Data Assimilation for Atmospheric, Oceanic and Hydrologic Ap, Park Seon K

Автор: Seon Ki Park; Liang Xu
Название: Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. III)
ISBN: 3319434144 ISBN-13(EAN): 9783319434148
Издательство: Springer
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Описание: Memorial Volume for Yoshi K. Sasaki

Автор: Reich
Название: Probabilistic Forecasting and Bayesian Data Assimilation
ISBN: 1107069394 ISBN-13(EAN): 9781107069398
Издательство: Cambridge Academ
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Описание: This book focuses on the Bayesian approach to data assimilation, outlining the subject`s key ideas and concepts, and explaining how to implement specific data assimilation algorithms. It is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.

Автор: Reich
Название: Probabilistic Forecasting and Bayesian Data Assimilation
ISBN: 1107663911 ISBN-13(EAN): 9781107663916
Издательство: Cambridge Academ
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Цена: 7445.00 р.
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Описание: This book focuses on the Bayesian approach to data assimilation, outlining the subject`s key ideas and concepts, and explaining how to implement specific data assimilation algorithms. It is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.

Автор: L. Bengtsson; M. Ghil; E. K?llen
Название: Dynamic Meteorology: Data Assimilation Methods
ISBN: 0387906320 ISBN-13(EAN): 9780387906324
Издательство: Springer
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Цена: 15672.00 р.
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Автор: SEON KI PARK; Liang Xu
Название: Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications
ISBN: 3642090095 ISBN-13(EAN): 9783642090097
Издательство: Springer
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Цена: 18284.00 р.
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Описание: This book presents the most recent achievements in data assimilation in Geosciences, especially regarding meteorology, oceanography and hydrology. It spans both theoretical and applied aspects with various methodologies including variational and Kalman filter.

Автор: Fletcher, Steven James
Название: Data Assimilation for the Geosciences
ISBN: 0128044446 ISBN-13(EAN): 9780128044445
Издательство: Elsevier Science
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Описание: Data Assimilation for the Geosciences: From Theory to Application brings together all of the mathematical,statistical, and probability background knowledge needed to formulate data assimilation systems in one place. It includes practical exercises for understanding theoretical formulation and presents some aspects of coding the theory with a toy problem. The book also demonstrates how data assimilation systems are implemented in larger scale fluid dynamical problems related to the atmosphere, oceans, as well as the land surface and other geophysical situations. It offers a comprehensive presentation of the subject, from basic principles to advanced methods, such as Particle Filters and Markov-Chain Monte-Carlo methods. Additionally, Data Assimilation for the Geosciences: From Theory to Application covers the applications of data assimilation techniques in various disciplines of the geosciences, making the book useful to students, teachers, and research scientists.

Автор: Pierre P. Brasseur; Jacques C.J. Nihoul
Название: Data Assimilation
ISBN: 3642789412 ISBN-13(EAN): 9783642789410
Издательство: Springer
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Цена: 18284.00 р.
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Описание: Proceedings of the NATO Advanced Research Workshop on Data Assimilation:Tools for Modelling the Ocean in a Global Change Perspective, held in Liege Belgium, May 1993

Автор: William Lahoz; Boris Khattatov; Richard Menard
Название: Data Assimilation
ISBN: 364242273X ISBN-13(EAN): 9783642422737
Издательство: Springer
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Цена: 23508.00 р.
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Описание: In recent years data assimilation methods have been applied to an increasing range of earth science disciplines. This book sets out the theoretical basis of data assimilation with contributions by top international experts in the field.

Автор: Geir Evensen
Название: Data Assimilation
ISBN: 3642424767 ISBN-13(EAN): 9783642424762
Издательство: Springer
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Цена: 26120.00 р.
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Описание: This book reviews popular data-assimilation methods, such as weak and strong constraint variational methods, ensemble filters and smoothers.