Improving deformation models by discounting transient signals in geodetic data: 1. Concept and synthetic examples
Improving deformation models by discounting transient signals in geodetic data: 1. Concept and synthetic examples
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DOI：
10.1002/2016jb013056
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发表时间：
2016-07-01
影响因子：
3.9
通讯作者：
Carafa, Michele M. C.
中科院分区：
文献类型：
--
作者：
Bird, Peter;Carafa, Michele M. C.
GPS 大地测量学提供了十年时间尺度上非常精确的基准速度，大地测量学家经常用速度协方差矩阵来描述其不确定性。然而，那些通过模拟新构造变形来估计长期地震灾害的人希望在数千年的时间尺度上限制稳定基岩的震间速度。当前者（可用数据）用作后者（所需约束）的代理时，有必要增加不确定性来表征各种瞬态和/或地表噪声过程，包括岩浆室补给、震后松弛、孔隙流体运动、极慢的滑坡和冰川均衡调整。瞬态噪声对远程参考基准的影响也增加了长期速度参考系的不确定性。我们使用来自简单模型的速度扰动向量的转置积来增强报告的速度协方差矩阵，该模型近似描述预期的瞬态和表面噪声源。由于速度矢量数据未改变，因此该方法不会引入伪影。当增广协方差矩阵的逆矩阵（减正态矩阵）用于部分由 GPS 数据驱动的新构造变形模型的目标函数时，瞬态和地表信号的扰动效应大大减少。即使先前对噪声过程的估计相当粗略，也会出现改进。我们提出了两个使用合成数据计算的示例。
GPS geodesy provides very precise velocities of benchmarks on decadal timescales, and geodesists often describe their uncertainties with a velocity covariance matrix. However, those who model neotectonic deformation to estimate long-term seismic hazard want constraints on the interseismic velocities of stable bedrock on multithousand-year timescales. When the former (available data) are used as proxies for the latter (desired constraints), it is necessary to increase uncertainties to characterize a variety of transient and/or surficial noise processes, including magma chamber recharge, postseismic relaxation, pore fluid motion, extremely slow landsliding, and glacial isostatic adjustment. The effects of transient noise on distant reference benchmarks also add to uncertainty of the long-term velocity reference frame. We augment the reported velocity covariance matrix with transpose products of velocity perturbation vectors from simple models approximately describing anticipated transient and surficial noise sources. No artifacts are introduced by this method because the velocity-vector data are unchanged. When the inverse of the augmented covariance matrix (the diminished normal matrix) is used in the objective function of a neotectonic deformation model partially driven by GPS data, the perturbing effects of transient and surficial signals are greatly reduced. Improvement occurs even when the prior estimates of noise processes are rather crude. We present two examples computed with synthetic data.