Climate modelling and analysis are facing new demands to enhance projections and
climate information. Here we argue that now is the time to push the frontiers of machine …

A holistic review is given of the Southern Ocean dynamic system, in the context of the crucial
role it plays in the global climate and the profound changes it is experiencing. The review …

Vertical mixing parameterizations in ocean models are formulated on the basis of the
physical principles that govern turbulent mixing. However, many parameterizations include …

Data assimilation is often viewed as a framework for correcting short‐term error growth in
dynamical climate model forecasts. When viewed on the time scales of climate however …

We parameterize sub‐grid scale (SGS) fluxes in sinusoidally forced two‐dimensional
turbulence on the β‐plane at high Reynolds numbers (Re∼ 25,000) using simple 2‐layer …

Ocean eddies affect large‐scale circulation and induce a kinetic energy cascade through
their non‐linear interactions. However, since global observations of eddy dynamics come …

Neural networks (NNs) are increasingly used for data‐driven subgrid‐scale
parameterizations in weather and climate models. While NNs are powerful tools for learning …

We review how the international modelling community, encompassing integrated
assessment models, global and regional Earth system and climate models, and impact …

Ocean mesoscale eddies are often poorly represented in climate models, and therefore,
their effects on the large scale circulation must be parameterized. Traditional …

In this study, we perform online sea ice bias correction within a Geophysical Fluid Dynamics
Laboratory global ice‐ocean model. For this, we use a convolutional neural network (CNN) …