Historical sea-level changes in Australia: Testing the Arctic ice melt hypothesis
Bibliographic record
Abstract
Rates of regional and global sea-level rise during the 20th century were faster than in any \ncentury over the last 3000 years. Sea-level rise accelerated between ~1850 and ~1950, before \ngreenhouse gases became the dominant forcing agent, which suggests, in part, a natural \norigin. The acceleration appears to have been more rapid in the Southern Hemisphere, which, \naccording to geophysical theory, could point at a contribution from Northern Hemisphere \nland-based ice melt. More high-resolution relative sea level (RSL) reconstructions from the \nSouthern Hemisphere are needed to test this hypothesis, and to complement a limited dataset \nof proxy and tide-gauge records. This study establishes three new RSL records for \nsoutheastern Australia (covering ~1830 – 2018) from analyses of salt-marsh sediments. New \ntraining sets of contemporary salt-marsh foraminifera were used for transfer-function \nanalyses to derive palaeo sea-level estimates. High-resolution chronologies were established \nvia Accelerator Mass Spectrometry radiocarbon, radiogenic lead, stable lead isotope ratios \nand pollen analyses. The new records demonstrate that, when corrected for glacio-isostatic \nadjustment, sea level has risen by ~0.2 – 0.3 m since ~1830 in southeastern Australia. Rates of \nsea-level rise were especially high over the first half of the 20th century, with maximum \naverage rates of 4.0 (-0.4 – 7.1 95 % confidence range) mm yr-1, but there is regional variability \nbetween sites. A modelled sea-level budget indicates that the acceleration was initially driven \nby the barystatic component (including gravity, rotation and deformation), but subsequently \namplified and driven by sterodynamic sea-level change. An analysis of the sea-level \nfingerprints of the barystatic component to 20th century global sea-level rise points at a \nsignificant input from the Greenland (17 %) and Antarctic Ice Sheets (11 %) as well as glaciers \nin Alaska (14 %), the Russian Arctic (10 %), western Canada and the US (9 %), south Asia and \nsouthern Andes (8 % each).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".