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.
| ISBN: | 9783319399959 |
| Publication date: | 2nd November 2016 |
| Author: | Sivaramakrishnan Lakshmivarahan, John M Lewis, Rafal Jabrzemski |
| Publisher: | Springer an imprint of Springer International Publishing |
| Format: | Hardback |
| Pagination: | 270 pages |
| Series: | Springer Atmospheric Sciences |
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.
Hardback. Not Available.
Forecast Error Correction Using Dynamic Data Assimilation was written by Sivaramakrishnan Lakshmivarahan, John M Lewis, Rafal Jabrzemski and published by Springer an imprint of Springer International Publishing
Forecast Error Correction Using Dynamic Data Assimilation has 270 pages
Yes it is part of Springer Atmospheric Sciences series