Mixing Nonlocality and Mixing Anisotropy in an Idealized Western Boundary Current Jet
Bibliographic record
Abstract
Abstract Motivated by the key role of western boundary currents in shaping water mass distribution and gyre water exchanges, this study characterizes mixing in an idealized western boundary current jet using a barotropic quasigeostrophic model with numerical particles deployed. Both the nonlocality of mixing, depicted by nonlocality ellipses, and mixing anisotropy, depicted by mixing ellipses, are estimated. Mixing is more nonlocal within the jet compared to the jet flanks. In general, the size of nonlocality ellipses, a metric of the degree of mixing nonlocality, scales with the eddy velocity magnitude and the equilibration time for diffusivity. The tilt and eccentricity of the nonlocality ellipses, a characterization of the anisotropy of mixing nonlocality, agree with those of momentum flux ellipses in the regions where mixing nonlocality is small. Mixing ellipse characteristics are flow regime dependent. In regions dominated by wave radiation, the mixing ellipses align with the contours of the wave streamfunction and are very anisotropic. Inside the recirculations, however, the mixing ellipses are nearly isotropic. Mixing ellipses are zonally elongated in the jet upstream because of the suppression of cross-jet mixing by the jet and the anisotropy of eddy velocity, and they can have negative minor axis length in the jet downstream, indicating negative cross-jet eddy diffusivity, which is consistent with upgradient eddy fluxes there. Thus, despite significant spatial heterogeneity in mixing nonlocality and anisotropy, in this idealized system at least, spatial patterns in these diagnostics tend to be relatively large scale and tied to larger-scale dynamics. The implications of these results to eddy parameterization and jet dynamics are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".