Guzzi Data Assimilation: Mathematical Concepts and Instructive Examples
1. Auflage 2016
ISBN: 978-3-319-22410-7
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 135 Seiten, eBook
Reihe: SpringerBriefs in Earth Sciences
ISBN: 978-3-319-22410-7
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
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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Weitere Infos & Material
Preface1 Introduction through historical perspective1.1 From Gauss to Kolmogorov1.2 Approaching the meteorological system1.3 Numerical Weather Prediction models1.4 What, Where, When 2 Representation of the physical system2.1 The observational system and errors2.2 Variational approach: 3-D VAR and 4-D VAR2.3 Assimilation as an inverse problem3 Sequential interpolation3.1 An effective introduction of a Kalman Filter3.2 More Kalman Filters 4 Advanced data assimilation methods4.1 Recursive Bayesian Estimation4.2 Ensemble Kalman Filter4.3 Issues due to small ensembles4.4 Methods to reduce problems of undersampling5 Applications5.1 Lorenz model5.2 Biology and Medicine5.3 Mars data assimilation: the General Circulation Model5.4 Earthquake forecastA AppendixA.1 Hadamard productA.2 Differential calculusA.3 The method of characteristicsA.4 Calculus of variationsA.5 The solution for the simplified equation of oceanographic circulation
