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A penalized four-dimensional variational data assimilation method for reducing forecast error related to adaptive observations

Hossen, Jakir; Navon, I. M.; Fang, F.


Four-dimensional variational (4D-Var) data assimilation method is used to find the optimal initial conditions by minimizing a cost function in which background information and observations are provided as the input of the cost function. The optimized initial conditions based on background error covariance matrix and observations improve the forecast. The targeted observations determined by using methods such as adjoint sensitivity, observation sensitivity, or singular vectors may further...[Show more]

CollectionsANU Research Publications
Date published: 2012
Type: Journal article
Source: International Journal for Numerical Methods in Fluids
DOI: 10.1002/fld.2736


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