Towards high-fidelity simulations of coastal submesoscale baroclinic instabilities with MPAS-O (vE3SM3.0.0) – Part 1: Idealized experiments

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 comparing coastal submesoscale processes representation in two models with very different numerical approaches: MPAS-O, an unstructured grid global ocean model, and ROMS, a structured grid regional model. This study is 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, with the previously validated ROMS model serving as a benchmark. An important motivation for this study is to examine the suitability of models designed for global ocean simulations in reproducing energetic coastal flows. 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 exhibits a stronger variance-producing response 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.