Characteristics of Mesoscale and Submesoscale Eddies in the Labrador Sea: Observations vs. Model
Bibliographic record
Abstract
Mesoscale eddies play an important role in lateral property fluxes. Observational studies often use sea level anomaly maps from satellite altimetry to estimate eddy statistics (incl. eddy kinetic energy). Recent findings suggest that altimetry derived eddy characteristics may suffer from the low spatial resolution of past and current satellite-tracks in high-latitude oceans associated with small Rossby radii. This study presents results of an eddy reconstruction that provides an alternative perspective on the eddy field based on a nonlinear, damping Gauss-Newton optimisation algorithm using ship-based current profiler observations from two research expeditions in the Labrador Sea in 2014 and 2018. The derived eddy characteristics are compared to the high-resolution submesoscale permitting NATL60 model (1/60°). Overall, a total of 14 eddies with radii ranging from 7 to 35km and azimuthal velocities ranging from 20 to 60 cm s−1 were detected, of which 3 eddies were identified as Irminger rings. Irminger rings are characterised by a warm, salty lens either surface trapped or overlaid by a cold, fresh cap of water. The modelled eddies are on average 25% smaller in radius and 20% higher in azimuthal velocity accompanied by increased nonlinearity. The inner ring velocity structure for observations and NATL60 suggests solid-body rotation for 1/2 to 2/3 of the radius. The eddy boundary and outer ring velocity structure follows a more Gaussian-like shape, best described by a exp(−r2) dependency. Furthermore, the maximum azimuthal velocity may deviate from solid-body rotation by more than 30% for the observations and 50% for the model. In order to verify the skill of eddy reconstruction, the NATL60 served as a reference data set for the skill assessment of the Gauss-Newton method. It is shown that the eddy characteristics are affected by the location of the ship track through the velocity field. In most cases, however, the derived properties are not expected to deviate by more than 10%. Spectral analysis of the horizontal velocity implies that the mesoscale regime is well represented in NATL60 compared with the observations. The representation of the submesoscale flow decreases in the model with increasing depth. In particular, observations and model spectra diverge in the pycnocline by roughly one order of magnitude at scales smaller than 50km. Besides, the transition of power spectra slopes from k−2 to k−3 in ship-based measurements and model suggests a weak seasonal signal.
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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 | 0.000 |
| Open science | 0.001 | 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".