The example of a numerical prediction model shows the basic method of developing adjoint assimilation system of numeric predict model.
而后以一个数值预报模式为例，说明了构造伴随模式同化系统的基本方法。
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。
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。
To carry out the data assimilation of sea temperature observations the adjoint method is applied, which can provide an accurate initial temperature field for numerical prediction.
以一维水温模型为例，利用伴随算子法进行海洋观测数据同化，以便给水温的数值预报提供一个较准确的初始场。
To carry out the data assimilation of sea temperature observations the adjoint method is applied, which can provide an accurate initial temperature field for numerical prediction.
以一维水温模型为例，利用伴随算子法进行海洋观测数据同化，以便给水温的数值预报提供一个较准确的初始场。
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