T. S. Finn

Accounting for model error in ensemble variational data assimilation through learned generative dynamics

Many approaches have recently been proposed to combine data assimilation with machine learning for improved forecasts with geophysical models. Here, we focus on combining advanced sequential data assimilation schemes with a generative forecasting model which accounts for complex model errors. This generative model prov...