21st century estimates of mass loss rates from glaciers in the Gulf of Alaska and Canadian Archipelago using a GRACE constrained glacier model
Bibliographic record
Abstract
Abstract. Ice mass loss rates from glaciers in the Gulf of Alaska and the Canadian Archipelago are expected to increase through the end of century in response to increasing temperatures. Here, we develop a new glacier model constrained by GRACE gravimetry observations for the period between 2002 and 2017. The high temporal and regional spatial resolution of GRACE mass balance estimates allows us to estimate regional glacier sensitivities to atmospheric changes, and account for higher order of glacier dynamics. We use our regionally constrained models to extrapolate future mass loss under different climate emission scenarios. Generally our 21st century sea level estimates are at the high end compared to other studies. We find that the Gulf of Alaska exhibits the highest mass loss rates between −79 to −112 Gt yr−1 between 2006 and 2100 under different scenarios, and displays the highest sensitivity to the specific scenario (RCP 2.6/4.5/8.5). Our estimates for Baffin Island are significantly higher than prior work (−57 to −85 Gt yr−1) and are comparable to projected mass loss rates from the Ellesmere region (−63 to −101 Gt yr−1).
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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 | 0.000 | 0.001 |
| 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".