Accumulation at the equilibrium-line altitude of glaciers inferred from a degree-day model and tested against field observations
Bibliographic record
Abstract
Abstract We extrapolate temperature data from a gridded climatology to the equilibrium-line altitude (ELA) of a glacier and tune a degree-day model by adjusting precipitation to give zero mass balance at the ELA. We verify the tuned model by comparing modelled accumulation with winter balance where this has been measured (presently for 180 glaciers). The modelled accumulation naturally depends upon the vertical lapse rate (VLR) for temperature and the degree-day factor (DDF) for snowmelt. Both are somewhat uncertain in high-mountain areas, but modelled accumulation and measured winter balance are in reasonable agreement for most glaciers. The degree-day model predicts a non-linear relation between accumulation and summer temperature at the ELA as assumed by many workers, but we find a family of curves rather than a single universal curve. Maritime glaciers with low annual temperature range have proportionally more accumulation than continental glaciers with high annual temperature range for a similar summer mean temperature. Averages of winter balance for the five main geographical regions where mass-balance data are available agree well with annual accumulation from the degree-day model.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".