Drivers of deep heat uptake in the North Atlantic Subpolar Gyre
Bibliographic record
Abstract
The decadal to multi-decadal temperature variability of the intermediate (700 – 2000 m) North Atlantic Subpolar Gyre (SPG) significantly imprints the global pattern of ocean heat uptake. Here, the origins and dominant pathways of this variability are investigating with an ocean analysis product (EN4), an ocean state estimate (ECCOv4), and idealized modeling approaches. Sustained increases and decreases of intermediate temperature in the SPG correlate with long-lasting warm and cold states of the upper ocean – the Atlantic Multidecadal Variability – with the largest anomalous vertical heat exchanges found in the vicinity of continental boundaries and strong ocean currents. In particular, vertical diffusion along the boundaries of the Labrador and Irminger Seas and advection in the region surrounding Flemish Cap stand as important drivers of the recent warming trend observed during 1996-2014. The impact of those processes is well captured by a 1-dimensional diffusive model with appropriate boundary-like parametrization and illustrated through the continuous downward propagation of a passive tracer in an eddy-permitting numerical simulation. Our results imply that the slow and quasi-periodic variability of intermediate thermohaline properties in the SPG are not strictly driven by the well-known convection-restratification events in the open seas but also receives a key contribution from boundary sinking and mixing. Increased skill for modelling and predicting intermediate-depth ocean properties in the North Atlantic will hence require the appropriate representation of surface-deep dynamical connections within the boundary currents encircling Greenland and Newfoundland.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".