Verification and Intercomparison of Global Ocean Eulerian Currents
Bibliographic record
Abstract
All ocean prediction systems contain errors. Verification and post-processing of the ocean forecasts is essential and contributes significantly to forecast accuracy. This paper describes the verification of ocean model currents against Eulerian currents derived from the drifting buoys, and intercomparison of currents from various global models. The OceanPredict task team for Intercomparison and Validation (IV-TT) has established the CLASS4 data standard for routine forecast verification against reference observing platforms. The set of CLASS4 reference data has been recently extended to include near-surface currents derived from the trajectories of drifting buoys drogued at 15 m. We have applied these data to the Ocean Model, Analysis and Prediction System (OceanMAPS) at the Australian Bureau of Meteorology for verification and inter-comparison with multiple global ocean models namely: Mercator Océan International ocean forecast system (MOi); the operational models of the Met Office, UK: Forecast Ocean Assimilation (FOAM) and Coupled Atmosphere-Land-Ocean-Ice Data Assimilation (CPLDA) systems; and the Global Ice Ocean Prediction System (GDPS-GIOPS) at the Canadian Centre for Meteorological and Environmental Prediction (CCMEP). The aims for this verification analysis are to extend the routine monitoring of the operational system; to assess the OceanMAPS skill against other models; and to inform our stakeholders of the OceanMAPS performance. We have assessed the impacts of adding Stokes drift and tidal currents from separate global wave and global tidal models to the model currents on the verification of currents. Inclusion of surface stokes drift improves the model representation with the observations while inclusion of tides has no significant impact. Overall, the MOi and the new version of OceanMAPS show the best performance against the observations. Although there are significant differences in the model configurations of the eight models under evaluation, all models are shown to be remarkably statistically equivalent with consistent spatial and temporal patterns. Thus, indicating that the main differences are attributable to unrepresented processes. We therefore conclude that there remains scope to further improve the representation of the modelled currents with the observations.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".