Anatomy of apparent seasonal variations from GPS-derived site position time series
Anatomy of apparent seasonal variations from GPS-derived site position time series
复制标题
DOI：
10.1029/2001jb000573
复制
发表时间：
2002-04-10
影响因子：
3.9
通讯作者：
Miyazaki, S
中科院分区：
文献类型：
--
作者：
Dong, D;Fang, P;Miyazaki, S
[1]明显的季节性站点位置变化来自4.5年的全球连续GPS时间序列，并通过“对等”的方法进行了探索。Peering是一种描述相对知名的季节性来源的贡献的方法，以深入了解相对鲜为人知的贡献者。极潮效应，海潮负荷，大气负荷，非潮汐海洋质量，地下水负荷的贡献进行了评估。我们的研究结果表明，观测到的站点位置的年垂直变化的近似40%的功率可以由这些季节性表面质量再分布的联合贡献来解释。从观测中去除这些季节性影响后，还研究了未建模的对流层湿效应、基岩热膨胀、相位中心变化模型中的误差和轨道建模中的误差的潜在贡献。提出了一种比例敏感性矩阵分析来评估高度相关参数的贡献。通过比较不同GPS数据分析中心的解，研究了采用不同分析策略的效果。比较结果表明，目前的解决方案的几个分析中心能够检测到的季节性信号，但这些解决方案之间的差异是残留的季节性效应的主要原因。模拟全球站点位置的季节性变化的潜在影响进行了探讨，特别是，作为一种方法，以提高季节性时间尺度上的陆地参考框架的稳定性。
[1] Apparent seasonal site position variations are derived from 4.5 years of global continuous GPS time series and are explored through the "peering'' approach. Peering is a way to depict the contributions of the comparatively well-known seasonal sources to garner insight into the relatively poorly known contributors. Contributions from pole tide effects, ocean tide loading, atmospheric loading, nontidal oceanic mass, and groundwater loading are evaluated. Our results show that similar to40% of the power of the observed annual vertical variations in site positions can be explained by the joint contribution of these seasonal surface mass redistributions. After removing these seasonal effects from the observations the potential contributions from unmodeled wet troposphere effects, bedrock thermal expansion, errors in phase center variation models, and errors in orbital modeling are also investigated. A scaled sensitivity matrix analysis is proposed to assess the contributions from highly correlated parameters. The effects of employing different analysis strategies are investigated by comparing the solutions from different GPS data analysis centers. Comparison results indicate that current solutions of several analysis centers are able to detect the seasonal signals but that the differences among these solutions are the main cause for residual seasonal effects. Potential implications for modeling seasonal variations in global site positions are explored, in particular, as a way to improve the stability of the terrestrial reference frame on seasonal timescales.