Near-Inertial Surface Currents around Islands
Bibliographic record
Abstract
Abstract Motivated by observations of enhanced near-inertial currents at the island chain of Palau, the modification of wind-generated near-inertial oscillations (NIOs) by the presence of an island is examined using the analytic solutions of Longuet-Higgins and a linear, inviscid, 1.5-layer reduced-gravity model. The analytic solution for oscillations at the inertial frequency f provides insights into flow adjustment near the island but excludes wave dynamics. To account for wave motion, the numerical model initially is forced by a large-scale wind field rotating at f, where the forcing is increased then decreased to zero. Numerical simulations are carried out over a range of island radii and the ocean response detailed. Near the island, wind energy in the frequency band near f can excite subinertial island-trapped waves and superinertial Poincaré waves. In the small-island limit, both the Poincaré waves and the island-trapped waves are very near f, and their sum resembles the Longuet-Higgins analytic solution but with increased amplitude near the island. The flow field can be viewed as primarily a far-field NIO locally deflected by the island plus an island-trapped contribution, leading to enhanced near-inertial currents near the island, on the scale of the island radius. As the island size is increased, the island-trapped wave frequency deviates further from f and its amplitude depends strongly on the frequency bandwidth and wavenumber structure of the wind forcing. In the large-island limit, the island-trapped wave resembles a Kelvin wave, and the sum of incident and reflected Poincaré waves suppresses the near-inertial current amplitude near the island. Significance Statement Strong, impulsive winds over the ocean excite currents that rotate in the opposite direction to Earth’s rotation. This work examines how these wind-generated currents, known as near-inertial oscillations (NIOs), are modified by the presence of an island. Around small islands, the primary response is locally enhanced near-inertial currents. Alternatively, around large islands, near-inertial currents are weaker. Understanding how these currents behave should provide insight into the physical processes that drive current variability near islands and spur local mixing.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".