Temperature mediated albedo decline portends acceleration of North American glacier mass loss
Bibliographic record
Abstract
Abstract North American glaciers experienced accelerated mass loss over the last decade, yet the degree to which albedo decline drove this mass loss remains uncertain. We use daily summer glacier surface albedo averaged by decade (2000 − 2009 and 2010 − 2019) derived from Moderate Resolution Imaging Spectroradiometer to investigate how snow and ice darkening influenced glacier mass loss for 25 of the largest and most heavily glaciated regions in North America. Here we show that glacier albedo respectively decreased by 0.019 ± 0.019 and 0.018 ± 0.009 in western North America and in the Canadian Arctic. This decrease in albedo coincides with increased geodetically derived glacier mass loss within these regions (R 2 = 0.76, R 2 = 0.63; p < 0.01). Modelled surface energy balance and melt rates, forced by European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation Land reanalysis and regional decadal averages of albedo, indicate that 31% of increased melt rate in Western North America and 41% of increased melt rate in the Canadian Arctic can be attributed to albedo decline. Projected increases in air temperature this century will further reduce glacier albedo, and the resulting positive feedback will further accelerate glacier mass loss.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".