The diffusion coefficient is estimated by variational assimilation method for 1-d diffusion equations.
利用变分同化方法对一维扩散方程扩散系数进行了估计。
In this paper the variational adjoint method is applied to the assimilation of the observed data into the sectional distribution of sea temperature to optimize the initial field.
以二维断面海温分布模型为例，利用海温实际观测数据，将变分伴随方法应用于断面海温初始场的优化。
The key problem of four-dimensional variational data assimilation method, which solves the constraining numerical predict equations through accompanied model, is how to establish an accompanied model.
应用伴随方法求解以数值预报方程作为约束条件的四维变分资料同化方案，关键问题是如何构造伴随模式。
In this numeric experiment, adjoint code is introduced into the method for variational assimilation, which brings forward a new way for predicting the primitive field.
在本文的数值试验中，使用了共轭码方法对该上述方案进行了变分同化，提出了构建数值预报初始场的新途径。
Ideal experiments are also conducted to verify the effect of the regularization method on variational data assimilation.
并通过数值试验进一步肯定正则化理论在资料同化中的作用。
Ideal experiments are also conducted to verify the effect of the regularization method on variational data assimilation.
并通过数值试验进一步肯定正则化理论在资料同化中的作用。
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