Global Tidal Impacts of Large‐Scale Ice Sheet Collapses
Bibliographic record
Abstract
Abstract Recent studies show that the glaciers draining both the West Antarctic and the Greenland Ice Sheets are experiencing an accelerated ice loss, highlighting the possibility of large‐scale ice sheet retreat and sea level rise in the coming centuries and millennia. These sea level changes would vary spatially and could significantly alter global tides as the latter are highly dependent on bathymetry (or water column thickness under ice shelves) and basin shape. This paper investigates how the principal semidiurnal (M2) tidal amplitudes and energy dissipation respond to the nonuniform sea level changes induced by complete ice sheet collapses. The sea level changes are calculated using gravitationally self‐consistent sea level theory, and the tides are simulated using an established tidal model. Results from the simulations show global and spatially heterogeneous changes in tidal amplitudes. In addition, pronounced changes in tidal energy dissipation occur in both the open ocean and in shelf‐seas, also altering the location of tidal mixing fronts. These changes have the potential to impact ocean mixing, and hence large‐scale currents and climate patterns, and the contribution of shelf‐sea to the global carbon cycle. The new results highlight the importance of considering changes in the tides in predictions of future climate and reconstructions of past climate phases such as the Last Interglacial.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".