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...

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Autors principals:	Matthew Kretschmer, Brian R. Hunt, Edward Ott
Format:	Artigo
Idioma:	Inglês
Publicat:	Stockholm University Press 2015-05-01
Col·lecció:	Tellus: Series A, Dynamic Meteorology and Oceanography
Matèries:	ensemble Kalman filter climatological covariance data assimilation
Accés en línia:	http://www.tellusa.net/index.php/tellusa/article/view/26617/pdf_34
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