Forecast Error Correction using Dynamic Data Assimilation

• Κύριοι συγγραφείς: Lakshmivarahan, Sivaramakrishnan (Συγγραφέας), Lewis, John M. (Συγγραφέας), Jabrzemski, Rafal (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Σειρά: Springer Atmospheric Sciences,
• Θέματα: Computer science.; Geology > Statistical methods.; Atmospheric sciences.; Computers.; Data mining.; Computer simulation.; Computer Science.; Data Mining and Knowledge Discovery.; Simulation and Modeling.; Models and Principles.; Atmospheric Sciences.; Quantitative Geology.

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...

Πίνακας περιεχομένων:

• 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. .