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Towards a data assimilation system for morphodynamic modeling: bathymetric data assimilation for wave property estimation

机译：走向用于形态动力学建模的数据同化系统：用于波特性估计的测深数据同化

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Data assimilation is mainly concerned with the proper management of uncertainties. The main objective of the present work is to implement and analyze a data assimilation technique capable of assimilating bathymetric data into a coupled flow, wave, and morphodynamic model. For the case presented here, wave significant height, wave direction of incidence, and wave peak period are being optimized based on bathymetric data taken from a twin experiment. An adjoint-free variational scheme is used. In this approach, a linear reduced order model (ROM) is constructed as an approximation of the full model. The ROM is an autoregressive model of order 1 (AR1) that preserves the parametrization. Since the ROM is linear, the construction of its adjoint is straightforward, making the implementation of 4D variational data assimilation effortless. The scheme is able to update the morphodynamic model satisfactorily despite the fact that the model shows nonlinear behavior even for very small perturbations of all three parameters. The size and direction of the perturbations necessary for constructing the ROM have a significant impact on the performance of the technique.
机译：数据同化主要涉及不确定性的正确管理。本工作的主要目的是实施和分析能够将测深数据同化为流量，波动和形态动力学模型的数据同化技术。对于此处介绍的情况，正在根据双胞胎实验获得的测深数据来优化波的有效高度，波的入射方向和波峰周期。使用无伴随变分方案。在这种方法中，线性降阶模型（ROM）被构造为完整模型的近似值。 ROM是1阶（AR1）的自回归模型，可保留参数化。由于ROM是线性的，因此其附件的构造非常简单，从而使4D变异数据同化的实现变得毫不费力。该方案能够令人满意地更新形态动力学模型，尽管该模型即使在所有三个参数的很小扰动下仍显示出非线性行为。构造ROM所需的扰动的大小和方向对技术的性能有重大影响。

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