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:: Volume 10, Issue 40 (2019) ::
joc 2019, 10(40): 85-95 Back to browse issues page
Enhanced predictions of tides in the Persian Gulf through data assimilatio
Davood Shariatmadari, Seyed Mostafa Siadatmousavi Dr , Cyrus Ershadi Dr
Iran University of Science and Technology, Tehran, Iran , siadatmousavi@iust.ac.ir
Abstract:   (1044 Views)
Abstract
Hydrodynamic models are widely used for simulating water level and oceanic current; however due to uncertainties involved in this process such as accuracy of input data or realization of the governing equations, there are some errors in the simulation results. Data assimilation is one of the effective solutions to avoid and to limit some of these errors. This manuscript evaluates how Ensemble Kalman filter, one of the most advance assimilation techniques, can enhance water elevation predictions in the Persian Gulf. The open source Delft3D FM was used as a hydrodynamic model and open source code of Open DA was employed to apply Kalman Filter. The Open DA was coupled inside the code of hydrodynamic model to improve its performance. We have setup several experiments to estimate the best number of groups, error parameter of observations, error parameter of open boundary, and the most effective station for assimilation. The results show that the data assimilation can effectively improve the hydrodynamic model results and can be used for real applications.
Keywords: Data assimilation, Ensemble Kalman Filter, Delft3D-FM, Open DA, tide, Persian Gulf
Full-Text [PDF 1124 kb]   (208 Downloads)    
Type of Study: Research | Subject: Coastal Engineering
Received: 2019/09/22 | Accepted: 2019/12/15 | ePublished: 2020/05/26
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Shariatmadari D, Siadatmousavi S M, Ershadi C. Enhanced predictions of tides in the Persian Gulf through data assimilatio. joc. 2019; 10 (40) :85-95
URL: http://joc.inio.ac.ir/article-1-1552-en.html


Volume 10, Issue 40 (2019) Back to browse issues page
نشریه علمی پژوهشی اقیانوس شناسی Journal of Oceanography
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