A new study offers a compelling example where the merger of dynamical modeling, machine learning, and ocean measurements enhances oceanographic understanding, monitoring, and mapping.
Oliver Watt-Meyer
Associate Editor, JAMES
Posted inEditors' Highlights
New Machine Learning Parameterization Tested on Atmospheric Model
For the first time, a neural network parameterization of subgrid momentum transport is developed by training on a coarse-grained high-resolution atmospheric simulation.