9 citations · 14 across the 3 of their papers we have counts for
4 papers
Accurate deep learning-based filtering for chaotic dynamics by identifying instabilities without an ensemble
Marc Bocquet, Alban Farchi, Tobias S. Finn +5
We investigate the ability to discover data assimilation (DA) schemes meant for chaotic dynamics with deep learning. The focus is on learning the analysis step of sequential DA, fr…
Tailoring data assimilation to discontinuous Galerkin models
Ivo Pasmans, Yumeng Chen, Alberto Carrassi +1
During the last few years discontinuous Galerkin (DG) methods have received increased interest from the geophysical community. In these methods the solution in each grid cell is ap…
Inferring the instability of a dynamical system from the skill of data assimilation exercises
Yumeng Chen, Alberto Carrassi, Valerio Lucarini
Data assimilation (DA) aims at optimally merging observational data and model outputs to create a coherent statistical and dynamical picture of the system under investigation. Inde…
Dimension Splitting and a Long Time-Step Multi-Dimensional Scheme for Atmospheric Transport
Yumeng Chen, Hilary Weller, Stephen Pring +1
Dimensionally split advection schemes are attractive for atmospheric modelling due to their efficiency and accuracy in each spatial dimension. Accurate long time-steps can be achie…