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Record W2079240338 · doi:10.1029/2003jf000112

Hydrological controls on diurnal ice flow variability in valley glaciers

2005· article· en· W2079240338 on OpenAlexaff
P. W. Nienow, Alun Hubbard, Bryn Hubbard, David Chandler, Douglas Mair, Martin Sharp, Ian Willis

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMeltwaterGlacierGeologyIce streamGeomorphologySnowDiurnal cycleClimatologyAtmospheric sciencesCryosphereSea ice

Abstract

fetched live from OpenAlex

This paper uses a combination of field data and three‐dimensional modeling to investigate the spatial variability in basal conditions required to induce observed fluctuations in diurnal ice velocity at Haut Glacier d'Arolla, Switzerland. A network of surface velocity markers was observed at intervals of as little as four hours over diurnal cycles in both winter and late summer. Winter motion showed limited diurnal variability, presumably due to the absence of supraglacial meltwater inputs. By contrast, diurnal fluctuations in ice motion were recorded in summer across the lower and upper glacier. In the lower glacier, surface velocities were intimately linked to hydrological forcing in the vicinity of a subglacial channel. Previously observed diurnal excursions of meltwater away from the channel should reduce areas of basal drag adjacent to the channel thereby impacting on ice dynamics. Using a first‐order ice flow approximation, we investigated the distribution of basal shear traction adjacent to the channel necessary to replicate the observed surface velocity field during periods of rapid ice motion. The modeling suggests that the observed variations in diurnal velocity will only occur with extensive reductions in basal drag across a transverse zone of up to 560 m across, well beyond the immediate vicinity and previously observed extent of diurnal excursions of meltwater away from the subglacial channel.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.305
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.304
Teacher spread0.262 · 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

Citations77
Published2005
Admission routes1
Has abstractyes

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