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dc.contributor.authorHossen, M. J.
dc.contributor.authorNavon, Ionel Michael
dc.contributor.authorDǎescu, Dacian N.
dc.identifier.citationHossen, M. J., Navon, I. M., & Daescu, D. N. (2012). Effect of random perturbations on adaptive observation techniques. International Journal for Numerical Methods in Fluids, 69(1), 110-123. doi:10.1002/fld.2545en_US
dc.descriptionhis article was published in the International Journal for Numerical Methods in Fluids [© 2011 John Wiley & Sons, Ltd.] and the definite version is available at : The Journal's website is at:
dc.description.abstractAn observation sensitivity (OS) method to identify targeted observations is implemented in the context of four-dimensional variational (4D-Var) data assimilation. This methodology is compared with the well-established adjoint sensitivity (AS) method using a nonlinear Burgers equation as a test model. Automatic differentiation software is used to implement the first-order adjoint model (ADM) to calculate the gradient of the cost function required in the 4D-Var minimization algorithm and in the AS computations and the second-order ADM to obtain information on the Hessian matrix of the 4D-Var cost that is necessary in the OS computations. Numerical results indicate that the observation-targeting is particularly successful in reducing the forecast error for moderate Reynolds numbers. The potential benefits of the OS targeting approach over the AS are investigated. The effect of random perturbations on the performance of these adaptive observation techniques is also analyzed.en_US
dc.publisher© 2012 John Wiley & Sons, Ltd.en_US
dc.subjectAdaptive observationsen_US
dc.subjectAdjoint sensitivityen_US
dc.subjectAutomatic differentiationen_US
dc.subjectForecast erroren_US
dc.subjectHessian matrixen_US
dc.subjectObservation sensitivityen_US
dc.titleEffect of random perturbations on adaptive observation techniquesen_US
dc.contributor.departmentDepartment of Mathematics and Natural Sciences, BRAC University

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