Parameter Estimation for a 2D Tidal Model with POD 4D VAR Data Assimilation
Combining the proper orthogonal decomposition (POD) reduced order method and 4D VAR (four-dimensional Variational) data assimilation method with a two-dimensional (2D) tidal model, a model is constructed to simulate the M2 tide in the Bohai, Yellow, and East China Seas (BYECS). This model consists o...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2016-01-01
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| Series: | Mathematical Problems in Engineering |
| Online Access: | http://dx.doi.org/10.1155/2016/6751537 |
| Summary: | Combining the proper orthogonal decomposition (POD) reduced order method and 4D VAR (four-dimensional Variational) data assimilation method with a two-dimensional (2D) tidal model, a model is constructed to simulate the M2 tide in the Bohai, Yellow, and East China Seas (BYECS). This model consists of two submodels: the POD reduced order forward model is used to simulate the tides, while its adjoint model is used to optimize the control variables. Numerical experiment is carried out to assimilate the harmonic constants, which are derived from TOPEX/Poseidon (T/P) altimeter data, into the 2D tidal model through optimizing the initial values and the temporally and spatially varying open boundary conditions (OBCs). The absolute mean difference between the model results and observations is 3.2 cm and 2.9∘ for amplitude and phase-lag, respectively, better than the results of Lu and Zhang (2006), suggesting that the construction of the POD reduced order model and the inversion of control variables are successful. |
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| ISSN: | 1024-123X 1563-5147 |