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Titlebook: Data Assimilation Fundamentals; A Unified Formulatio Geir Evensen,Femke C. Vossepoel,Peter Jan van Leeu Textbook‘‘‘‘‘‘‘‘ 2022 The Editor(s)

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21#
發(fā)表于 2025-3-25 04:01:32 | 只看該作者
https://doi.org/10.1007/978-3-642-30770-6This chapter introduces the . (SC-4DVar) method. By strong constraint, we refer to the dynamical model having no model errors. Hence, the model solution over the assimilation window is entirely determined by the model as soon as we give the initial conditions.
22#
發(fā)表于 2025-3-25 08:27:42 | 只看該作者
23#
發(fā)表于 2025-3-25 11:56:45 | 只看該作者
Prenatal Diagnosis of Oral CleftsThis chapter will introduce another approximation where we represent all state error covariances using a finite ensemble of the state. This approximation allows us to search for the solution in the ensemble subspace, leading to very efficient ensemble data-assimilation methods.
24#
發(fā)表于 2025-3-25 15:48:26 | 只看該作者
Sommerlad’s Technique of Cleft Palate RepairThis chapter provides an introduction to methods that, in theory, samples precisely the posterior pdf. Commonly-used ensemble data-assimilation methods, like the EnKF and EnRML, only sample the posterior pdf correctly in the Gauss-linear case and typically fail in cases with strong nonlinearity.
25#
發(fā)表于 2025-3-25 22:26:58 | 只看該作者
26#
發(fā)表于 2025-3-26 00:42:10 | 只看該作者
27#
發(fā)表于 2025-3-26 07:23:02 | 只看該作者
28#
發(fā)表于 2025-3-26 11:36:35 | 只看該作者
Die Kunden, die unbekannten Wesen!Eknes and Evensen (1997) solved the weak-constraint variational problem for a linear Ekman-flow model using the representer method. They computed the weak constraint solution for a long time series of velocity measurements. Additionally, they considered a parameter-estimation problem which rendered the problem nonlinear.
29#
發(fā)表于 2025-3-26 14:13:36 | 只看該作者
30#
發(fā)表于 2025-3-26 20:22:40 | 只看該作者
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