Common Era sea-level budgets of North America
Bibliographic record
Abstract
A sea-level budget improves understanding of driving processes and their relative contributions. However, most sea-level budget assessments are limited to the 20th and 21st centuries and are global in scale. Here, we estimate the sea-level budget on centennial to millennial timescales of the Common Era (last 2000 years). We expand upon previous analysis of sites along the U.S. mid-Atlantic coast (Walker et al., 2021) and produce site-specific sea-level budgets for all of the eastern and western North American coastlines and Gulf coast. This broader scope further improves understanding of the temporal evolution and variability of driving processes of sea-level changes in the past and present, and which will shape such changes in the future. To produce the sea-level budgets, we use an updated global database of instrumental and proxy sea-level records coupled with a spatiotemporal model. Using the unique spatial scales of driving processes, we separate relative sea-level records into global, regional, and local-scale components. Preliminary results along the eastern North American coastline reveal that each budget is dominated by regional-scale, temporally-linear processes driven by glacial isostatic adjustment until at least the mid-19th century. This signal exhibits a spatial gradient, ranging from 1.0 ± 0.02 mm/yr (1σ) in Newfoundland to a maximum of 1.6 ± 0.02 mm/yr in southern New Jersey to 0.5 ± 0.02 mm/yr in Florida. Non-linear regional and local-scale processes, such as ocean/atmosphere dynamics and groundwater withdrawal, are smaller in magnitude and vary temporally and spatially. The most significant change to the budgets is the increasing influence of the global signal due to ice melt and thermal expansion since ~1800 CE, which reaches a 20th century rate of 1.3 ± 0.1 mm/yr, accounting for 43-65% of each budget.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".