منابع مشابه
The behaviour of 4D-Var for a highly nonlinear system
To forecast the future state of the atmosphere, data assimilation is required in order to provide a good estimate of the initial conditions, combining observations and model predictions. To meet current operational limitations the incremental approach is being implemented to reduce the computational cost of four-dimensional variational assimilation (4D-Var) which assumes that processes are clos...
متن کاملReduced-order 4D-Var: a preconditioner for the Incremental 4D-Var data assimilation method
This study demonstrates how the incremental 4D-Var data assimilation method can be applied efficiently preconditioned in an application to an oceanographic problem. The approach consists in performing a few iterations of the reduced-order 4D-Var prior to the incremental 4D-Var in the full space in order to achieve faster convergence. An application performed in the tropical Pacific Ocean, with ...
متن کاملDiscussion on ‘4D-Var or EnKF?’
The development of data assimilation techniques for numerical weather prediction has been very successful ever since the early 1950s until now, starting with simple two-dimensional and univariate spatial interpolation techniques like the successive corrections (SC, Bergthorsson and Döös, 1955) ending up with the four-dimensional variational data assimilation (4D-Var, Rabier et al., 2000) and en...
متن کاملEfficient Computation of Observation Impact in 4D-Var Data Assimilation
Data assimilation combines information from an imperfect model, sparse and noisy observations, and error statistics, to produce a best estimate of the state of a physical system. Different observational data points have different contributions to reducing the uncertainty with which the state is estimated. Quantifying the observation impact is important for analyzing the effectiveness of the ass...
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ژورنال
عنوان ژورنال: Nonlinear Processes in Geophysics
سال: 2018
ISSN: 1607-7946
DOI: 10.5194/npg-25-713-2018