Rigorous Fusion of Gravity Field into Stationary Ocean Models

在Rifugio中，我们认为高程海面是用球谐函数表示的大地水准面高度和用有限元方法参数化的平均动态地形的总和。利用这种组合模型，我们避免了逐步逼近中所需的反演和平滑过程，并以一种直接的方式估计了平均动态地形的法方程。随后，这些法方程被用于静态海洋模型中，以最小二乘意义对模型数据失配进行加权。这些严格组合的模式的原型是为我们的主要研究区域北大西洋开发的，并被同化到三维反演模式IFEOM中。有必要对数据合并过程中产生的数字效应进行详细分析。Rifugio+的主要目标是评估这种严格的数据同化，并对我们的方法进行调整和改进。此外，我们还希望通过整合GOCE大地水准面模型和多任务测高来提高模型的空间分辨率。一个重要的方面是，这项研究中的海洋模型是否能够改进对平均动态地形的估计。在详细的冗余分析中，我们将研究新数据对海洋模型的影响，从而反馈信息来确定重力场解。

In RIFUGIO we considered the altimetric sea surface as a sum of geoid heights represented in terms of spherical harmonics and the mean dynamic topography parameterized by a finite element method. With this combined model we avoid the inversion and smoothing processes which are necessary in the step-by-step approaches and estimate the normal equations of the mean dynamic topography in a straightforward way. Subsequently, these normal equations have been used in stationary ocean models to weight the model data misfit in a least-squares sense. Prototypes of those rigorously combined models were developed for our main study area the North Atlantic ocean and assimilated into the 3D-inverse model IFEOM. A detailed analysis of numerical effects arising during the data combination will be necessary. The main goal of RIFUGIO+ is the assessment of this rigorous data assimilation and the tuning and refinement of our method. In addition we want to increase the spatial resolution of our model by the integration of GOCE geoid models and multi-mission altimetry. An important aspect is the question whether the ocean models in this study can improve estimates of the mean dynamic topography. In a detailed redundancy analysis we will study the impact of the new data on the ocean model and thus feedback information into determining gravity field solutions.