Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz `96 Model
Stochastic parameterizations account for uncertainty in the representation of unresolved subgrid processes by sampling from the distribution of possible subgrid forcings. Some …
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