Accelerated contributions of Canada's Baffin and Bylot Island glaciers to sea level rise over the past half century
Bibliographic record
Abstract
Abstract. Canadian Arctic glaciers have recently contributed large volumes of meltwater to the world's oceans. To place recently observed glacier wastage into a historical perspective and to determine the region's longer-term (~50 years) contribution to sea level, we estimate mass and volume changes for the glaciers of Baffin and Bylot Islands using digital elevation models generated from airborne and satellite stereoscopic imagery and elevation postings from repeat airborne and satellite laser altimetry. In addition, we update existing glacier mass change records from GRACE satellite gravimetry to cover the period from 2003 to 2011. Using this integrated approach, we find that the rate of mass loss from the region's glaciers increased from 11.1 ± 3.4 Gt a−1 (271 ± 84 kg m−2 a−1) for the period 1963–2006 to 23.8 ± 6.1 Gt a−1 (581 ± 149 kg m−2 a−1) for the period 2003–2011. The doubling of the rate of mass loss is attributed to higher temperatures in summer with little change in annual precipitation. Through both direct and indirect effects, changes in summer temperatures accounted for 70–98% of the variance in the rate of mass loss, to which the Barnes Ice Cap was found to be 1.7 times more sensitive than either the Penny Ice Cap or the region's glaciers as a whole. This heightened sensitivity is the result of a glacier hypsometry that is skewed to lower elevations, which are shown to have a higher mass change sensitive to temperature compared to glacier surfaces at higher elevations. Between 2003 and 2011 the glaciers of Baffin and Bylot Islands contributed 0.07 ± 0.02 mm a−1 to sea level rise accounting for 16% of the total contribution from glaciers outside of Greenland and Antarctica, a rate much higher than the longer-term average of 0.03 ± 0.01 mm a−1 (1963 to 2006).
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".