Identification and Extraction of Seasonal Geodetic Signals Due to Surface Load Variations
Identification and Extraction of Seasonal Geodetic Signals Due to Surface Load Variations
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DOI：
10.1029/2018jb016607
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发表时间：
2018-12-01
影响因子：
3.9
通讯作者：
Avouac, J. -P.
中科院分区：
文献类型：
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作者：
Larochelle, S.;Gualandi, A.;Avouac, J. -P.
与大陆水团重新分布相关的地球表面变形，一阶解释了在大地位置时间序列中观察到的季节性信号。在大地测量中将这些季节性信号与其他变形源区分开来对于分离构造信号和监测大陆水储存的时空变化至关重要。我们提出了一种新的方法来识别和提取这些季节性信号。该方法使用变分贝叶斯独立分量分析 (vbICA) 来提取季节性信号，并使用基于重力的变形模型来识别哪些信号是由表面载荷引起的。我们在阿拉伯半岛和尼泊尔喜马拉雅山这两个研究区域测试了该程序，发现该技术成功地提取了具有一个或两个独立分量的季节性信号，具体取决于负载是静止还是移动。该方法对于大地测量固有的空间异质性具有鲁棒性，并且可以帮助提取大地测量产品中的系统误差（例如，巨龙误差）。我们还讨论了如何处理大地测量数据集中存在但基于重力的模型未捕获的 1 度变形场。
Deformation of the Earth's surface associated with redistributions of continental water mass explains, to first order, the seasonal signals observed in geodetic position time series. Discriminating these seasonal signals from other sources of deformation in geodetic measurements is essential to isolate tectonic signals and to monitor spatio-temporal variations in continental water storage. We propose a new methodology to identify and extract these seasonal signals. The approach uses a variational Bayesian Independent Component Analysis (vbICA) to extract the seasonal signals and a gravity-based deformation model to identify which of these signals are caused by surface loading. We test the procedure on two study areas, the Arabian Peninsula and the Nepal Himalaya, and find that the technique successfully extracts the seasonal signals with one or two independent components, depending on whether the load is stationary or moving. The approach is robust to spatial heterogeneities inherent to geodetic measurements and can help extract systematic errors in geodetic products (e.g., draconitic errors). We also discuss how to handle the degree-1 deformation field present in the geodetic data set but not captured by the gravity-based model.