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Record W2044150370 · doi:10.1029/2011jc007730

Continental constriction and oceanic ice‐cover thickness in a Snowball‐Earth scenario

2012· article· en· W2044150370 on OpenAlexaff
Eli Tziperman, Dorian S. Abbot, Yosef Ashkenazy, Hezi Gildor, David Pollard, Christian Schoof, Daniel P. Schrag

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSnowball EarthGeologyFlow (mathematics)Sea ice growth processesLead (geology)GeophysicsScalingClimatologyLatitudeSea iceMechanicsGeometryGeomorphologyDrift iceCryosphereGeodesyPhysicsGlacial periodMathematics

Abstract

fetched live from OpenAlex

Ice flow over a Snowball ocean was shown in recent years to be capable of very effectively homogenizing ice thickness globally. Previous studies all used local or one‐dimensional global (latitude‐only) models, formulated in a way that is difficult to extend to two‐dimensional global configuration. This paper uses a two‐dimensional global ice flow model to study the effects of continental constriction on ice flow and ice thickness in a Snowball‐Earth scenario using reconstructed Neoproterozoic landmass configuration. Numerical simulations and scaling arguments are used to show that various configurations of continents and marginal seas which are not represented by one dimensional models lead to large ice thickness variations, including narrow areas between sub‐continents and marginal seas whose entrance is constricted. This study ignores many known important factors such as thermodynamic, optical effects, dust and dust transport, and is therefore meant as a process study focusing on one specific effect, rather than a realistic simulation of Neoproterozoic ice thickness. The model formulation developed here generalizes and extends previous results in several ways, including the introduction of corrections due to spherical coordinates and lateral geometry. This study is therefore a step toward coupling Snowball ice flow models to general circulation ocean and atmospheric models and allowing a more quantitative simulation of Neoproterozoic Snowball ice thickness.

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 score0.020
Threshold uncertainty score0.988

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.038
GPT teacher head0.291
Teacher spread0.254 · 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

Citations53
Published2012
Admission routes1
Has abstractyes

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