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Data Assimilation: Mathematical Concepts and Instructive Examples [electronic resource] / by Rodolfo Guzzi.

By: Guzzi, Rodolfo [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Earth Sciences: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: VIII, 135 p. 4 illus., 1 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319224107.Subject(s): Computer science | Water quality | Water pollution | Physical geography | Environmental sciences | Computer simulation | Physics | Computer Science | Simulation and Modeling | Earth System Sciences | Theoretical, Mathematical and Computational Physics | Environmental Science and Engineering | Water Quality/Water PollutionAdditional physical formats: Printed edition:: No titleDDC classification: 003.3 Online resources: Click here to access online
Contents:
Preface -- 1. Introduction through historical perspective -- 2. Representation of the physical system -- 3. Sequential interpolation -- 4. Advanced data assimilation methods -- 5. Applications -- A. Appendix.
In: Springer eBooksSummary: This book endeavours to give a concise contribution to understanding the data assimilation and related methodologies. The mathematical concepts and related algorithms are fully presented, especially for those facing this theme for the first time.  The first chapter gives a wide overview of the data assimilation steps starting from Gauss' first methods to the most recent as those developed under the Monte Carlo methods.  The second chapter treats the representation of the physical  system as an ontological basis of the problem. The third chapter deals with the classical Kalman filter, while the fourth chapter deals with the advanced methods based on  recursive Bayesian Estimation. A special chapter, the fifth, deals with the possible applications, from the first Lorenz model, passing trough the biology and medicine up to planetary assimilation, mainly on Mars. This book serves both teachers and college students, and other interested parties providing the algorithms and formulas to manage the data assimilation everywhere a dynamic system is present.
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Preface -- 1. Introduction through historical perspective -- 2. Representation of the physical system -- 3. Sequential interpolation -- 4. Advanced data assimilation methods -- 5. Applications -- A. Appendix.

This book endeavours to give a concise contribution to understanding the data assimilation and related methodologies. The mathematical concepts and related algorithms are fully presented, especially for those facing this theme for the first time.  The first chapter gives a wide overview of the data assimilation steps starting from Gauss' first methods to the most recent as those developed under the Monte Carlo methods.  The second chapter treats the representation of the physical  system as an ontological basis of the problem. The third chapter deals with the classical Kalman filter, while the fourth chapter deals with the advanced methods based on  recursive Bayesian Estimation. A special chapter, the fifth, deals with the possible applications, from the first Lorenz model, passing trough the biology and medicine up to planetary assimilation, mainly on Mars. This book serves both teachers and college students, and other interested parties providing the algorithms and formulas to manage the data assimilation everywhere a dynamic system is present.

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