Simulating the ocean’s submesoscale is key to understand the mass and energy cycles of the ocean and the global climate system. Contrast to the ocean’s mesoscale, submesoscale processes are usually highly ageostrophic and manifest at the scales within 10km. Ocean general circulation models with kilometer-resolution are capable to resolve key submesoscale processes, hence indispensable for both process and climate studies. We construct a grid hierarchy for the ocean-sea ice model in the High-Resolution Earth System Model on Sunway supercomputer (SW-HRESM), which is based on Community Earth System Model (CESM2) with deep optimizations on the Chinese home-brew supercomputing architecture of Sunway. The highest grid resolution is 0.03o (2.4km globally). In this study we evaluate the ocean-sea ice coupled simulations by SW-HRESM, focusing on the submesoscale and the kinetic energy (KE) cycles. In particular, highly ageostrophic submesoscale turbulence is simulated, dominated by deepened mixed layers (ML) during winter and the ensuing instabilities. KE and its transition between scales are further evaluated for major western boundary current systems. During winter, submesoscale is shown to dominate inverse cascading which energizes large-scale flows, as well as forward cascading to dissipation scales. The mesoscale-submesoscale continuum and the associated inverse KE cascading is further complemented by the forward KE cascading from the large-scale due to flow instabilities. In order to fully resolve the submesoscale spectrum, including frontal processes and wind-wave interactions, models finer than 1km are needed. Besides the model resolution, improvements for both the ocean and the fully coupled model of SW-HRESM are also discussed.

A document by Lu Yang. Click on the document to view its contents.

This study investigates the influence of oceanic and atmospheric processes in extratropical thermodynamic air-sea interactions resolved by satellite observations (OBS) and by two climate model simulations run with eddy-resolving high-resolution (HR) and eddy-parameterized low-resolution (LR) ocean components. Here, spectral methods are used to characterize the sea surface temperature (SST) and turbulent heat flux (THF) variability and co-variability over scales between 50-10000 km and 60 days-80 years in the Pacific Ocean. The relative roles of the ocean and atmosphere are interpreted using a stochastic upper-ocean temperature evolution model forced by noise terms representing intrinsic variability in each medium, defined using climate model data to produce realistic rather than white spectral power density distributions. The analysis of all datasets shows that the atmosphere dominates the SST and THF variability over zonal wavelengths larger than ~2000-2500 km. In HR and OBS, ocean processes dominate the variability of both quantities at scales smaller than the atmospheric first internal Rossby radius of deformation (R1, ~600-2000 km) due to a substantial ocean forcing coinciding with a weaker atmospheric modulation of THF (and consequently of SST) than at larger scales. The ocean-driven variability also shows a surprising temporal persistence, from intraseasonal to multidecadal, reflecting a red spectrum response to ocean forcing similar to that induced by atmospheric forcing. Such features are virtually absent in LR due to a weaker ocean forcing relative to HR.