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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
Estuarine, Coastal and Shelf Science ( IF 2.6 ) Pub Date : 2020-05-05 , DOI: 10.1016/j.ecss.2020.106809
Daosheng Wang , Jicai Zhang , Xinyan Mao , Changwei Bian , Zhou Zhou

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.



中文翻译:

伴随法在渤海海域同时将多源观测资料同化为三维悬浮黏性泥沙输运模型

可以通过数据同化来提高悬浮粘性泥沙输送模型的性能。但是,以前的研究仅吸收了悬浮沉积物浓度(SSCs)的一种观测资料。这项研究调查了多种来源的SSC观测资料,包括原位SSC观测资料和GOCI回收的SSC资料,通过伴随法在渤海中被同化为三维悬浮粘性沉积物传输模型。

在双胞胎实验中,首先将通过运行悬浮的粘性泥沙运移模型获得的人工SSC观测结果同化。当使用通过GOCI修复的SSC获得的初始表面条件时,同化多源人工SSC观测后的模型性能比仅同化GOCI人工SSC或就地SSC观测的模型性能有所改善。然后在实际实验中将真实的多源SSC观测值同化。实验结果表明,初始条件不仅对于SSC模拟很重要,而且对于数据同化也很重要。除了表面层,仅吸收GOCI修复的SSC可以显着改善中层和底层的模拟SSC。总体上,

更新日期:2020-05-05
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