Sequential Data Assimilation Techniques for Data Assimilation

Abstract

The time-variable terrestrial water storage (TWS) products from the Gravity Recovery And Climate Experiment (GRACE) have been increasingly used in recent years to improve the simulation of hydrological models by applying data assimilation techniques. In this study, we assess the performance of established sequential data assimilation techniques for integrating GRACE TWS into the World-Wide Water Resources Assessment (W3RA) model. We implement six versions of the classical ensemble Kalman filters (EnKF), as well as Particle filters.