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Forecast error correction using dynamic data assimilation

Author: S Lakshmivarahan; John M Lewis; Rafal Jabrzemski
Publisher: Switzerland : Springer, [2017]
Series: Springer atmospheric sciences.
Edition/Format:   eBook : Document : EnglishView all editions and formats
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Forecast Error Correction Using Dynamic Data Assimilation.
[Place of publication not identified] : Springer-Verlag New York Inc 2016
(OCoLC)950953198
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: S Lakshmivarahan; John M Lewis; Rafal Jabrzemski
ISBN: 9783319399973 3319399977
OCLC Number: 961185277
Description: 1 online resource (xvi, 270 pages).
Contents: Part I Theory --
Introduction --
Dynamics of evolution of first- and second-order forward sensitivity: discrete time and continuous time --
Estimation of control errors using forward sensitivities: FSM with single and multiple observations --
Relation to adjoint sensitivity and impact of observation --
Estimation of model errors using Pontryagin?s Maximum Principle- its relation to 4-D VAR and hence FSM --
FSM and predictability --
Lyapunov index --
Part II Applications --
Mixed-layer model --
the Gulf of Mexico problem --
Lagrangian data assimilation --
Conclusions --
Appendix --
Index.
Series Title: Springer atmospheric sciences.
Responsibility: Sivaramakrishnan Lakshmivarahan, John M. Lewis, Rafal Jabrzemski.

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