Evaluation of Ocean Tide Models Used for Jason-2 Altimetry Corrections
Bibliographic record
Abstract
It has been more than a decade since the last comprehensive accuracy assessment of global ocean tide models. Here, we conduct an evaluation of the barotropic ocean tide corrections, which were computed using FES2004 and GOT00.2, and other models on the Jason-2 altimetry Geophysical Data Record (GDR), with a focus on selected coastal regions with energetic ocean dynamics. We compared nine historical and contemporary ocean tide models with pelagic tidal constants and with multiple satellite altimetry mission (T/P, ERS-1/-2, Envisat, GFO, Jason-1/-2) sea level anomalies using variance reduction studies. All accuracy assessment methods show consistent results. We conclude that all the contemporary ocean tide models evaluated have similar performance in the selected coastal regions. However, their accuracies are region-dependent and overall are significantly worse than those in the deep-ocean, which are at the 2–3 cm RMS (root-mean-square) level. The Gulf of Mexico and Northwest Atlantic regions present the least reduction of altimetry sea surface height variability after ocean tides are removed, primarily because of large oceanic variability associated with loop currents in the Gulf of Mexico and the Gulf Stream in the Northwest Atlantic.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".