Generalized Variational Data Assimilation Method and Numerical Experiment for Non-Differential System
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摘要: 讨论了不可微预报系统中的广义变分同化方法．对于不可微预报系统，由于不可微性,系统不存在切线性系统,而切线性系统的不存在,使得无法用通常的途径导出伴随系统A·D2引进不可微系统的弱形式后，可以不考虑切线性系统，而直接导出伴随系统．主要就3种形式的问题展开了讨论,第1种为低维系统,第2种情形为高维系统整体观测资料,第3种情形为高维系统局部观测资料．可以称此方法为结合反问题思想的广义变分同化方法．Abstract: The generalized variational data assimilation for non-differential dynamical systems is studied.There is no tangent linear model for non-differential systems and thus the general adjoint model can not be derived in the traditional way.The weak form of the original system was introduced,and then the generalized adjoint model was derived.The generalized variational data assimilation methods were developed for non-differential low dimensional system and non-differential high dimensional system with global and local observations.Furthermore,ideas in inverse problems are introduced to 4DVAR of non-differential partial differential system with local observations.
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Key words:
- variational data assimilation /
- non-differential system /
- adjoint method
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