The Nature and Variability of Eddy Kinetic Energy in an Ocean General Circulation Model \nWith a Focus on the South Pacific Subtropical Gyre and the Labrador Sea
Bibliographic record
Abstract
This thesis focuses on the nature of oceanic Eddy Kinetic Energy (EKE), its generation and temporal variability. An Ocean General Circulation Model (OGCM) based on the NEMO code builds the foundation for these investigations. For a first case study, several simulations of a 1/4° configuration are used to investigate the temporal variability of EKE in the South Pacific Subtropical Countercurrent (STCC). Decadal changes in wind stress curl associated with the Interdecadal Pacific Oscillation (IPO) lead to up- and downwelling in the STCC, influencing the meridional density gradient and thereby STCC strength, baroclinic instability and the resulting EKE. An additional 30 to 40% of the local density anomalies can be explained by long baroclinic Rossby waves propagating into the region, modulating the decadal signal of the IPO’s influence in the STCC on interannual time scales. In a second case study, the model’s horizontal resolution is regionally increased to 1/20° in the North Atlantic to investigate different types of mesoscale eddies in the Labrador Sea. On decadal time scales, the temporal variability of EKE in the LS is driven by the large-scale atmospheric circulation. In the case of Convective Eddies (CE), local winter heat loss leads to deep convection, a baroclinically unstable rim-current is established along the edge of the convection area and generates EKE at mid-depth. The variations of EKE associated with the surface intensified Irminger Rings (IR) and Boundary Current Eddies are driven by the large-scale changes of the currents of the subpolar gyre. While IR play a vital role in stratifying large parts of the LS and thus suppressing deep convection, CE are the major driver of rapid restratification during and after deep convection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".