Data assimilation: methods, algorithms, and applications

Mark Asch 1 Marc Bocquet 2 Maëlle Nodet 3
3 AIRSEA - Mathematics and computing applied to oceanic and atmospheric flows
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, UJF - Université Joseph Fourier - Grenoble 1, INPG - Institut National Polytechnique de Grenoble
Abstract : Data assimilation is an approach that combines observations and model output, with the objective of improving the latter. This book places data assimilation into the broader context of inverse problems and the theory, methods, and algorithms that are used for their solution. It provides a framework for, and insight into, the inverse problem nature of data assimilation, emphasizing “why” and not just “how.” Methods and diagnostics are emphasized, enabling readers to readily apply them to their own field of study.
Readers will find
  • a comprehensive guide that is accessible to nonexperts;
  • numerous examples and diverse applications from a broad range of domains, including geophysics and geophysical flows, environmental acoustics, medical imaging, mechanical and biomedical engineering, economics and finance, and traffic control and urban planning;
  • and the latest methods for advanced data assimilation, combining variational and statistical approaches.
Type de document :
Ouvrage (y compris édition critique et traduction)
SIAM, pp.xviii + 306, 2016, Fundamentals of Algorithms, 978-1-611974-53-9
Liste complète des métadonnées

https://hal.inria.fr/hal-01402885
Contributeur : Maëlle Nodet <>
Soumis le : vendredi 25 novembre 2016 - 11:51:59
Dernière modification le : mercredi 11 avril 2018 - 01:50:55

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  • HAL Id : hal-01402885, version 1

Citation

Mark Asch, Marc Bocquet, Maëlle Nodet. Data assimilation: methods, algorithms, and applications. SIAM, pp.xviii + 306, 2016, Fundamentals of Algorithms, 978-1-611974-53-9. 〈hal-01402885〉

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