Firn densification in the accumulation zone of Kaskawulsh Glacier, Yukon Territory, Canada
Bibliographic record
Abstract
As sources of fresh water and critical components of the global climate system, terrestrial glaciers are important features to monitor, particularly in light of anthropogenic climate change. Remote sensing techniques are being increasingly used to gather information on Earth’s shrinking complex glacial terrains. However, these methods possess critical challenges, including capturing firn dynamics and the presence of ice lenses. Meltwater percolation and retention, as well as thermodynamic effects on snow and firn density can complicate the relationship between surface height and mass balance changes; lowering of the glacier surface may masquerade as a mass change as detected by remote sensing technologies. The St. Elias Mountains, straddling the border between Yukon Territory, Canada and Alaska, USA, are home to extensive icefields. While numerous mass balance studies have been conducted in this region using remote sensing, there is a significant lack of in situ measurements of accumulation zone processes and firn properties. Our research examines refrozen ice layers and firn densification processes in the accumulation zone of Kaskawulsh Glacier in the St. Elias Mountains. In spring 2018, we extracted two firn cores (20 m and 35 m) from the study area and conducted a snow stratigraphy and ice lens survey on both core sections. After subsampling and melting the cores, we analyzed major ion and isotope chronology to identify extreme meltwater percolation and refreezing events, both of which critically affect firn density. The snow stratigraphy analysis from both of the cores showed numerous refrozen ice layers, indicating surface melt and refreezing processes in the accumulation zone. Preliminary results from isotope chronology analysis reveal a wash-out of the glaciochemical pattern in the 35 m and the 20 m ice core at 15 m depth, thus indicating severe surface warming events and subsequent changes in the density of the firn. This may indicate errors in the assumed density of the accumulation zone snow and firn when using remote sensing technologies to infer mass balance of Kaskawulsh Glacier.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".