We commonly refer to state estimation theory in geosciences as data assimilation (DA). This
term encompasses the entire sequence of operations that, starting from the observations of a …

Abstract The Twentieth Century Reanalysis (20CR) project is an international effort to
produce a comprehensive global atmospheric circulation dataset spanning the twentieth …

We present a detailed description of TOPAZ4, the latest version of TOPAZ–a coupled ocean-
sea ice data assimilation system for the North Atlantic Ocean and Arctic. It is the only …

A new algorithm for classification of sea ice types on Sentinel-1 Synthetic Aperture Radar
(SAR) data using a convolutional neural network (CNN) is presented. The CNN is trained on …

Abstract The ensemble Kalman filter (EnKF) is a sequential data assimilation method that
has been demonstrated to be effective for history matching reservoir production data and …

The study considers an iterative formulation of the ensemble Kalman filter (EnKF) for
strongly nonlinear systems in the perfect-model framework. In the first part, a scheme is …

A GSI-based data assimilation (DA) system, including three-dimensional variational
assimilation (3DVar) and ensemble Kalman filter (EnKF), is extended to the multiscale …

Monitoring stations have been used for decades to properly measure hydrological variables
and better predict floods. To this end, methods to incorporate these observations into …

Inverse problems are common and important in many applications in computational physics
but are inherently ill-posed with many possible model parameters resulting in satisfactory …

For flood simulation in humid catchments, utilizing discharge observations to update the
states of hydrological models may enhance performance. Asynchronous Ensemble Kalman …