MétaCan
Menu
Back to cohort
Record W2024214284 · doi:10.1002/hyp.1194

Impact of an extreme melt event on the runoff and hydrology of a high Arctic glacier

2003· article· en· W2024214284 on OpenAlexafffund
Sarah Boon, Martin Sharp, Peter Nienow

Bibliographic record

VenueHydrological Processes · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaGeological Society of America
KeywordsGlacierGreenland ice sheetSnowArcticSurface runoffClimatologyWind speedGlacier mass balanceGeologyAtmospheric sciencesEnvironmental scienceHydrology (agriculture)OceanographyGeomorphology

Abstract

fetched live from OpenAlex

Abstract On 28–30 July 2000, an extreme melt event was observed at John Evans Glacier (JEG), Ellesmere Island (79° 40′N, 74° 00′W). Hourly melt rates during this event fell in the upper 4% of the distribution of melt rates observed at the site during the period 1996–2000. Synoptic conditions during the event resulted in strong east‐to‐west flow over the northern sector of the Greenland Ice Sheet, with descending flow on the northwest side reaching Ellesmere Island. On JEG, wind speeds during the event averaged 8·1 m s −1 at 1183 m a.s.l., with hourly mean wind speeds peaking at 11·6 m s −1 . Air temperatures reached 8°C, and rates of surface lowering measured by an ultrasonic depth gauge averaged 56 mm day −1 . Calculations with an energy balance model suggest that increased turbulent fluxes contributed to melt enhancement at all elevations on the glacier, while snow albedo feedback resulted in increased melting due to net radiation at higher elevations. The event was responsible for 30% of total summer melt at 1183 m a.s.l. and 15% at 850 m a.s.l. Conditions similar to those during the event occurred on only 0·1% of days in the period 1948–2000, but 61% of events occurred in the summer months and there was an apparent clustering of events in the 1950s and 1980s. Such events have the potential to impact significantly on runoff, mass balance and drainage system development at high Arctic glaciers, and changes in their incidence could play a role in determining how high Arctic glaciers respond to climate change and variability. Copyright © 2003 John Wiley & Sons, Ltd.

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 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 score0.014
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.041
GPT teacher head0.249
Teacher spread0.208 · 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

Citations28
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueHydrological ProcessesSame topicCryospheric studies and observationsFrench-language works237,207