| 書(shū)目名稱 | Forecast Error Correction using Dynamic Data Assimilation |
| 編輯 | Sivaramakrishnan Lakshmivarahan,John M. Lewis,Rafa |
| 視頻video | http://file.papertrans.cn/346/345282/345282.mp4 |
| 概述 | Introduces the reader to a new method of dynamic data assimilation called Forward Sensitivity Method (FSM) through theory and application.The connection between the FSM and the well-known adjoint sens |
| 叢書(shū)名稱 | Springer Atmospheric Sciences |
| 圖書(shū)封面 |  |
| 描述 | 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. ? ? ? ? |
| 出版日期 | Book 2017 |
| 關(guān)鍵詞 | Adjoint Method; Adjoint Sensitivity Analysis; Data Assimilation; Dynamic Predictability; FSM; Fitting Dat |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-39997-3 |
| isbn_softcover | 978-3-319-82010-1 |
| isbn_ebook | 978-3-319-39997-3Series ISSN 2194-5217 Series E-ISSN 2194-5225 |
| issn_series | 2194-5217 |
| copyright | Springer International Publishing Switzerland 2017 |
|Archiver|手機(jī)版|小黑屋|
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