Overturning in the Subpolar North Atlantic Program: A New International Ocean Observing System
Bibliographic record
Abstract
Abstract For decades oceanographers have understood the Atlantic meridional overturning circulation (AMOC) to be primarily driven by changes in the production of deep-water formation in the subpolar and subarctic North Atlantic. Indeed, current Intergovernmental Panel on Climate Change (IPCC) projections of an AMOC slowdown in the twenty-first century based on climate models are attributed to the inhibition of deep convection in the North Atlantic. However, observational evidence for this linkage has been elusive: there has been no clear demonstration of AMOC variability in response to changes in deep-water formation. The motivation for understanding this linkage is compelling, since the overturning circulation has been shown to sequester heat and anthropogenic carbon in the deep ocean. Furthermore, AMOC variability is expected to impact this sequestration as well as have consequences for regional and global climates through its effect on the poleward transport of warm water. Motivated by the need for a mechanistic understanding of the AMOC, an international community has assembled an observing system, Overturning in the Subpolar North Atlantic Program (OSNAP), to provide a continuous record of the transbasin fluxes of heat, mass, and freshwater, and to link that record to convective activity and water mass transformation at high latitudes. OSNAP, in conjunction with the Rapid Climate Change–Meridional Overturning Circulation and Heatflux Array (RAPID–MOCHA) at 26°N and other observational elements, will provide a comprehensive measure of the three-dimensional AMOC and an understanding of what drives its variability. The OSNAP observing system was fully deployed in the summer of 2014, and the first OSNAP data products are expected in the fall of 2017.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".