Searched for: department%3A%22mathematics%22
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Van Velzen, C. (author), Altaf, M.U. (author), Verlaan, M. (author)
Data assimilation methods provide a means to handle the modeling errors and uncertainties in sophisticated ocean models. In this study, we have created an OpenDA-NEMO framework unlocking the data assimilation tools available in OpenDA for use with NEMO models. This includes data assimilation methods, automatic parallelization, and a recently...
journal article 2016
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Altaf, M.U. (author), Butler, T. (author), Luo, X. (author), Dawson, C. (author), Mayo, T. (author), Hoteit, I. (author)
This paper presents a robust ensemble filtering methodology for storm surge forecasting based on the singular evolutive interpolated Kalman (SEIK) filter, which has been implemented in the framework of the H? filter. By design, an H? filter is more robust than the common Kalman filter in the sense that the estimation error in the H? filter has,...
journal article 2013
document
Altaf, M.U. (author)
Identifying uncertain parameters in large-scale numerical flow models can be done using the variational method. However, for implementing the variational method the adjoint model have to be available, which requires highly complex computer code and maintenance and thus hampers its applications. To ease this problem, this thesis has explored...
doctoral thesis 2011