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03398nam a22005655i 4500 |
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|a 9783319399973
|9 978-3-319-39997-3
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|a 10.1007/978-3-319-39997-3
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|a 006.312
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|a Lakshmivarahan, Sivaramakrishnan.
|e author.
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|a Forecast Error Correction using Dynamic Data Assimilation
|h [electronic resource] /
|c by Sivaramakrishnan Lakshmivarahan, John M. Lewis, Rafal Jabrzemski.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2017.
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|a XVI, 270 p. 125 illus., 104 illus. in color.
|b online resource.
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|a text
|b txt
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|a computer
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|a online resource
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|a text file
|b PDF
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|a Springer Atmospheric Sciences,
|x 2194-5217
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|a 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. .
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|a 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. .
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|a Computer science.
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|a Geology
|x Statistical methods.
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|a Atmospheric sciences.
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|a Computers.
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|a Data mining.
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|a Computer simulation.
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|a Computer Science.
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|a Data Mining and Knowledge Discovery.
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|a Simulation and Modeling.
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|a Models and Principles.
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|a Atmospheric Sciences.
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|a Quantitative Geology.
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|a Lewis, John M.
|e author.
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|a Jabrzemski, Rafal.
|e author.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783319399959
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|a Springer Atmospheric Sciences,
|x 2194-5217
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|u http://dx.doi.org/10.1007/978-3-319-39997-3
|z Full Text via HEAL-Link
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|a ZDB-2-EES
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|a Earth and Environmental Science (Springer-11646)
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