## Abstract We apply information theory within an ensembleβbased data assimilation approach and define __information matrix in ensemble subspace__. The information matrix in ensemble subspace employs a flowβdependent forecast error covariance and it is of relatively small dimensions (equal to the e
Adaptive observations in ensemble data assimilation
β Scribed by Bahri Uzunoglu
- Publisher
- Elsevier Science
- Year
- 2007
- Tongue
- English
- Weight
- 881 KB
- Volume
- 196
- Category
- Article
- ISSN
- 0045-7825
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β¦ Synopsis
An important question in ensemble based data assimilation scheme is how to configure our observations to correctly capture the important features in either our atmospheric or oceanic models given a set of ensembles. In this paper a systematic approach for effective sensor placement is formulated to evaluate how to target our observations. This method is based on a criterion of Shannon information entropy and condition number of our ensemble subspace covariance matrix yielding adaptive observation configurations. The theory behind this method is presented as well as an example illustrated with a global shallow water equations model on the sphere.
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