04252nam 22007815 450 991025501250332120251116150934.03-319-22410-710.1007/978-3-319-22410-7(CKB)3710000000476931(EBL)4178484(SSID)ssj0001584235(PQKBManifestationID)16264470(PQKBTitleCode)TC0001584235(PQKBWorkID)14865651(PQKB)10514774(DE-He213)978-3-319-22410-7(MiAaPQ)EBC4178484(PPN)190523867(EXLCZ)99371000000047693120150916d2016 u| 0engur|n|---|||||txtccrData assimilation: mathematical concepts and instructive examples /by Rodolfo Guzzi1st ed. 2016.Cham :Springer International Publishing :Imprint: Springer,2016.1 online resource (140 p.)SpringerBriefs in Earth Sciences,2191-5369Description based upon print version of record.3-319-22409-3 Includes bibliographical references at the end of each chapters and index.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.SpringerBriefs in Earth Sciences,2191-5369Computer simulationPhysical geographyMathematical physicsEnvironmental sciencesWater qualityWaterPollutionSimulation and Modelinghttps://scigraph.springernature.com/ontologies/product-market-codes/I19000Earth System Scienceshttps://scigraph.springernature.com/ontologies/product-market-codes/G35000Theoretical, Mathematical and Computational Physicshttps://scigraph.springernature.com/ontologies/product-market-codes/P19005Environmental Science and Engineeringhttps://scigraph.springernature.com/ontologies/product-market-codes/G37000Water Quality/Water Pollutionhttps://scigraph.springernature.com/ontologies/product-market-codes/212000Computer simulation.Physical geography.Mathematical physics.Environmental sciences.Water quality.WaterPollution.Simulation and Modeling.Earth System Sciences.Theoretical, Mathematical and Computational Physics.Environmental Science and Engineering.Water Quality/Water Pollution.519.5Guzzi Rodolfoauthttp://id.loc.gov/vocabulary/relators/aut32371MiAaPQMiAaPQMiAaPQBOOK9910255012503321Data Assimilation: Mathematical Concepts and Instructive Examples2007734UNINA