

FOLLOWUS
1. First Institute of Oceanography State Oceanic Administration
2. Key Laboratory of Marine Science and Numerical Modeling State Oceanic Administration
3. Institute of Oceanology Chinese Academy of Sciences
纸质出版:2000
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Wave assimilation and numerical prediction[J]. 海洋湖沼学报(英文), 2000,18(4):301-308.
Yong-zeng, Y., Fang-li, Q. & Zeng-di, P. Wave assimilation and numerical prediction., Chin. J. Ocean. Limnol. 18, 301–308 (2000). https://doi.org/10.1007/BF02876076
Wave assimilation and numerical prediction[J]. 海洋湖沼学报(英文), 2000,18(4):301-308. DOI: 10.1007/BF02876076.
Yong-zeng, Y., Fang-li, Q. & Zeng-di, P. Wave assimilation and numerical prediction., Chin. J. Ocean. Limnol. 18, 301–308 (2000). https://doi.org/10.1007/BF02876076 DOI:
An adjoint variational method for wave data assimilation in the LAGFD-WAM wave model is proposed. The adjoint equation of the wavenumber energy spectrum balance equation is derived. And fortunately
its characteristic equations are the same as those in the LAGFD-WAM wave model. Simple experiments on the functional optimization and assimilation effectiveness during the prediction period indicated that the adjoint variational method is effective for wave assimilation and that the initial optimization of the wave model is important for the short-range wave prediction. All of this is under the assumption that the wind field is accurate
the method is the important first step for combined wind and wave data assimilation systems.
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