143 citations · 304 across the 12 of their papers we have counts for
3 papers · 1 filter
Inference of stochastic parameterizations for model error treatment using nested ensemble Kalman filters
Guillermo Scheffler, Juan Ruiz, Manuel Pulido
Stochastic parameterizations are increasingly being used to represent the uncertainty associated with model errors in ensemble forecasting and data assimilation. One of the challen…
A Review of Innovation-Based Methods to Jointly Estimate Model and Observation Error Covariance Matrices in Ensemble Data Assimilation
Pierre Tandeo, Pierre Ailliot, Marc Bocquet +4
Data assimilation combines forecasts from a numerical model with observations. Most of the current data assimilation algorithms consider the model and observation error terms as ad…
Kernel embedding of maps for sequential Bayesian inference: The variational mapping particle filter
Manuel Pulido, Peter Jan vanLeeuwen
In this work, a novel sequential Monte Carlo filter is introduced which aims at efficient sampling of high-dimensional state spaces with a limited number of particles. Particles ar…