Quantifying the Sensitivity of Sea Level Change in Coastal Localities to the Geometry of Polar Ice Mass Flux
Bibliographic record
Abstract
Abstract It has been known for over a century that the melting of individual ice sheets and glaciers drives distinct geographic patterns, or fingerprints, of sea level change, and recent studies have highlighted the implications of this variability for hazard assessment and inferences of meltwater sources. These studies have computed fingerprints using simplified melt geometries; however, a more generalized treatment would be advantageous when assessing or projecting sea level hazards in the face of quickly evolving patterns of ice mass flux. In this paper the usual fingerprint approach is inverted to compute site-specific sensitivity kernels for a global database of coastal localities. These kernels provide a mapping between geographically variable mass flux across each ice sheet and glacier and the associated static sea level change at a given site. Kernels are highlighted for a subset of sites associated with melting from Greenland, Antarctica, and the Alaska–Yukon–British Columbia glacier system. The latter, for example, reveals an underappreciated sensitivity of ongoing and future sea level change along the U.S. West Coast to the geometry of ice mass flux in the region. Finally, the practical utility of these kernels is illustrated by computing sea level predictions at a suite of sites associated with annual variability in Greenland ice mass since 2003 constrained by satellite gravity measurements.
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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 | 0.003 | 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 | 0.000 | 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) | 0.000 | 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".