Forecast Error Correction using Dynamic Data Assimilation

di Sivaramakrishnan Lakshmivarahan (Autore)

John M. Lewis (Autore)

Rafal Jabrzemski (Autore)

Springer International Publishing AG, 2016

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.        

• Autore: Sivaramakrishnan Lakshmivarahan, John M. Lewis, Rafal Jabrzemski
• Editore: Springer International Publishing AG
• Collana: Springer Atmospheric Sciences
• Anno: 2016
• Rilegatura: Hardback
• Pagine: 270 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783319399959

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