8 citations · 11 across the 4 of their papers we have counts for
5 papers
Online model error correction with neural networks in the incremental 4D-Var framework
Alban Farchi, Marcin Chrust, Marc Bocquet +2
Recent studies have demonstrated that it is possible to combine machine learning with data assimilation to reconstruct the dynamics of a physical model partially and imperfectly ob…
Estimating Model Error Covariances with Artificial Neural Networks
Massimo Bonavita, Patrick Laloyaux
Methods to deal with systematic model errors are an increasingly important component of modern data assimilation systems and their effectiveness has increased in recent years thank…
A comparison of combined data assimilation and machine learning methods for offline and online model error correction
Alban Farchi, Marc Bocquet, Patrick Laloyaux +2
Recent studies have shown that it is possible to combine machine learning methods with data assimilation to reconstruct a dynamical system using only sparse and noisy observations…
Exploring the structure of time-correlated model errors in the ECMWF Data Assimilation System
Massimo Bonavita
Model errors are increasingly seen as a fundamental performance limiter in both Numerical Weather Prediction and Climate Prediction simulations run with state of the art Earth syst…
Using machine learning to correct model error in data assimilation and forecast applications
Alban Farchi, Patrick Laloyaux, Massimo Bonavita +1
The idea of using machine learning (ML) methods to reconstruct the dynamics of a system is the topic of recent studies in the geosciences, in which the key output is a surrogate mo…