Efficient Formulation and Implementation of Data Assimilation Methods

Efficient Formulation and Implementation of Data Assimilation Methods

This Special Issue presents efficient formulations and implementations of sequential and variational data assimilation methods. The methods address three important issues in the context of operational data assimilation: efficient implementation of localization methods, sampling methods for approachi...

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Bibliographic Details
Main Authors: Elias D. Nino-Ruiz, Adrian Sandu, Haiyan Cheng
Format: Article
Language:English
Published: MDPI AG 2018-07-01
Series:Atmosphere
Subjects:
ensemble Kalman filter
posterior ensemble
modified Cholesky decomposition
sampling methods
empirical orthogonal functions
Gaussian mixture models
Online Access:http://www.mdpi.com/2073-4433/9/7/254
Description
Summary:This Special Issue presents efficient formulations and implementations of sequential and variational data assimilation methods. The methods address three important issues in the context of operational data assimilation: efficient implementation of localization methods, sampling methods for approaching posterior ensembles under non-linear model errors, and adjoint-free formulations of four dimensional variational methods.
ISSN:2073-4433

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