the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 13 May 2026
Towards high-fidelity simulations of coastal submesoscale baroclinic instabilities with MPAS-O (vE3SM3.0.0) Part I: Idealized experiments
Abstract. Rapid advances in computational power over the past decade have enabled global, kilometer-scale simulations that realistically represent open-ocean submesoscale dynamics. However, the ability of global ocean models to represent coastal submesoscale dynamics—where flows are more heterogeneous and strongly shaped by coastlines, bathymetry, and buoyancy inputs—remains largely unexplored. This study is the first of two companion papers assessing coastal submesoscale processes in MPAS-O, an unstructured global ocean model. Here, we present the first idealized evaluation of MPAS-O’s representation of coastal submesoscale dynamics using observed conditions in the Mississippi–Atchafalaya (M-A) River plume as a template for initial conditions, and with the previously validated structured-grid regional model ROMS serving as a benchmark. We compare statistical metrics based on flow invariants—total strain, relative vorticity, and divergence—as well as velocity gradients in frontal coordinates, across horizontal resolutions ranging from 10 km to 100 m within an idealized model domain. We find that the representation of submesoscale baroclinic instabilities is highly similar across all resolutions such that the impact of model choice is smaller than the choice of spatial grid resolution. We also compare numerical and physical mixing between models using online diagnostics based on discrete variance decay. We find that ROMS generally has more numerical mixing and less physical mixing than MPAS-O across all resolutions. Trends in numerical mixing likely arise from MPAS-O's flux-corrected transport tracer advection scheme, which is shown to be anti-diffusive relative to the MPDATA scheme used in the ROMS simulations. Trends in physical mixing likely arise from differences in each model’s configuration of the vertical mixing scheme (the K-Profile Parameterization). A companion paper extends this idealized model-model comparison to realistic simulations of the M-A River plume.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-1566', Sergey Danilov, 05 Jun 2026
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RC2: 'Comment on egusphere-2026-1566', Anonymous Referee #2, 14 Aug 2026
Review of “Towards high-fidelity simulations of coastal submesoscale baroclinic instabilities with MPAS-O (vE3SM3.0.0) Part I: Idealized experiments”
General comment
This manuscript presents a systematic comparison of MPAS-O and ROMS simulations over a wide range of horizontal resolutions. The experiments are computationally substantial, and the comparison of frontal statistics and physical and numerical mixing is potentially useful for the development of high-resolution unstructured-grid ocean models. The manuscript is generally well organized, but the central claim concerning the representation of submesoscale baroclinic instability requires stronger dynamical support. I recommend revision before publication.
Major comment
The title and stated objective emphasize coastal submesoscale baroclinic instabilities, whereas most analyses focus on kinematic and statistical characteristics, including surface kinetic energy, vorticity, divergence, strain, frontal velocity gradients, and tracer mixing. Similar submesoscale intensity or flow statistics do not necessarily imply that the two models represent the underlying instability dynamics similarly. In particular, comparable kinetic energy may result from different balances among available-potential-energy release, baroclinic conversion, wind input, and physical or numerical dissipation. This possibility is especially relevant because the two models show different instability timing and mixing behavior. The authors should therefore provide a more direct comparison of the instability energetics, such as the evolution of available potential energy and eddy kinetic energy, baroclinic conversion or vertical buoyancy flux, and relevant dissipation terms, at least for representative resolutions.
Minor comments
- Line 52: “ROMS; Shchepetkin and McWilliams, 2005”.
- Line 192: “tracer advection schemes”.
- Line 203: it should be Table 1.
- Line 227: “vertical velocity cell phases” should likely be “vertical velocity cell faces”.
- Line 241: Please define explicitly how the frontal angle α is determined and how points with weak gradients are treated.
- 6. Figure 4 caption: please explain “Negative relative vorticity values correspond to a greater number of eddies, while positive vorticity values indicate a greater number of fronts.”
- 7. Lines 353–355: it would be better to use |δ/f|, with convergence and divergence treated separately.
- 8. Figure 6 caption: The ROMS panels should be cited as (e–h).
- 9. Line 378: “principal component”.
- 10. Line 473: “certainly due to”.
- 11. Figure A1 caption: “and (b) MPAS-O”.
Citation: https://doi.org/10.5194/egusphere-2026-1566-RC2
Data sets
Towards high-fidelity simulations of coastal submesoscale baroclinic instabilities with MPAS-O (vE3SM3.0.0) Part I: Data and Code Kyle Hinson, Dylan Schlichting, Robert Hetland, Darren Engwirda, Katherine Smith, Mark Petersen, and Kaila Uyeda https://doi.org/10.5281/zenodo.18868239
Video supplement
MPASO_Bichan_AllResolutions_Day0_Day50.mp4; ROMS_Bichan_AllResolutions_Day0_Day50.mp4 Kyle Hinson, Dylan Schlichting, Robert Hetland, Darren Engwirda, Katherine Smith, Mark Petersen, and Kaila Uyeda https://doi.org/10.5281/zenodo.18868239
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- 1
The manuscript presents a test case and compares the performance of ROMS and MPAS-O. The test could be of interest for other groups, as it explores model performance at rather small scales where dynamics is very much different from the dynamics dominated by mesoscale baroclinic instabilities. I therefore recommend this manuscript for the journal. Below are some suggestions/remarks that could be helpful.
The Introduction is too MPAS-centric in my opinion. The value of this manuscript is in presenting a properly documented test case and simulation results. The test case and documented diagnostics can be used by other groups. Place some focus on this. Staggered discretizations on unstructured meshes have spurious modes, and therefore need a certain level of dissipation. Test cases that explore fine-scale dynamics which might be affected by dissipations or by modes are indeed welcome. You show that for MPAS all this does not present a problem. Other groups can, perhaps, follow.
Small things:
145 'enstrophy-dissipating' -- since the Leith viscosity enters the momentum equation, it serves to dissipate kinetic energy dissipating. (It is the derivation of this viscosity that is based on the idea of enstrophy dissipation).
Section 2.3.5. Formula (8) gives an estimate only for 1D uniform velocity. In a general case the third order scheme will introduce viscosity in the direction of velocity, while the one in MPAS-O is isotropic. So it is difficult to say which viscosity is larger. A better way to judge would be to estimate the KE dissipation due to horizontal advection in ROMS and explicit biharmonic viscosity in MPAS-O (This would be of interest for others too).
230 The relative vorticity is, strictly speaking, not an invariant.
265 This diagnostics works only for the first order upwind advection schemes. For higher-order schemes, the estimate it provides locally are contaminated by much larger dispersive errors, see Banerjee et al., 2024. For bulk volume estimate one can look at the change of s^2 due to advection of s without running any special diagnostics.
389 ' ... of antidiffusion ...' One cannot call this antidiffusion, as the negative DVD may reflect dispersive errors of the method.
407 ' ... anti-diffusive response ... ' I find this result to be strange. If the third order advection is used in MPAS-O together with flux correction method, both are dissipative. Even if the third-fourth order advection is applied, it is still dissipative. The standard FCT algorithm is dissipative.
485 ' is more anti-diffusive' --- or less diffusive
Sergey Danilov