An Energy- and Enstrophy-Constrained Parameterization of Barotropic Eddy Potential Vorticity Fluxes
Bibliographic record
Abstract
Abstract A parameterization for barotropic eddy potential vorticity (PV) fluxes is introduced, which applies both an energetic and an enstrophetic constraint to a downgradient PV mixing closure. An eddy kinetic energy budget and an eddy potential enstrophy budget are employed to constrain the parameterized eddy PV fluxes. Through the budgets, the parameterization facilitates a bidirectional exchange of kinetic energy between the parameterized eddies and the large-scale flow and a conversion of potential enstrophy from the large-scale flow to the parameterized eddies. The parameterization is tested in simulations of barotropic, freely decaying turbulence in a doubly periodic domain over variable bottom topography. The simulations show that employing the parameterization results in an upscale transfer of kinetic energy on average, consistent with quasigeostrophic theory. Furthermore, the kinetic energy and potential enstrophy budgets employed are sufficient to constrain the large-scale flow in a realistic manner when compared to an eddy-resolving model. As a result, a topography-following flow of the correct magnitude emerges in a coarse-resolution model with parameterized eddy effects. Dissipation in the coarse-resolution simulations is significant, leading to the most significant source of discrepancy between the coarse-resolution simulation with parameterized eddy effects and the eddy-resolving simulation. This work constitutes a first step toward the ultimate aim of parameterizing both baroclinic and barotropic turbulence. How this may be achieved by integrating this parameterization with other methods in more realistic ocean simulations is discussed. Significance Statement Mesoscale eddies in the ocean, the analog of atmospheric weather systems, are an important factor in determining the large-scale flow. In particular, in regions where the height of the ocean floor varies, eddies drive the flow toward a structure which resembles that of the ocean floor. Commonly employed methods of representing eddies in climate models are unable to capture this process because they fail to represent accurately the underlying physical processes that constrain the eddies. Here, we present a method for representing ocean eddies in climate models, which uses the conservation of energy, and of a similar quantity that measures the amount of turbulent stirring, to constrain the feedback of the eddies on the large-scale flow. We test the new method experimentally in a simple computational ocean model, analyzing both the parameters that are important in the underlying physics and the properties of the large-scale flows produced by the eddies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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".