Data Assimilation
Improved variational methods in statistical data assimilation
... in data assimilation, focus on the role of the number of measurements one requires for accuracy in that approxi- mation, and permit the evaluation of systematic corrections to the approximation when the ...
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Streamflow data assimilation for soil moisture analysis
... measured data is ...streamflow data assimilation should not be expected to be a suitable tool for soil moisture analysis in a land sur- face model like ...
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Lagrangian data assimilation into layered ocean model
... Lagrangian data assimilation methods for the systematic development of ocean circulation models and the assimilation of Lagrangian data in ocean models in support of the ocean modeling and ...
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Evaluation of Physical Education Multimedia Teaching for Data Assimilation
... data assimilation, we consider the characterization of the sample and the difference between the ...Therefore, data assimilation can greatly reduce the consumption of computer storage and ...
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A material balancing scheme for ocean colour data assimilation
... an assimilation system in isolation, avoiding the need to address all problems ...real-world data in the test-bed would be desirable but would require the test bed’s emulation of the 3-D model to be ...
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Simplified aerosol modeling for variational data assimilation
... In this paper we present a simplified aerosol model that simulates AOD from emission fluxes of the main aerosol species and gaseous precursors. The model has been de- signed with the aim to estimate the intensity of the ...
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Trends on Major Actinides from an Integral Data Assimilation
... Abstract: Nuclear data evaluations on major actinides can be improved by integral data assimilation. Appropriate integral measurements with reliable experimental techniques have been selected such as ...
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Influence of proxy data uncertainty on data assimilation for the past climate
... 2013). Data assimilation (DA) combines empirical information from proxy data with numerical simulations to obtain the best climate state esti- mates, aiming to capture both the forced and internal ...
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A defensive marginal particle filtering method for data assimilation
... speaking, data assimilation is to estimate the optimal prediction based on both the output of the mathematical model, which is only an approximation of the real-world system, and the observations that are ...
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Synchronicity in predictive modelling: a new view of data assimilation
... of data assimilation can be viewed as one of synchronizing two dynamical systems, one repre- senting “truth” and the other representing “model”, with a unidirectional flow of information between the ...of ...
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The impact of nonlinearity in Lagrangian data assimilation
... that assimilation of such trajectory data may lead to the divergence of EnKF – the so-called saddle effect (Kuznetsov et ...Lagrangian data assimilation problem have not yet given sufficient ...
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NAME Modeling and Data Assimilation: a strategic overview
... ways data assimilation provides one of the most direct ways of addressing model ...climate data assimilation is that a model forced (via data insertion) to remain close to the observed ...
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COSMO Data Assimilation. Applications for Romanian Territory
... The COSMO model is run operationally in the National Meteorological Administration since 2005, on a domain which covers the Romanian territory with 201 × 177 grid points for 7km horizontal resolution and 361 × 291 grid ...
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Representing model error in ensemble data assimilation
... Abstract. The paper investigates a method to represent model error in the ensemble data assimilation (EDA) sys- tem. The ECMWF operational EDA simulates the effect of both observations and model ...
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Complexity Computational Environment: Data Assimilation SERVOGrid
... the data, as well as to interpret the observed measurements in terms of that ...space-time data, and 2) analyze the scale dependence of the governing dynamical equations, with a view towards developing a ...
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On deterministic error analysis in variational data assimilation
... The purpose of this paper is to analyze the impact of errors on the prediction in order to provide some information on the improvement of prediction. This is a new statement in comparison with the former paper by Le ...
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Model error estimation in ensemble data assimilation
... Like (Dee and Da Silva, 1998; Dee and Todling, 2000), this paper addresses the problem of additive model error es- timation and correction in data assimilation. Based on the optimal linear filters of ...
13
pygeodyn 1.1.0: a Python package for geomagnetic data assimilation
... netic data assimilation tool written in ...flexible data assimila- tion ...embedded data and priors or to supply custom ones; tunable parameters through configuration files; and adapted ...
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Merging particle filter for sequential data assimilation
... sequential data assimilation with acceptable computational cost, except some methods such as the EnKF and the SEIK filter which also have a disadvantage in that it is not necessarily appli- cable to cases ...
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On analysis error covariances in variational data assimilation
... The paper is organized as follows. In Sect.2, we provide the statement of the vari- ational DA problem for a nonlinear evolution model to identify the initial condition. In Sect.3, the equation of the analysis error is ...
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