Modellierung der Dynamiken des Nordatlantiks und der Labrador See mit dem hochaufgelösten Ozeanmodell FESOM
Bibliographic record
Abstract
The subpolar regions of the North Atlantic ocean are crucial for the global climate in terms of deep water formation, which is a major driver for the Atlantic Meridional Overturning Circulation (AMOC) that transports heat into northern latitudes and returns cold deep water masses southward. The influence of a high horizontal resolution (5-15 km) on the general circulation and hydrography in the North Atlantic is investigated using the finite element sea ice-ocean model FESOM. A stronger shift of the upper ocean circulation and water mass properties during the model spinup is found in the high-resolution model version compared to the low-resolution (ca. 1 deg) control run. In quasi-equilibrium, the high-resolution model is able to reduce typical low-resolution model biases. Especially, it exhibits a weaker salinification of the North Atlantic subpolar gyre and a reduced mixed layer depth in the Labrador Sea. However, during the spinup adjustment, initially improved high-resolution features partially reduce over time: the strength of the Atlantic overturning and the path of the North Atlantic Current are not maintained, and hence hydrographic biases known from low-resolution ocean models return in the high-resolution quasi-equilibrium state. Long baroclinic Rossby waves are identified as a potential cause for the strong upper ocean adjustment of the high-resolution model. In addition, the high-resolution model is able to represent turbulent processes on the meso- and submesoscale within the Labrador Sea interior. Mesoscale eddies transport buoyant seawater into regions of strong convection, thereby contributing significantly to restratification. In particular, ageostrophic velocities associated with baroclinic instability were found to play a crucial role on length scales on the order of O(10) km. Until now, the dynamics on such scales were rarely modeled with a realistic global high-resolution ocean model in quasi-equilibrium.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".