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Forecast Error Correction using Dynamic Data Assimilation (Springer Atmospheric Sciences)

Posted By: Rare-1
Date: 25 Oct 2016 12:09:09
Forecast Error Correction using Dynamic Data Assimilation (Springer Atmospheric Sciences)

Forecast Error Correction using Dynamic Data Assimilation (Springer Atmospheric Sciences) by Sivaramakrishnan Lakshmivarahan, John M. Lewis, Rafal Jabrzemski
English | ISBN: 3319399950 | 2017 | PDF | 270 pages | 7.25 MB


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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