Data Assimilation with Gaussian Mixture Models using the Dynamically Orthogonal Field Equations. Part I. Theory and Scheme

This work introduces and derives an efficient, data-driven assimilation scheme, focused on a time-dependent stochastic subspace, that respects nonlinear dynamics and captures non-Gaussian statistics as it occurs. The motivation is to obtain a filter that is applicable to realistic geophysical applic...

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Bibliographic Details
Main Authors: Sondergaard, Thomas, Lermusiaux, Pierre F. J.
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering
Format: Article
Language:en_US
Published: American Meteorological Society 2013
Online Access:http://hdl.handle.net/1721.1/78912
https://orcid.org/0000-0002-1869-3883

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