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Record W4283372765 · doi:10.5194/tc-16-2421-2022

Controls on Greenland moulin geometry and evolution from the Moulin Shape model

2022· article· en· W4283372765 on OpenAlexaff
Lauren C. Andrews, Kristin Poinar, Celia Trunz

Bibliographic record

Venue˜The œcryosphere · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversité de Sherbrooke
FundersUniversity at BuffaloGoddard Space Flight CenterNuclear Safety and Security CommissionNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsMeltwaterGeologyGlacierGeometryHydrology (agriculture)GeomorphologyMathematicsGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract. Nearly all meltwater from glaciers and ice sheets is routed englacially through moulins. Therefore, the geometry and evolution of moulins has the potential to influence subglacial water pressure variations, ice motion, and the runoff hydrograph delivered to the ocean. We develop the Moulin Shape (MouSh) model, a time-evolving model of moulin geometry. MouSh models ice deformation around a moulin using both viscous and elastic rheologies and melting within the moulin through heat dissipation from turbulent water flow, both above and below the water line. We force MouSh with idealized and realistic surface melt inputs. Our results show that, under realistic surface melt inputs, variations in surface melt change the geometry of a moulin by approximately 10 % daily and over 100 % seasonally. These size variations cause observable differences in moulin water storage capacity and moulin water levels compared to a static, cylindrical moulin. Our results suggest that moulins are important storage reservoirs for meltwater, with storage capacity and water levels varying over multiple timescales. Implementing realistic moulin geometry within subglacial hydrologic models may therefore improve the representation of subglacial pressures, especially over seasonal periods or in regions where overburden pressures are high.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient 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 score0.100
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.019
GPT teacher head0.203
Teacher spread0.185 · 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

Citations16
Published2022
Admission routes1
Has abstractyes

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