Forecast error correction using dynamic data assimilation

This book introduces the reader to a new method of data assimilation with deterministic constraints (exact satisfaction of dynamic constraints)?an optimal assimilation strategy called Forecast Sensitivity Method (FSM), as an alternative to the well-known four-dimensional variational (4D-Var) data as...

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Bibliographic Details
Main Authors Lakshmivarahan, S. (Author), Lewis, John M. (Author), Jabrzemski, Rafal (Author)
Format Electronic eBook
LanguageEnglish
Published Switzerland : Springer, [2017]
SeriesSpringer atmospheric sciences.
Subjects
Online AccessFull text
ISBN9783319399973
9783319399959
ISSN2194-5225
Physical Description1 online resource (xvi, 270 pages)

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Summary:This book introduces the reader to a new method of data assimilation with deterministic constraints (exact satisfaction of dynamic constraints)?an optimal assimilation strategy called Forecast Sensitivity Method (FSM), as an alternative to the well-known four-dimensional variational (4D-Var) data assimilation method. 4D-Var works with a forward in time prediction model and a backward in time tangent linear model (TLM). The equivalence of data assimilation via 4D-Var and FSM is proven and problems using low-order dynamics clarify the process of data assimilation by the two methods. The problem of return flow over the Gulf of Mexico that includes upper-air observations and realistic dynamical constraints gives the reader a good idea of how the FSM can be implemented in a real-world situation.- Resumé vydavatel
Bibliography:Includes bibliographical references (pages 259-263) and index.
ISBN:9783319399973
9783319399959
ISSN:2194-5225
Access:Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty
Physical Description:1 online resource (xvi, 270 pages)