000777615 000__ 03453cam\a2200493Ii\4500 000777615 001__ 777615 000777615 005__ 20230306142725.0 000777615 006__ m\\\\\o\\d\\\\\\\\ 000777615 007__ cr\nn\nnnunnun 000777615 008__ 161025s2017\\\\sz\\\\\\ob\\\\001\0\eng\d 000777615 019__ $$a961207206$$a962258283$$a965347152$$a966555787 000777615 020__ $$a9783319399973$$q(electronic book) 000777615 020__ $$a3319399977$$q(electronic book) 000777615 020__ $$z9783319399959 000777615 020__ $$z3319399950 000777615 035__ $$aSP(OCoLC)ocn961185277 000777615 035__ $$aSP(OCoLC)961185277$$z(OCoLC)961207206$$z(OCoLC)962258283$$z(OCoLC)965347152$$z(OCoLC)966555787 000777615 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dIDEBK$$dYDX$$dEBLCP$$dN$T$$dGW5XE$$dOCLCF$$dCOO$$dIDB$$dUAB$$dIOG 000777615 049__ $$aISEA 000777615 050_4 $$aQA614.8$$b.L35 2017eb 000777615 08204 $$a515/.352$$223 000777615 1001_ $$aLakshmivarahan, S.,$$eauthor. 000777615 24510 $$aForecast error correction using dynamic data assimilation /$$cSivaramakrishnan Lakshmivarahan, John M. Lewis, Rafal Jabrzemski. 000777615 264_1 $$aSwitzerland :$$bSpringer,$$c[2017] 000777615 300__ $$a1 online resource (xvi, 270 pages) 000777615 336__ $$atext$$btxt$$2rdacontent 000777615 337__ $$acomputer$$bc$$2rdamedia 000777615 338__ $$aonline resource$$bcr$$2rdacarrier 000777615 4901_ $$aSpringer atmospheric sciences,$$x2194-5225 000777615 504__ $$aIncludes bibliographical references (pages 259-263) and index. 000777615 5050_ $$aPart I Theory -- Introduction -- Dynamics of evolution of first- and second-order forward sensitivity: discrete time and continuous time -- Estimation of control errors using forward sensitivities: FSM with single and multiple observations -- Relation to adjoint sensitivity and impact of observation -- Estimation of model errors using Pontryagin?s Maximum Principle- its relation to 4-D VAR and hence FSM -- FSM and predictability -- Lyapunov index -- Part II Applications -- Mixed-layer model -- the Gulf of Mexico problem -- Lagrangian data assimilation -- Conclusions -- Appendix -- Index. . 000777615 506__ $$aAccess limited to authorized users. 000777615 520__ $$aThis book introduces the reader to a new method of data assimilation with deterministic constraints (exact satisfaction of dynamic constraints)?an optimal assimilation strategy called Forecast Sensitivity Method (FSM), as an alternative to the well-known four-dimensional variational (4D-Var) data assimilation method. 4D-Var works with a forward in time prediction model and a backward in time tangent linear model (TLM). The equivalence of data assimilation via 4D-Var and FSM is proven and problems using low-order dynamics clarify the process of data assimilation by the two methods. The problem of return flow over the Gulf of Mexico that includes upper-air observations and realistic dynamical constraints gives the reader a good idea of how the FSM can be implemented in a real-world situation. . 000777615 588__ $$aDescription based on print version record. 000777615 650_0 $$aForecasting$$xMathematical models. 000777615 650_0 $$aDifferentiable dynamical systems. 000777615 7001_ $$aLewis, John M.,$$eauthor. 000777615 7001_ $$aJabrzemski, Rafal,$$eauthor. 000777615 77608 $$iPrint version:$$tForecast Error Correction Using Dynamic Data Assimilation.$$d[Place of publication not identified] : Springer-Verlag New York Inc 2016$$z9783319399959$$w(OCoLC)950953198 000777615 830_0 $$aSpringer atmospheric sciences. 000777615 852__ $$bebk 000777615 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-39997-3$$zOnline Access$$91397441.1 000777615 909CO $$ooai:library.usi.edu:777615$$pGLOBAL_SET 000777615 980__ $$aEBOOK 000777615 980__ $$aBIB 000777615 982__ $$aEbook 000777615 983__ $$aOnline 000777615 994__ $$a92$$bISE