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A continuous GPS coordinate time series analysis strategy for high-accuracy vertical land movements

机译:高精度垂直陆地运动的连续Gps坐标时间序列分析策略

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摘要

CGPS coordinate time series analysis strategy was evaluated to determine highly accurate vertical station velocity estimates with realistic uncertainties. This strategy uses a combination of techniques to (1) obtain the most accurate parameter estimates of the station motion model, (2) infer the stochastic properties of the time series in order to compute more realistic error bounds for all parameter estimates, and (3) improve the understanding of apparent common systematic variations in the CGPS coordinate time series, which are believed to be of geophysical and/or technical origin. The strategy provided a pre-processing of the coordinate time series in which outliers and discontinuities were identified. Subsequent parameterization included a mean value, a constant rate, periodic terms with annual and semi-annual frequencies, and offset magnitudes for identified discontinuities. All parameters plus the magnitudes of different stochastic noise were determined using maximum likelihood estimation (MLE). Empirical orthogonal function (EOF) analysis was used to study both the temporal and spatial variability of the common modes determined by this technique. After outlining the CGPS coordinate time series analysis strategy this paper shows initial results for coordinate time series for a four year (2000–2003) period from a selection of CGPS stations in Europe that are part of the European Sea Level Service (ESEAS) CGPS network
机译:对CGPS坐标时间序列分析策略进行了评估,以确定具有实际不确定性的高精度垂直站速度估算值。此策略使用技术组合来(1)获得站运动模型的最准确的参数估计值;(2)推断时间序列的随机属性,以便为所有参数估计值计算更实际的误差范围;以及(3 )增进对CGPS坐标时间序列中明显的常见系统变化的理解,这些变化被认为是地球物理和/或技术起源的。该策略提供了对坐标时间序列的预处理,其中可以识别异常值和不连续性。随后的参数化包括平均值,恒定速率,具有年度和半年度频率的周期项以及已识别不连续性的偏移量级。使用最大似然估计(MLE)确定所有参数以及不同随机噪声的大小。经验正交函数(EOF)分析用于研究此技术确定的共模的时间和空间变异性。在概述了CGPS坐标时间序列分析策略后,本文显示了从欧洲海平面服务(ESEAS)CGPS网络的一部分欧洲CGPS站中选择的四年(2000-2003年)期间坐标时间序列的初步结果

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