Intercomparison of the Charnock and CORE bulk wind stress formulations for coastal ocean modelling
Bibliographic record
Abstract
Abstract. The accurate parameterisation of momentum and heat transfer across the air-sea interface is vital for realistic simulation of the atmosphere-ocean system. In many modelling applications accurate representation of the wind stress is required to numerically reproduce surge, coastal ocean circulation, surface waves, turbulence and mixing. Different formulations can be implemented and impact the accuracy of: the instantaneous and long-term residual circulation; the surface mixed layer; and the generation of wave-surge conditions. This, in turn, affects predictions of storm impact, sediment pathways, and coastal resilience to climate change. The specific numerical formulation needs careful selection to ensure the accuracy of the simulation. Two wind stress formulae widely used in respectively the ocean circulation and the storm surge communities are studied with focus on an application to the NW region of the UK. Model-observation validation is performed at two nearshore and one estuarine ADCP stations in Liverpool Bay, a hypertidal region of freshwater influence with vast intertidal areas. The period of study covers both calm and extreme conditions to fully test the robustness of the 10 m wind stress component of the Common Ocean Reference Experiment (CORE) bulk formulae and the Charnock relation. In this coastal application a realistic barotropic-baroclinic simulation of the circulation and surge elevation is setup, demonstrating greater accuracy occurs when using the Charnock relation for surface wind stress.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".