Variational and ensemble methods have been developed separately by various research
and development groups and each brings its own benefits to data assimilation. In the last …

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 …

This tutorial provides a broad introduction to Bayesian data assimilation that will be useful to
practitioners, in interpreting algorithms and results, and for theoretical studies developing …

This article provides a detailed theoretical analysis of methods to approximate the solutions
of high‐dimensional (> 106) linear Bayesian problems. An optimal low‐rank projection that …

Developing effective ways to model and cycle the background‐error covariance matrix is an
active area of research in data assimilation. An important aspect of this problem when using …

Hybrid variational–ensemble data assimilation (hybrid DA) is widely used in research and
operational systems, and it is considered the current state of the art for the initialization of …

Integrating the hybrid and multiscale analyses and the parallel computation is necessary for
current data assimilation schemes. A local data assimilation method, Local DA, is designed …

Factorization of a background error covariance matrix (B factorization) constructed from
localization matrices and a small ensemble that obeys background error statistics is an …

On Cost Functions in the Hybrid Variational–Ensemble Method in: Monthly Weather Review
Volume 145 Issue 6 (2017) Jump to Content Jump to Main Navigation Logo Logo Logo Logo …

L'initialisation des hydrométéores est un enjeu majeur de la prévision numérique du temps
à échelle convective. Cette thèse vise à analyser ces hydrométéores dans le schéma …