There has been great progress in data assimilation within atmospheric and oceanographic
sciences during the last couple of decades. In data assimilation, one aims at merging the …

Abstract The ensemble Kalman filter (EnKF) is a Monte Carlo-based implementation of the
Kalman filter (KF) for extremely high-dimensional, possibly nonlinear, and non-Gaussian …

It is in the previous chapters stated that the EnKF analysis scheme may have problems in
cases where the number of measurements is larger than the number of members in the …

This article provides a fundamental theoretical basis for understanding EnKF and serves as
a useful text for future users. Data assimilation and parameter-estimation problems are …

This paper considers implications of different forms of the ensemble transformation in the
ensemble square root filters (ESRFs) for the performance of ESRF-based data assimilation …

There is an established framework that describes a class of ensemble Kalman filter
algorithms as square root filters (SRFs). These algorithms produce analyses by updating a …

A Non-Gaussian Ensemble Filter Update for Data Assimilation in: Monthly Weather Review
Volume 138 Issue 11 (2010) Jump to Content Jump to Main Navigation Logo Logo Logo Logo …

Uncertainty estimation and quality control are critically missing in most geophysical
tomographic applications. The few solutions to cope with that issue are often left out in …

Many modern algorithms for inverse problems and data assimilation rely on ensemble
Kalman updates to blend prior predictions with observed data. Ensemble Kalman methods …

Full-waveform inversion (FWI) has emerged as the state-of-the art high resolution seismic
imaging technique, both in seismology for global and regional scale imaging and in the …