Baroclinic Tidal Energetics Inferred from Satellite Altimetry
Bibliographic record
Abstract
Abstract The energetics of baroclinic tides are analyzed using the High Resolution Empirical Tide (HRET) model. The HRET model consists of maps of the sea surface height (SSH) anomaly associated with that component of the tides’ baroclinic pressure fields, which are phase locked with the gravitational tidal potential. The dynamical assumptions underpinning the transformation of SSH into corresponding baroclinic velocity and energy flux are examined critically through comparisons with independent information and term balances in the equations of motion. It is found that the HRET-derived phase speed of the mode-1 baroclinic tide agrees closely with the phase speed predicted by the theory for long waves propagating through the observed climatological stratification. The HRET SSH is decomposed into contributions from separate vertical modes, and the energy, energy flux, and energy flux divergence of mode-1 (for M2, S2, K1, and O1) and mode-2 (for M2) tides are computed, with an emphasis on the most accurately determined mode-1 M2. The flux divergence of HRET mode-1 M2, computed as the contour integral of the outbound normal flux around strong generation regions, is found to correspond with independent estimates of the area-integrated barotropic-to-baroclinic-mode-1 conversion, although, there is considerable uncertainty in both the flux divergence and the barotropic-to-baroclinic conversion. Further progress on mapping the baroclinic tidal energetics from altimeter observations will require more dynamically complete descriptions of the baroclinic tides than can be provided by kinematic models of SSH, such as HRET.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".