMOC, which consisted of bipolar deep-water formation forming two major cells, a southern and a northern cell. We will discuss characteristics of these water mass cells and their origin and operation using δ13C, δ18O, and εNd isotopic signatures. Evidence of deep-water mass formation in the North Atlantic is supported by sedimentological evidence from Hohbein et al. (2012) and Boyle et al., (2017), suggesting deep Nordic seas overflows at ~49 Ma and deep-water current flow forming contourite drifts on the Newfoundland Ridges at 47.8 Ma respectively.Ocean circulation modelling of intervals of past extreme warmth, such as DeepMIP, provide understanding into potential ocean structures that could have existed during the early-middle Eocene. The most common feature of model predictions is a global meridional overturning circulation with strong deep convection in the Southern Ocean and no deep convection in the North Atlantic (Zhang et al., 2022). This study provides compelling evidence to bolster the Southern Ocean findings, yet a major data-modelling discrepancy exists within the North Atlantic, where most current model simulations don’t reproduce the proxy derived deep northern cell. This could point to non-CO2 boundary conditions, such as North Atlantic bathymetry and gateways, as a cause of this discrepancy. Further proxy and modelling work is warranted to resolve the temporal extent of deep-water convection in the North Atlantic during the Eocene.ReferencesBoyle et al., 2017. Marine Geology, 385, 185–203.Hohbein et al., 2012, Geology, 40, 3, 255–258.Zhang et al., 2022, Paleoceanography and Paleoclimatology, 37, 3, 1–22.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.042
GPT teacher head0.236
Teacher spread0.194 · 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 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

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