Decontaminating tide gauge records for the influence of glacial isostatic adjustment: The potential impact of 3‐D Earth structure
Bibliographic record
Abstract
We investigate the potential impact of lateral variations in mantle viscosity and lithospheric thickness on predictions of present‐day relative sea‐level change due to glacial isostatic adjustment (GIA). We consider three viscoelastic Earth models. The first is a 1‐D model with a lithospheric thickness of 120 km and upper and lower mantle viscosities of 5 × 1020 Pa s and 5 × 1021 Pa s, respectively. The second model includes global lithospheric thickness variations and lateral heterogeneities in upper mantle viscosity ranging over three orders of magnitude, while the third model includes lateral variations in lower mantle viscosity alone. We find that the impact of 3‐D structure is significant. Indeed, the difference between the 3‐D and 1‐D model predictions at ∼300 sites with tide gauge records longer than 40 years duration is greater than 0.2 mm/yr and 0.5 mm/yr for 50% and 25% of the sites, respectively. The maximum difference exceeds several mm/yr. We conclude that efforts to decontaminate tide gauge records for ongoing GIA, to determine the rate and origin of global sea‐level rise, should incorporate 3‐D mantle structure into the GIA modelling.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".