Multi‐Century Impacts of Ice Sheet Retreat on Sea Level and Ocean Tides in Hudson Bay
Bibliographic record
Abstract
Abstract Past and modern large‐scale ice sheet loss results in geographically variable sea level changes. At present, in Hudson Bay, Canada, sea level is decreasing due to glacial isostatic adjustment, which represents a departure from the globally averaged sea level rise. However, there are large uncertainties in future sea level trends with further polar ice sheet retreat in the coming centuries. Sea level changes affect ocean tides considerably because tides are highly sensitive to changes in bathymetry. Here, we present multi‐century sea level projections associated with a suite of past and future ice loss scenarios and consider the impact of these changes on ocean tides using an established tidal model. Modern tides in Hudson Bay are poorly resolved due to large uncertainties in bathymetry. To establish an initial condition for our simulations, we constrain bathymetry in the bay using tide observations. Due to gravitational, Earth rotational and deformational effects, Greenland ice loss will produce a small sea level fall in the bay, while Antarctic ice loss will produce a larger than average sea level rise. Our results show that the response of the Antarctic ice sheet to climate change strongly impacts the magnitude and sign of future sea level and tidal amplitude changes in the region, with the largest changes predicted in Hudson Strait and Foxe Basin. We emphasize that further constraints on bathymetry and accurate projections of sea level and tides in Hudson Bay are imperative for assessing the associated impacts on coastal communities and ecosystems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".