Abstract Purpose of Review Assessment of the impact of ocean resolution in Earth System
models on the mean state, variability, and future projections and discussion of prospects for …

The use of machine learning to build subgrid parametrizations for climate models is
receiving growing attention. State‐of‐the‐art strategies address the problem as a supervised …

The AB system is a critical component of fluid dynamics, as it is capable of modeling the
nonlinear wave motions in two-layer fluids. In this study, we investigate soliton molecules …

We address the question of how to use a machine learned (ML) parameterization in a
general circulation model (GCM), and assess its performance both computationally and …

The use of coarse resolution and strong grid‐scale dissipation has prevented global ocean
models from simulating the correct kinetic energy level. Recently parameterizing energy …

Subgrid parameterizations of mesoscale eddies continue to be in demand for climate
simulations. These subgrid parameterizations can be powerfully designed using physics …

The understanding and representation of energetic transfers associated with ocean
mesoscale eddies is fundamental to the development of parameterizations for climate …

Mesoscale eddies modulate the stratification, mixing, tracer transport, and dissipation
pathways of oceanic flows over a wide range of spatiotemporal scales. The parameterization …

Accurate parameterizations of eddy fluxes across prograde, buoyant shelf and slope
currents are crucial to faithful predictions of the heat transfer and water mass transformations …

This 3-day hindcast case study focuses on the effects of the initial errors, a non-negligible
factor in oceanic prediction, on VTS prediction in the NSCS and provides scientific guidance …