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首页> 外文期刊>Estuarine Coastal and Shelf Science >Simultaneously assimilating multi-source observations into a three-dimensional suspended cohesive sediment transport model by the adjoint method in the Bohai Sea
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Simultaneously assimilating multi-source observations into a three-dimensional suspended cohesive sediment transport model by the adjoint method in the Bohai Sea

机译：同时将多源观测与渤海伴随方法同时将多源观测分成三维悬浮沉积物运输模型

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The performance of the suspended cohesive sediment transport model can be improved by using data assimilation; however, only one source of observations of suspended sediment concentrations (SSCs) is assimilated in the previous studies. This study investigates the simultaneous assimilation of multi-source SSC observations, including in-situ SSC observations and GOCI-retrieved SSCs, into a three-dimensional suspended cohesive sediment transport model by the adjoint method in the Bohai Sea.The artificial SSC observations obtained by running the suspended cohesive sediment transport model are firstly assimilated in the twin experiments. When the initial surface condition obtained using GOCI-retrieved SSCs was used, the model performance after assimilating multi-source artificial SSC observations was improved than that after assimilating only artificial GOCI-retrieved SSCs or in-situ SSC observations. The real multi-source SSC observations are then assimilated in practical experiments. The experimental results indicate that the initial conditions are not only important for SSC simulations, but also significant for data assimilation. Except for the surface layer, assimilating only GOCI-retrieved SSCs can significantly improve the simulated SSCs in the middle and bottom layers. On the whole, the results of simultaneously assimilating multi-source SSC observations are just slightly closer to the SSC observations than those after assimilating only GOCI-retrieved SSCs, but the convergence of adjoint data assimilation is accelerated and the model performance in deep layers is further improved, demonstrating the effectiveness of simultaneously assimilating multi-source SSC observations.
机译：通过使用数据同化可以提高悬浮的内聚沉积物传输模型的性能;然而，在先前的研究中仅同化悬浮沉积物浓度（SSCs）的一个观察来源。本研究调查了通过渤海中的伴随方法进入三维悬浮的沉积物传输模型的多源SSC观察的同时同时同时同化多源SSC观察，包括原位SSC观察和GOCI检索的SSC。通过在双实验中首先同化悬浮的粘性沉积物传输模型。当使用使用GOCI检索的SSC获得的初始表面条件时，在同化多源人工SSC观察后的模型性能得到改善，而是仅在吸收人工GOCI检索的SSC或原位SSC观察中的过程中。然后在实际实验中同化真实的多源SSC观察。实验结果表明，初始条件不仅对SSC仿真重要，而且对数据同化也很重要。除了表面层外，仅仅可以显着改善中间层和底层中的模拟SSC的同化。总的来说，同时吸收多源SSC观测的结果与SSC观察略近于同化仅吸收了Goci检索的SSC的SSC观察，但加速了伴随数据同化的收敛性，并且深层的模型性能进一步改进，展示了同时同时吸收多源SSC观测的有效性。

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