Large Eddy Simulations of Upper-Ocean Response to a Midlatitude Storm and Comparison with Observations*
Bibliographic record
Abstract
Abstract A large eddy simulation (LES) model is used to investigate an upper-ocean response to a fall storm in the open ocean of the North Pacific Ocean. The storm is characterized by rapid increases in wind speed and surface heat loss but a relatively steady wave field. The LES model shows that surface convergence zones or windrows organize into line patterns aligned with the wind direction, evolving from nearly parallel lines to irregular structures featuring Y junctions as the wind speed increases. The downwelling-to-upwelling velocity ratio ranges between 1.2 and 1.6, indicating a moderate level of asymmetry between the downwelling and upwelling plumes in Langmuir circulation. During the storm, the turbulent Langmuir number Lat increases from 0.2 to 0.5 while the vertical turbulence intensity σw2 decreases from 1.4 to 0.7 u*2, where u* is the friction velocity. The order of turbulence intensities in three directions switches from crosswind ≈ vertical > downwind directions to downwind > crosswind > vertical directions. This suggests a transition from Langmuir to shear turbulence as the storm progresses. The Hoennikker number (Ho) remains below 0.1 and the strong evaporative heat loss does not contribute much to the turbulence generation in the ocean mixed layer. The LES results are compared with in situ and acoustic measurements collected during the storm. Patterns of model-predicted near-surface downwelling zones are in good agreement with horizontal distributions of bubble clouds revealed in sidescan sonar images. Striking similarity is also found in the temperature anomalies between the LES model and high-resolution thermistor chain measurements.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".