| 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.
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