A new approach for inferring spatially continuous multi-technique vertical land motion (VLM) models for coastal areas and sea level research

确定沿着海岸的垂直地面运动（VLM）有助于更好地了解导致海岸沉降的过程，以及解释相对海平面（RSL）上升;后者对于海岸下沉速度比以前预测的更快很重要。我们建议创建一个新的VLM模型，通过整合三个数据集：全球导航卫星系统（GNSS）站观测到的VLM时间序列，从雷达测高（ALT）和验潮记录（TG）（ALT-TG）之间的差异估计的VLM时间序列和来自干涉合成孔径雷达（干涉合成孔径雷达）的VLM时间序列。我们的模型解决了估计沿着缺乏GNSS站覆盖的海岸的VLM时间序列的问题。我们在这里提到，我们不打算只插值随时间变化的VLM速率，而是将沿着欧洲和东南亚的预定义沿海地区插值单个月VLM值。为此，我们将使用三种插值方法：常用的克里金方法，最近派生的空间成像的基础上Delaunay三角剖分，和一个新提出的三角剖分方法，它可以被认为是空间成像算法的扩展。插值程序将在一个联合插值程序中同时应用于所有三个数据集。将针对合成数据集测试方法的可靠性。在建立了网格化的VLM时间序列模型之后，我们将通过计算ALT和VLM之间的差异（ALT-VLM）来估计沿着相对海平面（RSL）的网格化模型。然后将该网格化数据集与TG进行比较。我们的项目将结束模拟实验，将考虑是否未来增加超精密光学时钟的大地测量基础设施在TG网站将改善RSL和VLM模型。在此背景下，该项目将通过与ALT、TG、GNSS和干涉合成孔径雷达数据集相一致的改进的综合VLM时间序列模型，更好地限制RSL在月至十年时间尺度上的变化，改善欧洲和东南亚沿着海岸的区域海平面预算，从而限制RSL上升的重建和预测。

The determination of vertical land motion (VLM) along the coast contributes to a better understanding of the processes causing coastal subsidence, and the interpretation of relative sea level (RSL) rise; the latter is important for coasts sinking faster than previously predicted. We propose to create a new VLM model by integrating three datasets: VLM time series observed by Global Navigation Satellite System (GNSS) stations, VLM time series estimated from differences between radar altimetry (ALT) and tide gauge records (TG) (ALT-TG) and VLM time series derived from Interferometric Synthetic Aperture Radar (InSAR). Our model solves a problem for estimating VLM time series along the coasts that lack GNSS station coverage. We mention here that we do not intend to interpolate only the VLM rate over time, but will interpolate individual monthly VLM values along the pre-defined coastal areas of Europe and Southeast Asia. For this purpose, we will use three interpolation methods: often employed kriging approach, lately derived spatial imaging based on Delaunay triangulation, and a newly proposed triangulation approach, which can be considered as the extension of spatial imaging algorithm. Interpolation procedures will be applied to all three datasets at one time, in a one, joint interpolation procedure. The reliability of the methods will be tested for a synthetic dataset. Having created a gridded VLM time series model, we will estimate a gridded model of relative sea level (RSL) along the coasts, by computing differences between ALT and VLM (ALT-VLM). This gridded dataset will then be compared with TGs. Our project will conclude with simulation experiments that will consider whether the future addition of ultra-precise optical clocks to the geodetic infrastructure at the TG site would improve both RSL and VLM models. Against this background, this project will, through an improved integrated VLM time series model that is consistent with ALT, TG, GNSS, and InSAR datasets, better allow to constrain RSL change at monthly to decadal time scales, improve regional sea level budgets along the coasts of Europe and Southeast Asia, and thus constrain reconstructions and predictions of RSL rise.