Articles liés à Data Assimilation and its Applications
Synopsis
Data assimilation is a novel, versatile methodology for estimating atmospheric and oceanic variables. The estimation of a quantity of interest via data assimilation involves the combination of observational data with the underlying dynamical principles governing the system under observation.
This volume contains many original findings in data assimilation and its applications related to atmospheric, oceanic and environmental systems. This covers various data assimilation techniques with in Bayesian and non-Bayesian framework ranging from Least-Square, nudging, three dimensional variational (3DVAR), four-dimensional variational (4DVAR), Local Ensemble Kalman filter, Genetic algorithm etc. This also covers the applications to extreme weather event, hurricane, Asian summer monsoon, structure of the barrier layer in the equatorial Pacific ocean and identification of emission sources.
This volume will be useful as a reading material in graduate level courses dealing with data assimilation and its application to meteorology, ocean and air quality. The scientific community at large especially younger scientists will find this book a useful addition to their personal and institutional libraries.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Présentation de l'éditeur
Data assimilation is a novel, versatile methodology for estimating atmospheric and oceanic variables. The estimation of a quantity of interest via data assimilation involves the combination of observational data with the underlying dynamical principles governing the system under observation. This volume contains many original findings in data assimilation and its applications related to atmospheric, oceanic and environmental systems. This covers various data assimilation techniques with in Bayesian and non-Bayesian framework ranging from Least-Square, nudging, three dimensional variational (3DVAR), four-dimensional variational (4DVAR), Local Ensemble Kalman filter, Genetic algorithm etc. This also covers the applications to extreme weather event, hurricane, Asian summer monsoon, structure of the barrier layer in the equatorial Pacific ocean and identification of emission sources. This volume will be useful as a reading material in graduate level courses dealing with data assimilation and its application to meteorology, ocean and air quality. The scientific community at large especially younger scientists will find this book a useful addition to their personal and institutional libraries.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurBirkhäuser
- Date d'édition2012
- ISBN 10 3034804415
- ISBN 13 9783034804417
- ReliureBroché
- Langueanglais
- Nombre de pages292
- ÉditeurSharan Maithili, Issartel Jean Pierre
- Coordonnées du fabricantnon disponible
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Data Assimilation and its Applications
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Springer Basel, 2012
ISBN 10 : 3034804415
ISBN 13 : 9783034804417
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Data Assimilation and its Applications
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents an up-to-date and versatile methodologyContains many original findings for atmospheric, oceanic and environmental systems Suitable researchers as well as for graduate level coursesData assimilation is a nov. N° de réf. du vendeur 4318245
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Data Assimilation and its Applications
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Data assimilation is a novel, versatile methodology for estimating atmospheric and oceanic variables. The estimation of a quantity of interest via data assimilation involves the combination of observational data with the underlying dynamical principles governing the system under observation. This volume contains many original findings in data assimilation and its applications related to atmospheric, oceanic and environmental systems. This covers various data assimilation techniques with in Bayesian and non-Bayesian framework ranging from Least-Square, nudging, three dimensional variational (3DVAR), four-dimensional variational (4DVAR), Local Ensemble Kalman filter, Genetic algorithm etc. This also covers the applications to extreme weather event, hurricane, Asian summer monsoon, structure of the barrier layer in the equatorial Pacific ocean and identification of emission sources. This volume will be useful as a reading material in graduate level courses dealing with data assimilation and its application to meteorology, ocean and air quality. The scientific community at large especially younger scientists will find this book a useful addition to their personal and institutional libraries. N° de réf. du vendeur 9783034804417
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Data Assimilation and its Applications
Edité par
Springer Basel Mai 2012, 2012
ISBN 10 : 3034804415
ISBN 13 : 9783034804417
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data assimilation is a novel, versatile methodology for estimating atmospheric and oceanic variables. The estimation of a quantity of interest via data assimilation involves the combination of observational data with the underlying dynamical principles governing the system under observation. This volume contains many original findings in data assimilation and its applications related to atmospheric, oceanic and environmental systems. This covers various data assimilation techniques with in Bayesian and non-Bayesian framework ranging from Least-Square, nudging, three dimensional variational (3DVAR), four-dimensional variational (4DVAR), Local Ensemble Kalman filter, Genetic algorithm etc. This also covers the applications to extreme weather event, hurricane, Asian summer monsoon, structure of the barrier layer in the equatorial Pacific ocean and identification of emission sources. This volume will be useful as a reading material in graduate level courses dealing with data assimilation and its application to meteorology, ocean and air quality. The scientific community at large especially younger scientists will find this book a useful addition to their personal and institutional libraries. 292 pp. Englisch. N° de réf. du vendeur 9783034804417
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Data Assimilation and its Applications
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Springer Basel, Birkhäuser Basel Mai 2012, 2012
ISBN 10 : 3034804415
ISBN 13 : 9783034804417
Neuf
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. Neuware -Data assimilation is a novel, versatile methodology for estimating atmospheric and oceanic variables. The estimation of a quantity of interest via data assimilation involves the combination of observational data with the underlying dynamical principles governing the system under observation.This volume contains many original findings in data assimilation and its applications related to atmospheric, oceanic and environmental systems. This covers various data assimilation techniques with in Bayesian and non-Bayesian framework ranging from Least-Square, nudging, three dimensional variational (3DVAR), four-dimensional variational (4DVAR), Local Ensemble Kalman filter, Genetic algorithm etc. This also covers the applications to extreme weather event, hurricane, Asian summer monsoon, structure of the barrier layer in the equatorial Pacific ocean and identification of emission sources.This volume will be useful as a reading material in graduate level courses dealing with data assimilation and its application to meteorology, ocean and air quality. The scientific community at large especially younger scientists will find this book a useful addition to their personal and institutional libraries.Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 292 pp. Englisch. N° de réf. du vendeur 9783034804417
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Data Assimilation and Its Applications
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Data Assimilation and Its Applications
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Data Assimilation and Its Applications
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Paperback. Etat : Brand New. 2012 edition. 676 pages. 10.24x7.60x0.69 inches. In Stock. N° de réf. du vendeur 3034804415
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