A Consistent Sea-Level Reconstruction and Its Budget on Basin and Global Scales over 1958–2014
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Different sea level reconstructions show a spread in sea level rise over the last six decades and it is not yet certain whether the sum of contributors explains the reconstructed rise. Possible causes for this spread are, among others, vertical land motion at tide-gauge locations and the sparse sampling of the spatially variable ocean. To assess these open questions, reconstructed sea level and the role of the contributors are investigated on a local, basin, and global scale. High-latitude seas are excluded. Tide-gauge records are combined with observations of vertical land motion, independent estimates of ice-mass loss, terrestrial water storage, and barotropic atmospheric forcing in a self-consistent framework to reconstruct sea level changes on basin and global scales, which are compared to the estimated sum of contributing processes. For the first time, it is shown that for most basins the reconstructed sea level trend and acceleration can be explained by the sum of contributors, as well as a large part of the decadal variability. The sparsely sampled South Atlantic Ocean forms an exception. The global-mean sea level reconstruction shows a trend of 1.5 ± 0.2 mm yr−1 over 1958–2014 (1σ), compared to 1.3 ± 0.1 mm yr−1 for the sum of contributors. Over the same period, the reconstruction shows a positive acceleration of 0.07 ± 0.02 mm yr−2, which is also in agreement with the sum of contributors, which shows an acceleration of 0.07 ± 0.01 mm yr−2. Since 1993, both reconstructed sea level and the sum of contributors show good agreement with altimetry estimates.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it