Intra-annual and Long-term Dynamic Behaviour of Hubbard and Valerie Glaciers, Alaska
Bibliographic record
Abstract
Western North American mountain regions are warming at a faster rate than the global average, which is influencing the retreat and melting of glaciers, with a 75% disappearance of glacier volume in Western North America possible by 2100. The impacts of this are wide reaching, including increasing contributions to sea level rise, decreased freshwater availability, loss of stability of mountain slopes and changing aquatic ecosystems. Hubbard and Valerie glaciers are in the St. Elias Mountains of Alaska/Yukon, which is an important area of study as Alaskan glaciers are likely to respond to climate change differently than glaciers in other regions of the world. The studies on seasonal velocity flow of both glaciers have been limited, with few recent reports of dynamics and mass balance. The goals of this study were to 1) determine the seasonality of Hubbard and Valerie glaciers by creating the densest record of flow to date from July 2013-April 2022; 2) analyze the long-term velocity trend from 1985-2022 to confirm if both glaciers are decelerating; and 3) use surface elevation change and temperature data to analyze potential drivers of the determined velocity patterns. The velocity record of Hubbard and Valerie glaciers was created using ITS_LIVE, RADARSAT-2, RADARSAT Constellation Mission, and TerraSAR-X/TanDEM-X derived measurements. Valerie glacier had an expected seasonal pattern of peak velocities in May and minimum velocities between August-November. Hubbard Glacier had a seasonal pattern that had never been identified in previous studies, with peak velocities between December-February, velocities dropping slightly between January-April, a second velocity peak in May, and minimum velocities in August/September. The May peak and late summer minimum of both glaciers was determined to be from surface melt reaching the bed, increasing flow speeds with an inefficient drainage system before changing to a channelized subglacial hydrological system that causes a velocity drop. It is likely Hubbard Glacier’s winter velocity peak and slowdown before its May peak is internally driven, however the exact driver was not identified. The long-term velocity trend revealed Hubbard Glacier is decelerating, with a minimal deceleration near its terminus that was similar to the minimal deceleration on Valerie Glacier, while there was increased deceleration further up-glacier. For both glaciers, the deceleration did not match the expected patterns of thinning/thickening. Previous instances of pulsing were not resolved in this data. Overall, this study helps improve the knowledge of tidewater glacier dynamics through the identification of a unique intra-annual velocity pattern and can assist in improving sea level rise, ice dynamics, and mass loss models.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".