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Titlebook: Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II); Seon Ki Park,Liang Xu Book 2013 Springer-Verlag Berlin H

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S. Muller,R. Muñoz-Carpena,G. Kikerhe background, model forcings, and observations. An implementation of a posterior analysis method for diagnosing the error variances is described, and representative results from an atmospheric data assimilation systems are shown.
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Subhrajyoti Ghosh,Suddhasatwa Basu urban reservoirs. In this context, this chapter discusses some hydrological impact studies and presents results of a study done over the Sesan catchment in Lower Mekong Basin (in Southeast Asia). Sensitivity analysis and an optimization calibration scheme, SCE-UA algorithm, are applied to the SWAT model.
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The Adjoint Sensitivity Guidance to Diagnosis and Tuning of Error Covariance Parameters,tive results of observation impact assessment and sensitivity analysis obtained with the adjoint versions of the Naval Research Laboratory Atmospheric Variational Data Assimilation System – Accelerated Representer (NAVDAS-AR) and the Navy Operational Global Atmospheric Prediction System (NOGAPS).
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A Weak Constraint 4D-Var Assimilation System for the Navy Coastal Ocean Model Using the Representerg. Experiment results show that the assimilation system fits the data with relatively high prior errors in the initial conditions and surface forcing fluxes. However, the retrieved model forcing errors are well within the range of acceptable corrections according to an independent study.
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A Survey of Observers for Nonlinear Dynamical Systems, including Kalman filters, for nonlinear systems. We also review some fundamental concepts on the observability of systems defined by either differential equations or a numerical model. The hope is that some of these ideas will inspire research that can benefit the area of data assimilation.
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