Ensemble-based kernel learning for a class of data assimilation problems with imperfect forward simulators.
Simulator imperfection, often known as model error, is ubiquitous in practical data assimilation problems. Despite the enormous efforts dedicated to addressing this problem, properly handling simulator imperfection in data assimilation remains to be a challenging task. In this work, we propose an ap...
Main Author: | Xiaodong Luo |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2019-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0219247 |
Similar Items
-
Multilevel ensemble data assimilation
by: Gregory, Alastair
Published: (2017) -
Kernel-Based Ensemble Learning in Python
by: Benjamin Guedj, et al.
Published: (2020-01-01) -
An approach to localization for ensemble-based data assimilation.
by: Bin Wang, et al.
Published: (2018-01-01) -
Ultra Rapid Data Assimilation Based on Ensemble Filters
by: Roland Potthast, et al.
Published: (2018-10-01) -
Mesoscale ensemble-based data assimilation and parameter estimation
by: Aksoy, Altug
Published: (2005)