首页|Application of the finite analytic numerical method to a flow-dependent variational data assimilation

Application of the finite analytic numerical method to a flow-dependent variational data assimilation

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An anisotropic diffusion filter can be used to model a flow-dependent background error covariance matrix,which can be achieved by solving the advection-diffusion equation.Because of the directionality of the advection term,the discrete method needs to be chosen very carefully.The finite analytic method is an alternative scheme to solve the advection-diffusion equation.As a combination of analytical and numerical methods,it not only has high calculation accuracy but also holds the characteristic of the auto upwind.To demonstrate its ability,the one-dimensional steady and unsteady advection-diffusion equation numerical examples are respectively solved by the finite analytic method.The more widely used upwind difference method is used as a control approach.The result indicates that the finite analytic method has higher accuracy than the upwind difference method.For the two-dimensional case,the finite analytic method still has a better performance.In the three-dimensional variational assimilation experiment,the finite analytic method can effectively improve analysis field accuracy,and its effect is significantly better than the upwind difference and the central difference method.Moreover,it is still a more effective solution method in the strong flow region where the advective-diffusion filter performs most prominently.

finite analytic methodadvection-diffusion equationdata assimilationflow-dependent

Yan Hu、Wei Li、Xuefeng Zhang、Guimei Liu、Liang Zhang

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Tianjin Key Laboratory for Marine Environmental Research and Service,School of Marine Science and Technology,Tianjin University,Tianjin 300072,China

School of Marine Science and Technology,Tianjin University,Tianjin 300072,China

National Marine Environmental Forecasting Center,Ministry of Natural Resources,Beijing 100081,China

National Key Research and Development Program of ChinaNational Key Research and Development Program of ChinaNational Key Research and Development Program of ChinaNational Programme on Global Change and Air-Sea Interaction of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of China

2022YFC31048042021YFC31015012017YFC1404103GASI-IPOVAI-04418760144160603911801402

2024

10.1007/s13131-023-2229-z

海洋学报(英文版)
中国海洋学会

海洋学报(英文版)

CSTPCD
影响因子：0.323
ISSN：0253-505X
年,卷(期)：2024.43(3)
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