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 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.
伴随模式的方法是以数值天气预报的动力模式作为约束条件的变分方法，比传统的变分方法有了很大的改进。
It is a variational method whose constraints are represented by the dynamic model for numerical weather prediction, and is a substantial improvement on the traditional variational scheme.
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。
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。
The four-dimensional data assimilation is to integrate the current and past data into a forecast model equation for providing time continuity and dynamic coupling.
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。
The four-dimensional data assimilation is to integrate the current and past data into a forecast model equation for providing time continuity and dynamic coupling.
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