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Sensitivity of a shallow-water model to parameters

机译:浅水模型对参数的敏感性

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An adjoint based technique is applied to a shallow water model in order to estimate the influence of the model's parameters on the solution. Among parameters, the bottom topography, initial conditions, boundary conditions on rigid boundaries, viscosity coefficients, Coriolis parameter and the amplitude of the wind stress tension are considered. Their influence is analyzed from three points of view: flexibility of the model with respect to a parameter that is related to the lowest value of the cost function that can be obtained in the data assimilation experiment that controls this parameter;possibility to improve the model by the parameter's control, i.e., whether the solution with the optimal parameter remains close to observations after the end of control;sensitivity of the model solution to the parameter in a classical sense. That implies the analysis of the sensitivity estimates and their comparison with each other and with the local Lyapunov exponents that characterize the sensitivity of the model to initial conditions. Two configurations have been analyzed: an academic case of the model in a square box and a more realistic case simulating Black sea currents. It is shown in both experiments that the boundary conditions near a rigid boundary highly influence the solution. This fact points out the necessity to identify optimal boundary approximation during a model development.
机译:为了评估模型参数对解的影响,将一种基于伴随的技术应用于浅水模型。在参数中,考虑了底部地形,初始条件,刚性边界上的边界条件,粘度系数,科里奥利参数和风应力张力的幅度。从以下三个角度分析了它们的影响:模型相对于参数的灵活性,该参数与控制该参数的数据同化实验中可以获得的成本函数的最小值有关;可以通过以下方法改进模型:参数的控制,即控制结束后是否具有最优参数的解是否仍然接近观察值;经典意义上模型解对参数的敏感性。这意味着需要对灵敏度估计值进行分析,并将其与彼此以及与表征模型对初始条件的灵敏度的局部Lyapunov指数进行比较。分析了两种配置:一个在方盒中的模型的学术案例和一个模拟黑海潮流的更现实的案例。在两个实验中都表明,刚性边界附近的边界条件对解决方案有很大影响。这一事实指出了在模型开发过程中确定最佳边界近似的必要性。

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