Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/hyp.1194 Impact of an extreme melt event on the runoff and hydrology of a high Arctic glacier
Bibliographic record
Abstract
74°000W). 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 8Ð1 m s1 at 1183 m a.s.l., with hourly mean wind speeds peaking at 11Ð6 m s1. Air temperatures reached 8 °C, and rates of surface lowering measured by an ultrasonic depth gauge averaged 56 mm day1. 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 0Ð1 % 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. KEY WORDS synoptic climatology; hydrometeorology; Canadian Arctic; extreme melt events; energy balance; ablation
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.750 | 0.744 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".