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Data Assimilation Technique Applied to Tidal Prediction Model

Computer technology is growing fast in recent years. Modeling technique is used in predicting or in planning engineering works and even in preventing disaster. Modeling is widely used in many domains and unmanned Real-time online operation modeling systems on prediction become popular. Model may become inaccurate due to a number of uncertainties in the approximation and by numerical reasons. Data Assimilation technique is developed to solve this problem. Measured data is used to improve the model results. In this research, the Cressman scheme was chosen as the data assimilation scheme and used for correcting the modeling system.
An idealized model was constructed first as Taiwan Strait. In order to test the stability if data assimilation system several geographical variations and data availability cases were designed, eg adding varying bottom topography, an island added in the domain, different measurement data locations. In order to test the model sensibilities an error was inserted to the boundaries. Model results were first corrected with data assimilation system for a period of time, a Harmonic Analysis was, then, used for reanalysis the corrected time series on the boundaries. The new boundary condition is used in the new model run for making predictions. A true topography and island system as Taiwan Strait was tested with the true astronomical tide as the boundary input.
The data assimilation system using the Cressman scheme could reduce the RMSE effectively. The factor that affects the efficiency of the data assimilation system is the number and the location of the measurement data.
Date06 November 2012
CreatorsLin, Ken-Dei
ContributorsYang-Chi Chang, Jason C.S. Yu, Wen-Juinn Chen
Source SetsNSYSU Electronic Thesis and Dissertation Archive
Detected LanguageEnglish
Rightsunrestricted, Copyright information available at source archive

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