A Review of Innovation-Based Methods to Jointly Estimate Model and Observation Error
Covariance Matrices in Ensemble Data Assimilation in: Monthly Weather Review Volume 148 …

Abstract The Met Office Global and Regional Ensemble Prediction System–Global
(MOGREPS‐G) used an ensemble transform Kalman filter (ETKF) to perturb its initial …

This paper describes the three-dimensional variational (3D-Var) data assimilation (DA)
system for the Model for Prediction Across Scales–Atmosphere with the Joint Effort for Data …

This paper presents the formulation and preliminary results of a 3D ensemble‐variational
data assimilation algorithm (3DEnVar) for the AROME‐France model at 3.8 km horizontal …

The approach of applying different amounts of horizontal localization to different ranges of
background-error covariance horizontal scales as proposed by Buehner and Shlyaeva was …

Increasing the size of the ensemble used in hybrid‐variational assimilation methods has
been shown to be beneficial, but is computationally expensive. This work sets out to see …

The four‐dimensional ensemble‐variational (4DEnVar) formulation is a credible alternative
to the 4D‐Var formulation, especially for numerical weather prediction centres that have …

The traditional formulation of three-dimensional variational (3DVAR) data assimilation
schemes for oceanographic applications neglects the temporal evolution of background …

The European Centre for Medium‐Range Weather Forecasts has recently developed an
implicit coupling approach in the coupled atmosphere–ocean assimilation (CERA) system …

Assimilating oceanic observations into prediction systems is an advantageous approach for
real‐time ocean environment characterization. However, its benefits to underwater acoustic …