顾及环境负载的青藏高原东南缘GNSS垂向坐标时序噪声模型研究

Noise Model of GNSS Vertical Coordinate Time Series in Southeastern Tibet Plateau Based on Environmental Loading

    摘要
  • 摘要: 准确辨识出全球导航卫星系统（global navigation satellite system, GNSS）垂向坐标时间序列的最优噪声模型，对于获取可靠的抬升或沉降变形速度场并评估速度不确定度至关重要。利用青藏高原东南缘在2011-01-01—2022-12-30间94个GNSS连续站观测数据和环境负载模型数据，选用9种噪声模型对环境负载改正前后的GNSS垂向坐标时间序列进行噪声特性分析，并定量评价了环境负载效应的影响。研究结果表明，水文、大气、非潮汐海洋负载均对GNSS垂向坐标时间序列存在影响。环境负载改正后，三者的均方根分别减少-1.3%~22%、-1.4%~17.4%和-0.1%~1.3%，其平均值分别为8.7%、6.7%和0.6%。在空间分布上，位于鲜水河-安宁河-则木河断裂带西侧的测站受水文负载影响更大，而东侧的测站受大气负载影响更大。经过环境负载改正后，94个GNSS连续站最优噪声模型主要表现为幂律噪声（power-law noise, PL），其次是白噪声分别与闪烁噪声、PL的组合。环境负载改正前后，基于最优噪声模型估计的速度差值范围为-0.11~0.26 mm/a，速度不确定度差值范围为-0.33~0.16 mm/a。进一步通过分析测站速度不确定度与高程、年均降雨量、经度、纬度之间的线性关系，发现青藏高原东南缘的年均降雨量、高程、经度、纬度对GNSS测站的稳定性影响较小。

     

    Abstract:
    Objectives Accurately identifying the optimal noise model of global navigation satellite system (GNSS) vertical coordinate time series is vital to obtain reliable uplift or subsidence deformation velocity fields and assess the associated uncertainties.
    Methods In this paper, we collect data from 9 noise models including white noise (WN), flicker noise (FN), power-law noise (PL), random walk noise(RW), WN+FN, WN+PL, WN+generalized Gauss⁃Markov noise, WN+RW, WN+RW+FN.These data and noise models are used to analyze the noise characteristics of GNSS vertical coordinate time series before and after environmental loading correction at 94 stations spanning from January 2011 to December 2022 in the southeastern Tibet Plateau.
    Results The results show the root mean squares reduction is -1.3%⁃22%,-1.4%⁃17.4%, and -0.1%⁃1.3%, with a mean value of 8.7%, 6.7% and 0.6% for all stations after removing the hydrological, atmospheric, and nontidal ocean loading deformation from the GNSS vertical coordinate time series, respectively. The hydrological loading has a greater impact in the west side of Xianshuihe-Anninghe-Zemuhe fault zone, and the atmospheric load has a greater impact in east side of this fault zone. The optimal noise model at all stations was mainly represented by PL, a combination of WN, PL, and FN before and after environmental loading correction. The value of velocity and its uncertainty before and after environmental loading correction based on optimal noise model vary from -0.11⁃0.26 mm/a and from -0.33⁃0.16 mm/a. We analyze the stability of GNSS stations through the linear relationship between GNSS vertical velocity uncertainty and elevation, average annual rainfall, longitude, latitude. The results of correlations coefficient are 0.08, 0.07, 0.11, and 0.25, respectively, implying the average annual rainfall, elevation, longitude, and latitude have little impact on station stability in the southeastern Tibet Plateau.
    Conclusions This research suggest that the optimal noise model at most stations in the southeastern Tibet Plateau is PL. The results provide a reference for subsequent reasonable acquisition of GNSS velocity and its uncertainy in the southeastern Tibet Plateau.

     

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