Forecast error correction using dynamic data assimilation

• Main Authors: Lakshmivarahan, S., (Author), Lewis, John M., (Author), Jabrzemski, Rafal, (Author)
• Format: eBook
• Language: English
• Published: Switzerland : Springer, [2017]
• Series: Springer atmospheric sciences.
• Subjects: počítačová věda; geologie; statistické metody; fyzika atmosféry; počítačová simulace; dolování dat; computer science; geology; statistical methods; atmospheric physics; computer simulation; data mining; elektronické knihy; monografie; electronic books; monographs
• ISBN: 9783319399973; 9783319399959
• Physical Description: 1 online resource (xvi, 270 pages)
• 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

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