Ensemble data assimilation methods for estimating fault slip and future earthquake occurrences

In this dissertation, I explore ensemble data assimilation methods to enhance our capability to forecast earthquakes and slow slip events, focusing on the critical challenge posed by limited information on the current stress state of faults. <br/>At the outset, the research acknowledges the inherent limitations in our current understanding of...

An efficient ensemble Kalman Filter implementation via shrinkage covariance matrix estimation: exploiting prior knowledge

In this paper, we propose an efficient and practical implementation of the ensemble Kalman filter via shrinkage covariance matrix estimation. Our filter implementation combines information brought by an ensemble of model realizations, and that based on our prior knowledge about the dynamical system of interest. We perform the combination of...