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引用本文:杜云飞,张继才,王道胜.杭州湾三维悬浮泥沙输运模型初始场的伴随法反演研究.海洋与湖沼,2020,51(5):1025-1042.
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杭州湾三维悬浮泥沙输运模型初始场的伴随法反演研究
杜云飞1, 张继才1, 王道胜2,3
1.浙江大学海洋学院 舟山 316000;2.中国地质大学(武汉)海洋学院 海洋地质资源湖北省重点实验室 武汉 430074;3.南方海洋科学与工程广东省实验室(广州) 广州 511458
摘要:
在悬沙输运的数值模拟中,初始场的准确给定至关重要。目前诸多确定初始场的方案均存在一定的缺陷,初始场的准确性有待进一步提高。本文基于一个三维悬沙输运伴随同化模型,通过孪生实验和实际实验,对模型初始场进行了伴随法反演研究。在孪生实验中,首先验证了初始场的相对重要性;其次,探讨了初始场的反演结果对优化算法、初始猜测值、卫星遥感数据数量、同化时间窗口宽度和背景流场误差的敏感性;最后,比较了伴随法和插值法重构初始场的能力。孪生实验结果表明:最速下降法对初始场的优化反演效果要优于三种共轭梯度法和有限记忆BFGS法;初始场的反演效果对初始猜测值、卫星遥感数据数量和背景流场误差不敏感,而对同化窗口宽度较为敏感;与插值法相比,伴随法是重构模型初始场更有效的手段。实际实验中,在杭州湾海域同化典型的小潮时期和大潮时期的GOCI卫星遥感资料所得表层悬沙浓度数据,优化反演了初始场。实际实验结果表明:数据同化后,得到了更符合实际的最优初始场,表明伴随法是实现初始场优化反演的有效手段。该研究对进一步改进悬沙输运模型的初始化方案具有一定的参考价值,也对其他数值模型的初始化方案具有一定的借鉴价值。
关键词:  伴随同化  悬沙输运模型  初始场  GOCI
DOI:10.11693/hyhz20191000189
分类号:P731
基金项目:国家重点研发计划“全球变化及应对”重点专项,2017YFA0604100号;国家重点研发计划“海洋环境安全保障”重点专项,2017YFC1404000号;国家自然科学基金,41876086号;南方海洋科学与工程广东省实验室(广州)人才团队引进重大专项,GML2019ZD0604号;中央高校基本科研业务费专项资金,2019QNA4052号
INVERSION OF INITIAL CONDITION OF A THREE-DIMENSIONAL SUSPENDED SEDIMENT TRANSPORT MODEL IN HANGZHOU BAY WITH AN ADJOINT METHOD
DU Yun-Fei1, ZHANG Ji-Cai1, WANG Dao-Sheng2,3
1.Ocean college, Zhejiang University, Zhoushan 316000, China;2.College of Marine Science and Technology Hubei Key Laboratory of Marine Geological Resources, China University of Geosciences, Wuhan 430074, China;3.Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou), Guangzhou 511458, China
Abstract:
In the numerical simulation of suspended sediment transport, accurate setting of initial condition is important. Available methods of initial condition determination have some defects, and thus the accuracy of initial condition needs to be improved. Based on a three-dimensional suspended sediment transport model with the adjoint data assimilation, adjoint method was used to optimize initial condition of the model by running twin experiments and practical experiments. In the twin experiments, the influence of errors of initial condition on the simulation results was studied. Then, the sensitivity of inversion results of initial condition to different influencing factors such as optimization algorithms, initial guess values, number of satellite remote sensing data, window width of assimilation time, and errors of background flow field were discussed. At last, the ability to reconstruct initial condition with adjoint method and interpolation method was compared. The results of the twin experiments show that, the steepest descent algorithm was better than three conjugate-gradient algorithms and limited-memory Broyden-Fletcher-Goldfarb-Shanno algorithm in optimizing initial condition. The inversion results are less sensitive to initial guess values, number of satellite remote sensing data, and errors of background flow field, but sensitive to the width of assimilation window. Compared with interpolation methods, the adjoint method was a more effective method of reconstructing initial condition of a model. In the practical experiments, the surface suspended sediment concentration data obtained from the GOCI satellite remote sensing data in typical neap and spring tide periods in Hangzhou Bay were used to optimize the initial condition. Results of the practical experiments show that after data assimilation, a more realistic optimal initial condition could be obtained, indicating that the adjoint method was an effective tool for initial condition optimization. This study provides references for improving initialization schemes of suspended sediment transport model, and for the initialization schemes of other numerical models.
Key words:  adjoint assimilation  suspended sediment transport model  initial condition  GOCI
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