利用GPS和GRACE研究澳大利亚地壳垂向季节性变化

为探究重力场恢复与气候实验(gravity recovery and climate experiment,GRACE)卫星与全球定位系统(global positioning system,GPS)两种独立技术获取的因陆地水储量变化引起的地壳垂向季节性位移的一致性,选取澳大利亚27个GPS站点5～10 a的高程时间序...     

利用GPS垂直位移反演云南省陆地水储量变化

地表质量的重分布会引起固体地球的弹性形变,GPS连续运行观测站能够精确测定地表负荷引起的地壳形变。本文通过模拟数据对利用云南省及其周边47个中国大陆构造环境监测网（陆态网）台站反演云南地区陆地水储量的可行性进行分析：以水文模型周年振幅为真值,计算47个台站点的负荷形变,同时加入随机误差构成模拟观测数据,最后采用模型反演陆地水储量变化;1000次的随机模拟试验表明利用当前GPS台站数据可有效地反演云南地区陆地水储量变化。基于上述结论,笔者反演了云南省2010—2014年陆地水储量变化,GPS反演结果表明：云南省陆地水变化呈现明显的地域分布特征,西南部高山地区的水储量周年变化高于东部平原地区;在时间尺度上,云南省大部分地区水储量在10月（夏季末）达到最大值,在4月（冬季末）达到最小值;云南省2010—2014年陆地水呈缓慢增长趋势,约为20 mm/a。通过GPS陆地水储量反演结果与GRACE、GLDAS以及TRMM数据综合对比分析,表明利用云南地区当前GPS台站可以作为独立观测量用于GRACE与GRACE Follow-on衔接期间的陆地水储量变化监测。     

“陆态网”GPS与GRACE的中国大陆地表垂直形变对比分析

基于中国大陆构造环境监测网络的连续GPS观测数据,比较分析了中国大陆234个GPS台站和GRACE得到的地表垂直形变。GPS和GRACE垂直形变具有较好的一致性,反映了地表质量变化是引起GPS垂直形变非线性变化的重要因素之一,但二者也存在着一定的差异。为定量分析GPS和GRACE垂直形变的差异,探讨了热膨胀效应对GPS垂直位移的影响及区域地壳结构对GRACE估算地表垂直负荷形变的影响。结果表明,中国大陆50%以上的GPS台站热膨胀垂直形变周年振幅不小于1 mm;对GPS进行热膨胀效应改正后,中国大陆GPS与GRACE垂直形变具有更好的一致性;GPS与GRACE垂直形变周年振幅比值由1.07±0.06变为1.01±0.05;热膨胀效应可以解释6.2%的GPS与GRACE垂直形变的差异,热膨胀效应改正可使GPS和GRACE垂直形变的一致性相对增加11.2%。是否顾及区域地壳结构引起的GRACE估算中国大陆垂直负荷形变的相对差异为2.5%。     

利用GPS垂向位移监测西南地区干旱事件

GPS垂向位移包含了陆地水储量变化引起的地球弹性形变信息。本文利用中国大陆构造环境监测网(陆态网)31个GPS台站2010年8月—2016年12月的垂向位移数据,分析我国西南地区的干旱事件。结果表明,GPS垂向位移的季节性变化与降雨、GRACE反演的水储量、河流水位变化具有较强的负相关关系,其异常变化(非季节性变化)与我国使用的综合气象干旱指数(CI)、GRACE干旱强度指数(GRACE-DSI)相关性较强(相关系数约为-0.70),而与标准化降水蒸散指数(SPEI)的相关性较弱。相比于CI干旱指数,GPS垂向位移能更好地探测短期降雨急剧减少引起的干旱事件。数据缺失影响了GRACE-DSI探测干旱的准确性,而SPEI的波动较大,且存在高估某些短期降雨严重性的情况。研究结果展示了GPS在干旱监测方面的可靠性和优势。     

GPS坐标时间序列中的异常高频周期性噪声

本文分析了中国地壳运动观测网络GPS基准站及中国周边IGS连续站坐标中的周期性噪声,在北、东和垂向分量坐标时间序列中均发现了周期约351/n(n=1,…,6)天的正弦项,而地表质量负荷造成的位移序列中并没有对应的成分,不能解释异常周期项的来源。在估计台站的运动速率时,如考虑此类"异常"周期项,速率误差略微减小,而周年项振幅的估计误差显著增大,且残差离散度未见明显改善。因此,不推荐在GPS速率矢量反演中加入异常周期项参数。     

基于GPS观测的Baja California地震地壳变形分析

2010-04-04墨西哥Baja California(32.259°N,115.287°W)Ms 7.2级地震发生在GPS连续观测站及钻孔应变仪相当密集的区域,利用GPS监测数据计算出了若干站点地震前后的位移量。地壳变形分析结果表明,离震中近的观测站变形量普遍较大,最大可达0.2m,大部分观测站明显向东南方向运动。通过选择较稳定的观测站作为参考站,计算了4观测站的动态变形序列,同时得到地震波的传播速度为3.2km/s,与应变观测计算结果比较吻合。     

东日本Mw9.0大地震前、同震及震后地壳水平运动

利用“中国地壳运动观测网络(二期)”245个GPS连续观测站及其他站的大量观测结果,采用离震中很远的7个GPS站作为位错参考框架,得到2011年3月11日东日本Mw9.0大地震的同震水平位移和应变。此种参考框架的位移场解,符合弹性位错模型离震中很远且水平位移接近于0的要求,不仅有利于位错模型反演,也有利于合理分析此次大地震同震水平位移的影响范围。地震前后区域参考框架下远场GPS连续观测位移时间序列和同震位移弹性位错模型反演结果表明,东日本大地震同震水平位移既是地震断层破裂的结果,也是远场震前数月或数年水平位移的弹性回跳,据此可以进一步确认这些站震前水平位移前兆异常。由于这些震前异常位移中亦包含了同震位移量(方向相反),因此,弹性位错模型为定量研究大地震前远场地壳运动异常提供了一种理论模型。位错参考框架中的同震位移及其位错模型和区域参考框架的位移时间系列的综合研究有助于对此次大地震地壳运动异常的认识。这种持续时间为数月至数年的弹性形变异常,可以为大地震的中短期预测提供依据。     

High-frequency signal and noise estimates of CSR GRACE RL04

A sliding window technique is used to create daily-sampled Gravity Recovery and Climate Experiment (GRACE) solutions with the same background processing as the official CSR RL04 monthly series. By estimating over shorter time spans, more frequent solutions are made using uncorrelated data, allowing for higher frequency resolution in addition to daily sampling. Using these data sets, high-frequency GRACE errors are computed using two different techniques: assuming the GRACE high-frequency signal in a quiet area of the ocean is the true error, and computing the variance of differences between multiple high-frequency GRACE series from different centers. While the signal-to-noise ratios prove to be sufficiently high for confidence at annual and lower frequencies, at frequencies above 3 cycles/year the signal-to-noise ratios in the large hydrological basins looked at here are near 1.0. Comparisons with the GLDAS hydrological model and high frequency GRACE series developed at other centers confirm CSR GRACE RL04’s poor ability to accurately and reliably measure hydrological signal above 3–9 cycles/year, due to the low power of the large-scale hydrological signal typical at those frequencies compared to the GRACE errors.     

Quantifying FES2004 S<Subscript>2</Subscript> tidal model from multiple space-geodesy techniques,GPS and GRACE,over North West Australia

Unmodeled sub-daily ocean S₂ tide signals that alias into lower frequencies have been detected in the analysis of gravity recovery and climate experiment (GRACE) space gravity fields of GRGS. The most significant global S₂ aliased signal occurs off the northwest coast of Australia in a shallow continental shelf zone, a region with high tidal amplitudes at a period of 161 days. The GRACE S₂ aliased equivalent water height grids are convolved with Green’s functions to produce GRACE aliased tidal loading (GATL) vertical displacements. The analysis of hourly global positioning system (GPS) vertical coordinate estimates at permanent sites in the region confirms the presence of spectral power at the S₂ frequency when the same ocean tide model (FES2004) was used. Thus, deficiencies in the FES2004 ocean tide model are detected both directly and indirectly by the two independent space geodetic techniques. Through simulation, the admittance (ratio of amplitude of spurious long-wavelength output signal in the GRACE time-series to amplitude of unmodeled periodic signals) of the GRACE unmodeled S₂ tidal signals, aliased to a 161-day period, is found to have a global average close to 100%, although with substantial spatial variation. Comparing GATL with unmodeled S₂ tidal sub-daily signals in the vertical GPS time-series in the region of Broome in NW Australia suggests an admittance of 110–130%.     

GPS时间序列与强震预测研究

应用经验正交函数(EOF)分析方法，对中国大陆连续观测的基准站水平位移时间序列进行分析。通过对1999年3月份以来GPS1000周至1258周的原始时间序列的EOF分析、时间序列中除去长期位移速率后的EOF分析、及强震前半年时间段内的时间序列的EOF分析，研究强震前中国大陆水平位移场的时空演化特征及与强震发生的关系。     

环境负载对区域GPS基准站时间序列的影响分析

基于1999-2011年中国地壳运动观测网络(CMONOC)及2007-2012年武汉市连续运行卫星定位服务系统(WHCORS)的观测数据,联合中国及周边35个IGS基准站数据,采用GAMIT软件解算,获得了ITRF2008框架下的GPS基准站坐标时间序列.然后采用QOCA计算了环境负载位移,并利用其对GPS时间序列进行改正.研究结果表明环境负载造成的中国区域基准站位移呈现显著的区域性特征,东北、华北、华中区域变化较为一致且较大,西南区域基准站(KUNM)垂直方向的负载位移均方根(RMS)最大值达6.09 mm.通过对改正前后的数据进行时间序列分析,认为环境负载改正能够削弱中国区域大多数GPS基准站(约70%)垂直及水平东方向位移时间序列的非线性变化,其加权均方根(WRMS)减小量最大达1.5 mm,但是对于水平北方向坐标时间序列的改善作用不明显.     

Very high-rate GPS for measuring dynamic seismic displacements without aliasing: performance evaluation of the variometric approach

Very high-rate global positioning system (GPS) data has the capacity to quickly resolve seismically related ground displacements, thereby providing great potential for rapidly determining the magnitude and the nature of an earthquake’s rupture process and for providing timely warnings for earthquakes and tsunamis. The GPS variometric approach can measure ground displacements with comparable precision to relative positioning and precise point positioning (PPP) within a short period of time. The variometric approach is based on single-differencing over time of carrier phase observations using only the broadcast ephemeris and a single receiver to estimate velocities, which are then integrated to derive displacements. We evaluate the performance of the variometric approach to measure displacements using 50 Hz GPS data, which were recorded during the 2013 M_W 6.6 Lushan earthquake and the 2011 M_W 9.0 Tohoku-Oki earthquake. The comparison between 50 and 1 Hz seismic displacements demonstrates that 1 Hz solutions often fail to faithfully manifest the seismic waves containing high-frequency seismic signals due to aliasing, which is common for near-field stations of a moderate-magnitude earthquake. Results indicate that 10–50 Hz sampling GPS sites deployed close to the source or the ruptured fault are needed for measuring dynamic seismic displacements of moderate-magnitude events. Comparisons with post-processed PPP results reveal that the variometric approach can determine seismic displacements with accuracies of 0.3–4.1, 0.5–2.3 and 0.8–6.8 cm in the east, north and up components, respectively. Moreover, the power spectral density analysis demonstrates that high-frequency noises of seismic displacements, derived using the variometric approach, are smaller than those of PPP-derived displacements in these three components.     

Impact of seasonal station motions on VLBI UT1 intensives results

UT1 estimates obtained from the very long baseline interferometry (VLBI) Intensives data depend on the station displacement model used during processing. In particular, because of seasonal variations, the instantaneous station position during the specific intensive session differs from the position predicted by the linear model generally used. This can cause systematic errors in UT1 Intensives results. In this paper, we first investigated the seasonal signal in the station displacements for the 5 VLBI antennas participating in UT1 Intensives observing programs, along with the 8 collocated GPS stations. It was found that a significant annual term is present in the time series for most stations, and its amplitude can reach 8 mm in the height component, and 2 mm in horizontal components. However, the annual signals found in the displacements of the collocated VLBI and GPS stations at some sites differ substantially in amplitude and phase. The semiannual harmonics are relatively small and unstable, and for most stations no prevailing signal was found in the corresponding frequency band. Then two UT1 Intensives series were computed with and without including the seasonal term found in the previous step in the station movement model. Comparison of these series has shown that neglecting the seasonal station position variations can cause a systematic error in UT1 estimates, which can exceed 1  $\upmu $ s, depending on the observing program.     

Sub-daily noise in horizontal GPS kinematic time series due to thermal tilt of GPS monuments

The sub-daily noise in horizontal global positioning system (GPS) kinematic time series arising from monument tilts is quantitatively evaluated using tiltmeter data at GPS stations from the Japanese nationwide global navigation satellite system network. The estimated tilt-induced monument displacements show characteristics that are typical of those caused by thermal tilts of the monuments. The root mean square of the displacements is typically a few millimetres, with notable inter-seasonal variations. The stacked amplitude spectra of the monument displacements have peaks at the tidal bands S1 and S2, and their higher tones. The peaks at the S1 and S2 bands in the amplitude spectra are reduced by 41 and 43 % for the north–south component and 36 and 53 % for the east–west component, respectively, after correcting for the monument displacements. The monument displacements due to the thermal tilts of the monuments may also be a favourable candidate for sub-daily noise at the S1 and S2 bands found in other GPS networks.     

Comparative analysis of different environmental loading methods and their impacts on the GPS height time series

Three different environmental loading methods are used to estimate surface displacements and correct non-linear variations in a set of GPS weekly height time series. Loading data are provided by (1) Global Geophysical Fluid Center (GGFC), (2) Loading Model of Quasi-Observation Combination Analysis software (QLM) and (3) our own daily loading time series (we call it OMD for optimum model data). We find that OMD has the smallest scatter in height across the selected 233 globally distributed GPS reference stations, GGFC has the next smallest variability, and QLM has the largest scatter. By removing the load-induced height changes from the GPS height time series, we are able to reduce the scatter on 74, 64 and 41 % of the stations using the OMD models, the GGFC model and QLM model respectively. We demonstrate that the discrepancy between the center of earth (CE) and the center of figure (CF) reference frames can be ignored. The most important differences between the predicted models are caused by (1) differences in the hydrology data from the National Center for Atmospheric Research (NCEP) vs. those from the Global Land Data Assimilation System (GLDAS), (2) grid interpolation, and (3) whether the topographic effect is removed or not. Both QLM and GGFC are extremely convenient tools for non-specialists to use to calculate loading effects. Due to the limitation of NCEP reanalysis hydrology data compared with the GLDAS model, the GGFC dataset is much more suitable than QLM for applying environmental loading corrections to GPS height time series. However, loading results for Greenland from GGFC should be discarded since hydrology data from GLDAS in this region are not accurate. The QLM model is equivalent to OMD in Greenland and, hence, could be used as a complement to the GGFC product to model the load in this region. We find that the predicted loading from all three models cannot reduce the scatter of the height coordinate for some stations in Europe.     

Nontectonic signals in reprocessed continuous GPS position time series of CMONOC

The nearly nine-year continuous GPS data collected since 1 March 1999 from the Crustal Motion Observation Network of China (CMONOC) were consistently analyzed. Most of the nonlinear movements in the cumulative position time series produced by CMONOC data center disappeared; and more accurate vertical terms and tectonic signals were extracted. Displacements caused by atmospheric pressure loading, nontidal ocean loading, soil moisture mass loading, and snow cover mass loading using the National Centers for Environmental Prediction (NCEP) Reanalysis I/II models and Estimation of the Circulation and Climate of the Ocean (ECCO) data can explain most of the vertical annual terms at many stations, while only parts can be explained at Lhasa and southern coastal sites, indicating that there are some deformation mechanisms that are still unknown or not modeled accurately. The remarkable differences in vertical position time series for short-baseline sites reveal that GPS stations can be greatly affected by local factors; and attention should be paid when explaining observed GPS velocity vectors.     

Nontectonic signals in reprocessed continuous GPS position time series of CMONOC

The nearly nine-year continuous GPS data collected since 1 March 1999 from the Crustal Motion Observation Network of China(CMONOC) were consistently analyzed.Most of the nonlinear movements in the cumulative position time series pro-duced by CMONOC data center disappeared;and more accurate vertical terms and tectonic signals were extracted.Displacements caused by atmospheric pressure loading,nontidal ocean loading,soil moisture mass loading,and snow cover mass loading using the National Centers for Environmental Prediction(NCEP) Reanalysis I/II models and Estimation of the Circulation and Climate of the Ocean(ECCO) data can explain most of the vertical annual terms at many stations,while only parts can be explained at Lhasa and southern coastal sites,indicating that there are some deformation mechanisms that are still unknown or not modeled accurately.The remarkable differences in vertical position time series for short-baseline sites reveal that GPS stations can be greatly affected by lo-cal factors;and attention should be paid when explaining observed GPS velocity vectors.     

Combination of temporal gravity variations resulting from superconducting gravimeter (SG) recordings, GRACE satellite observations and global hydrology models

Gravity recovery and climate experiment (GRACE)-derived temporal gravity variations can be resolved within the μgal (10^?8 m/s ²) range, if we restrict the spatial resolution to a half-wavelength of about 1,500 km and the temporal resolution to 1 month. For independent validations, a comparison with ground gravity measurements is of fundamental interest. For this purpose, data from selected superconducting gravimeter (SG) stations forming the Global Geodynamics Project (GGP) network are used. For comparison, GRACE and SG data sets are reduced for the same known gravity effects due to Earth and ocean tides, pole tide and atmosphere. In contrast to GRACE, the SG also measures gravity changes due to load-induced height variations, whereas the satellite-derived models do not contain this effect. For a solid spherical harmonic decomposition of the gravity field, this load effect can be modelled using degree-dependent load Love numbers, and this effect is added to the satellite-derived models. After reduction of the known gravity effects from both data sets, the remaining part can mainly be assumed to represent mass changes in terrestrial water storage. Therefore, gravity variations derived from global hydrological models are applied to verify the SG and GRACE results. Conversely, the hydrology models can be checked by gravity variations determined from GRACE and SG observations. Such a comparison shows quite a good agreement between gravity variation derived from SG, GRACE and hydrology models, which lie within their estimated error limits for most of the studied SG locations. It is shown that the SG gravity variations (point measurements) are representative for a large area within the accuracy, if local gravity effects are removed. The individual discrepancies between SG, GRACE and hydrology models may give hints for further investigations of each data series.     

华北地区长期重力变化监测

利用GRACE卫星重力资料,计算了华北地区的长期重力变化结果,利用6个测站的绝对重力观测资料,获取了测站的重力变化时间序列,同时获取了北京、泰安测站的GRACE卫星月重力变化时间序列。卫星重力观测结果显示华北地区地下水流失严重,绝对重力观测结果表明地面沉降严重。     

Empirical modelling of site-specific errors in continuous GPS data

Continuous global positioning system (GPS) stations propagate biases and spurious signals into the derived parameter time series when the measurements are subject to site-specific effects, such as multipath. This is a particular problem in the investigation of geophysical and atmospheric phenomena where signals may be small in magnitude. A methodology to remove these erroneous signals from long-term time series will significantly increase the usefulness of the derived time series. This work provides the theoretical basis for use of an empirical site model (ESM) derived from post-fit phase residuals to mitigate unmodelled site-specific errors. Additionally, we also investigate the effectiveness of applying an ESM to a regional GPS network and a short baseline solution. Under most observing scenarios, we show that the ESM approach is predicted to improve the precision and accuracy of the site coordinates. However, it is important to note that we found some scenarios where the ESM can introduce a bias. For instance, when the antenna is mounted close to the ground. In this scenario, for a short baseline, we observed the introduction of a 4-mm bias in height. Use of an ESM for the same short baseline with an uncalibrated radome substantially improves the results by removing a large bias of over 10 mm in height. Similarly, application of an ESM derived from historic data yields similar improvements. This demonstrates that the ESM can be a powerful tool when applied to appropriate site-specific configurations and could potentially be implemented in routine GPS analysis for a broad range of applications.