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Effect of random perturbations on adaptive observation techniques
Author(s) -
Hossen M. J.,
Navon I. M.,
Daescu D. N.
Publication year - 2011
Publication title -
international journal for numerical methods in fluids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 112
eISSN - 1097-0363
pISSN - 0271-2091
DOI - 10.1002/fld.2545
Subject(s) - hessian matrix , data assimilation , automatic differentiation , computation , sensitivity (control systems) , context (archaeology) , mathematics , nonlinear system , adjoint equation , mathematical optimization , minification , software , computer science , algorithm , partial differential equation , mathematical analysis , physics , engineering , paleontology , quantum mechanics , electronic engineering , meteorology , biology , programming language
SUMMARY An 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. Copyright © 2011 John Wiley & Sons, Ltd.