The southern North Sea as a natural palaeo-laboratory to reconstruct the coastal response to Last Interglacial sea-level rise
Bibliographic record
Abstract
Current models that project sea-level rise beyond 2100 have large uncertainties because recent observation encompass a too limited range of climate variability to provide robust tests against which to simulate future changes. It is crucial to turn to the geological record where there are large-scale changes in climate, but the current interglacial provides limited evidence for how the Earth-system responds to increased temperatures, and therefore it is necessary to study previous climatically-warm periods. Global temperatures during the Last Interglacial were ~1oC warmer than pre-industrial values and 3-5oC warmer at polar latitudes, during which time global mean sea level was likely 6-9 m above present. Though the drivers of warming during the Last Interglacial are different to those of today, it is the amplified warming at polar latitudes, the primary locations of the terrestrial ice masses likely to contribute to long term sea-level rise, which makes the Last Interglacial an ideal palaeo-laboratory to understand coastal response to sea-level rise. However, our understanding of Last Interglacial sea level change is primarily limited to tropical and sub-tropical latitudes and it is important to understand the response of temperate estuarine settings to rising sea level. The ERC-funded RISeR project (Rates of Interglacial Sea-level Change, and Responses) focuses on specifically targeting palaeo shorelines buried within the southern North Sea, preserved beyond the limit of the Last Glacial Maximum ice sheets. Buried Last Interglacial sequences in this area provide a valuable record of marine transgression and are being unveiled in new geophysical and geotechnical datasets acquired to support the offshore renewable energy development. This offshore sedimentary archives offer significant advantages over the geomorphologically restricted onshore records allowing us to trace the transgression over a much large area, and should capture the earliest flooding of the Last Interglacial North Sea basin, when the far-field data suggests ice sheet melt was at it maximum. By integrating the already available datasets with newly acquired samples as part of the project, we aim to develop new palaeoenvironmental reconstructions of the Last Interglacial sea-level change from northwest Europe, providing the first chronological constraints on timing, and therefore rates. This has the potential to allow us to ‘fingerprint’ the source of melt (Greenland and/or Antarctica) during the interglacial sea-level highstand.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".