Overview

Data assimilation is considered a key component of numerical ocean model development and new data acquisition strategies. The basic concept of data assimilation is to combine real observations via estimation theory with dynamic models. Related methodologies exist in meteorology, geophysics and engineering. Of growing importance in physical oceanography, data assimilation can also be exploited in biological and chemical oceanography. Such techniques are now recognized as essential to understand the role of the ocean in a global change perspective. The book focuses on data processing algorithms for assimilation, current methods for the assimilation of biogeochemical data, strategy of model development, and the design of observational data for assimilation.

Full Product Details

Author:   Pierre P. Brasseur ,  Jacques C.J. Nihoul
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of the original 1st ed. 1994
Volume:   19
Dimensions:   Width: 15.50cm , Height: 1.40cm , Length: 23.50cm
Weight:   0.411kg
ISBN:  

9783642789410

ISBN 10:   3642789412
Pages:   253
Publication Date:   13 December 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Dynamics and Data Assimilation in Oceanography.- Assimilation of Sea Surface Temperature Data in a Numerical Ocean Circulation Model. A Study of the Water Mass Formation.- A Sensitivity Analysis of Variational Data Assimilation.- Optimal Interpolation in a model of the Azores Current in 1986–88.- Mathematical Visualisation of the Northern Bering Sea’s Summer Ecohydrodynamics.- The Northern Levantine Sea Circulation Based on Combined Analyses of CTD and ADCP DATA.- Extended Kalman Filtering for Vortex Systems: An Example of Observing-System Design.- Perspectives on Advanced Data Assimilation in Strongly Nonlinear Systems.- Using Adjoint Models for Stability and Predictability Analysis.

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