A Study of Data Assimilation on Nearshore Wind Wave Hindcasting
碩士 === 國立成功大學 === 水利及海洋工程學系碩博士班 === 92 === A revised SWAN model based on the data assimilation technique is developed by using the Finite Element Method (FEM). In the present FEM code the numerical scheme of the original SWAN model is improved to ensure the effectiveness of the computation at ever...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2004
|
| Online Access: | http://ndltd.ncl.edu.tw/handle/8txs3w |
| Summary: | 碩士 === 國立成功大學 === 水利及海洋工程學系碩博士班 === 92 === A revised SWAN model based on the data assimilation technique is developed by using the Finite Element Method (FEM). In the present FEM code the numerical scheme of the original SWAN model is improved to ensure the effectiveness of the computation at every operational stage. To enhance the efficiency of the numerical simulation, the existing experimentally observed data are combined with the first guess values upon linearizing by optimal interpolation. The data assimilation technique reduces the error in the wind field evaluation by using the optimal weighting, in which the correction length is chosen to be 6~8 times that of the gird length. Numerical tests show that the data assimilation analysis tends to be stable as the number of observations is lager than seven. The present model is also successfully applied to the wind wave forecasting at the eastern coast of Taiwan. The results indicate that the present model is applicable to predict typhoon waves efficiently and accurately.
|
|---|