Deep ocean circulation in the subpolar North Atlantic observed by acoustically-tracked floats
Bibliographic record
Abstract
The deep circulation in the subpolar North Atlantic determines the spread and mixing of high latitude climate signals to lower latitudes. However, our current understanding of the subpolar deep circulation has been limited due to relatively sparse observational data. To improve that understanding, we construct gridded fields of mean velocity and eddy kinetic energy (EKE) in the deep (1800–2800 dbar) subpolar North Atlantic using direct velocity measurements from 122 subsurface acoustically-tracked floats that drifted during June 2014–January 2019. The mean velocity field reveals a relatively strong deep boundary current around Greenland and in the Labrador Sea, with a weaker deep boundary current over the eastern flank of the Reykjanes Ridge, and near-zero mean flow over the western flank, implying a discontinuous deep boundary current across the subpolar basin. The deep EKE, albeit with smaller magnitudes, generally resembles the EKE pattern at the ocean surface, including relatively high values along pathways of the North Atlantic Current and west of Greenland where the Irminger Rings are formed. A surprising finding about deep EKE is an elevated band east of Greenland that parallels the coast and is not present in the surface EKE field. This high EKE band is possibly attributed to the combined influence from propagating Denmark Strait Overflow Cyclones, variability of the wind-driven recirculation offshore of southeast Greenland, and/or topographic waves. The float-based flow fields constructed in this study provide an unprecedented quantitative view of the kinematic properties of the large-scale deep circulation in the subpolar North Atlantic. Combined with cross-basin Eulerian measurements, we believe these recent observations provide a benchmark for testing and improving numerical simulations of deep ocean circulation and the Meridional Overturning Circulation, which are urgently needed for climate change predictions.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".