Fr. 69.00

Data Assimilation and its Applications

Anglais · Livre de poche

Expédition généralement dans un délai de 1 à 2 semaines (titre imprimé sur commande)

Description

En savoir plus

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.

Table des matières

Preface.- A. General Techniques.- B. Data Assimilation with Applications to the Atmosphere.- C. Data Assimilation with Applications to Air Quality.- D. Data Assimilation with Applications to the Ocean.

Résumé

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.

Détails du produit

Collaboration Jean Pierre Issartel (Editeur), Pierre Issartel (Editeur), Pierre Issartel (Editeur), Maithil Sharan (Editeur), Maithili Sharan (Editeur)
Edition Springer, Basel
 
Langues Anglais
Format d'édition Livre de poche
Sortie 22.03.2012
 
EAN 9783034804417
ISBN 978-3-0-3480441-7
Pages 286
Dimensions 191 mm x 16 mm x 260 mm
Poids 618 g
Illustrations VI, 286 p.
Thèmes Pageoph Topical Volumes
Pageoph Topical Volumes
Catégories Sciences naturelles, médecine, informatique, technique > Sciences de la Terre > Autres

B, Statistics, Geophysics, environmental science, engineering & technology, Earth and Environmental Science, Geophysics and Environmental Physics, Solid Earth Sciences, Earth System Sciences, Probability & statistics, Environmental Sciences, Atmospheric Sciences, Environmental Science and Engineering

Commentaires des clients

Aucune analyse n'a été rédigée sur cet article pour le moment. Sois le premier à donner ton avis et aide les autres utilisateurs à prendre leur décision d'achat.

Écris un commentaire

Super ou nul ? Donne ton propre avis.

Pour les messages à CeDe.ch, veuillez utiliser le formulaire de contact.

Il faut impérativement remplir les champs de saisie marqués d'une *.

En soumettant ce formulaire, tu acceptes notre déclaration de protection des données.