Estimate of the steric contribution to global sea level rise from a comparison of the WOCE one‐time survey with 2006–2008 Argo observations
Bibliographic record
Abstract
It is well known from observations by altimetric satellites (predominantly TOPEX/Poseidon and Jason‐1) that global sea level is rising. What is less well known is exactly how the observed sea level rise is partitioned between a steric contribution (sea level rising because of changes in ambient temperature and salinity) and a contribution arising from the addition of new water mass to the oceans. Strictly speaking, such a separation is not possible because of the non‐linearity in the equation of state for sea water, but in practice the non‐linearities are sufficiently small to allow this separation as a very good first approximation. A careful comparison of the World Ocean Circulation Experiment (WOCE) one‐time survey with recent observations by the Argo array indicate a steric component to sea level rise of 2.2 mm y–1 between the early 1990s and 2006 to 2008. This is a significantly larger rise rate than previously estimated and, along with recent estimates of melt rate from ice sheets, is in much closer agreement with the total rise rate as reported by altimetric satellites, 3.2 ± 0.4 mm y–1 over this period.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".