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Data Assimilation: Mathematical Concepts and Instructive Examples

  • Rodolfo Guzzi

Part of the SpringerBriefs in Earth Sciences book series (BRIEFSEARTH)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Rodolfo Guzzi
    Pages 19-37
  3. Rodolfo Guzzi
    Pages 39-59
  4. Rodolfo Guzzi
    Pages 61-87
  5. Rodolfo Guzzi
    Pages 89-122
  6. Back Matter
    Pages 123-135

About this book

Introduction

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.

Keywords

3DDA 4DDA Biology and Data Assimilation Cost Function and Data Assimilation Data Assimilation and Applications Data Model Building Inverse Problems and Applications NWP Numerical Weather Prediction Robotics and Data Assimilation Statistical Estimation Weather Forecast and Data Assimilation kalman Filter and Stochastical Modeling

Authors and affiliations

  • Rodolfo Guzzi
    • 1
  1. 1.System Biology GroupUniversity La SapienzaRomeItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-22410-7
  • Copyright Information The Author(s) 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-22409-1
  • Online ISBN 978-3-319-22410-7
  • Series Print ISSN 2191-5369
  • Series Online ISSN 2191-5377
  • Buy this book on publisher's site
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