Data assimilation using a climatologically augmented local ensemble transform Kalman filter
Ensemble data assimilation methods are potentially attractive because they provide a computationally affordable (and computationally parallel) means of obtaining flow-dependent background-error statistics. However, a limitation of these methods is that the rank of their flow-dependent background-err...
Main Authors: | Matthew Kretschmer, Brian R. Hunt, Edward Ott |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2015-05-01
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Series: | Tellus: Series A, Dynamic Meteorology and Oceanography |
Subjects: | |
Online Access: | http://www.tellusa.net/index.php/tellusa/article/view/26617/pdf_34 |
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