… forecast bias by means of data assimilation, based on an … , in the context of suboptimal
data-assimilation methods which are … based on previously produced assimilated-data sets can be …

… Weak-constraint variational methods offer a great deal of flexibility in configuring a data
assimilation system to account for the presence of model errors. All such methods introduce …

… Courtier, P., 1993: Introduction to numerical weather prediction data assimilation methods.
Proc. … of analysis and forecast errors in variational data assimilation. ECMWF Tech. Memo. …

… This process is known as data assimilation. Data assimilation is a very computationally …
This paper proposes a novel method to reduce the computational cost of data assimilation: …

This work explores the potential of online parameter estimation as a technique for model
error treatment under an imperfect model scenario, in an ensemble-based data assimilation …

… : Chemical data assimilation is the process by which models use measurements to produce
… data assimilation. We discuss the Bayesian framework for developing data assimilation …

… with observational bias in hydrological data assimilation for both state updating and pa- …
The novelty of the study lies in the focus on data assimilation bias estimation in a complex, …

… Data assimilation is the application of Bayes' theorem to … , we cannot expect that data
assimilation will preserve all of the … , observations, and evaluation data in a way that allows us to …

… -art data assimilation systems with unprecedented ease. A basic data assimilation system for
… Adaptive inflation facilitates the use of ensemble data assimilation in the presence of errors …

… thinking that underpins the approach taken to data assimilation in this book. Chapter 2 sets
up the problem of data assimilation, based on an underlying stochastic dynamical system in …