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 …

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 …

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 …

Data assimilation is an iterative approach to the problem of estimating the state of a
dynamical system using both current and past observations of the system together with a …

Numerical weather prediction models as well as the atmosphere itself can be viewed as
nonlinear dynamical systems in which the evolution depends sensitively on the initial …

We describe the development and testing of the hybrid ensemble/4D‐Var global data
assimilation system that was implemented operationally at the Met Office in July 2011, giving …

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 …

An ensemble Kalman filter–variational hybrid data assimilation system based on the
gridpoint statistical interpolation (GSI) three-dimensional variational data assimilation …

Abstract The Met Office has recently introduced a short‐range ensemble prediction system
known as MOGREPS. This system consists of global and regional ensembles, with the …

The use of perturbed observations in the traditional ensemble Kalman filter (EnKF) results in
a suboptimal filter behaviour, particularly for small ensembles. In this work, we propose a …