Annual variation detected by GPS,GRACE and loading models

Most GPS coordinate time series, surface displacements derived from the Gravity Recovery and Climate Experiment (GRACE), and loading models display significant annual signals at many regions. This paper compares the annual signals of the GPS position time series from the Crustal Dynamics Data Information System (CDDIS), estimates of loading from GRACE monthly gravity field models calculated by three processing centers (Center of Spatial Research, CSR; Jet Propulsion Laboratory, JPL; GeoForschungsZentrum, GFZ) and three geophysical fluids models (National Center for Environmental Prediction, NCEP; Estimating the Circulation and Climate of the Ocean, ECCO; Global Land Data Assimilation System, GLDAS) for 270 globally distributed stations for the period 2003-2011. The results show that annual variations derived from the level-2 products from the three GRACE product centers are very similar. The absolute difference in annual amplitude between any two centers is never larger than 1.25 mm in the vertical and 0.11 mm in horizontal displacement. The mean phase differences of the GRACE results are less than ten days for all three components. When we correct the GPS vertical coordinate time series using the GRACE annual amplitudes using the products from three GRACE analysis centers, we find that we are able to reduce the GPS annual signal in the vertical at about 80% stations and the average reduction is about 47%. In the north and the east, the annual amplitude is reduced on 77% and 72% of the stations with the average reduction 32% and 33%. We also compare the annual surface displacement signal derived from two environmental models; the two models use the same atmospheric and non-tidal ocean loading and differ only in the continental water storage model that we use, either NCEP or GLDAS. We find that the model containing the GLDAS continental water storage is able to better reduce the annual signal in the GPS coordinate time series.     

Global-scale validation of model-based load deformation of the Earth's crust from continental watermass and atmospheric pressure variations using GPS

Temporal mass variations in the continental hydrosphere and in the atmosphere lead to changes in the gravitational potential field that are associated with load-induced deformation of the Earth’s crust. Therefore, models that compute continental water storage and atmospheric pressure can be validated by measured load deformation time series. In this study, water mass variations as computed by the WaterGAP Global Hydrology Model (WGHM) and surface pressure as provided by the reanalysis product of the National Centers for Environmental Prediction describe the hydrological and atmospheric pressure loading, respectively. GPS observations from 14 years at 208 stations world-wide were reprocessed to estimate admittance factors for the associated load deformation time series in order to determine how well the model-based deformation fits to real data. We found that such site-specific scaling factors can be identified separately for water mass and air pressure loading. Regarding water storage variation as computed by WGHM, weighted global mean admittances are 0.74 ± 0.09, 0.66 ± 0.10, 0.90 ± 0.06 for the north, east and vertical component, respectively. For the dominant vertical component, there is a rather good fit to the observed displacements, and, averaged over all sites, WGHM is found to slightly overestimate temporal variations of water storage. For Europe and North America, with a dense GPS network, site-specific admittances show a good spatial coherence. Regarding regional over- or underestimation of WGHM water storage variations, they agree well with GRACE gravity field data. Globally averaged admittance estimates of pre-computed atmospheric loading displacements provided by the Goddard Geodetic VLBI Group were determined to be 0.88 ± 0.04, 0.97 ± 0.08, 1.13 ± 0.01 for the north, east and vertical, respectively. Here, a relatively large discrepancy for the dominant vertical component indicates an underestimation of corresponding loading predictions.     

Loading effects in Metsähovi from the atmosphere and the Baltic Sea

Loading by atmosphere and by the Baltic Sea cause gravity change at Metsähovi, located 15 km from the open sea. Gravity is changed by both the Newtonian attraction of the loading mass and by the crustal deformation. We have performed loading calculations using appropriate Green's function for both gravity and deformation, for both atmospheric and Baltic loading. The loading by atmosphere has been computed using a detailed surface pressure field from high resolution limited area model (HIRLAM) for north Europe up to 10° distances. Baltic Sea level is modelled using tide gauge records. Calculations show that 1 m of uniform layer of water corresponds to 31 nm s⁻² in gravity and −11 mm in height. Modelled loading is compared with observations of the superconducting gravimeter T020 for years 1994–2002. The combination of HIRLAM and a tide gauge record decreases RMS of gravity residuals by 14% compared to single admittance in air pressure corrections without sea level data. Regression of gravity residuals on the tide gauge record at Helsinki (at 30 km distance) gives a gravity effect of 26 nm s⁻² m⁻¹ for Baltic loading.The gravity station is co-located with a permanent GPS station. We have also associated the loading effects of the atmosphere and of the Baltic Sea with temporal height variations. The range of modelled vertical motion due to air pressure was 46 mm and that due to sea level 18 mm. The total range was 38 mm. The effects of the Baltic Sea and of the atmosphere partly cancel each other, since at longer periods the inverse barometer assumption is valid. Regression of the modelled height on local air pressure gives −0.37 mm hPa⁻¹, corresponding approximately to width 6° for pressure system.We have tested the models using one year of daily GPS data. Multilinear regression on local air pressure and sea level in Helsinki gives the coefficient −0.34 mm hPa⁻¹ for pressure, and −11 mm m⁻¹ for sea level. These match model values. Loading by air pressure and Baltic Sea explains nearly 40% of the variance of daily GPS height solutions.     

武汉九峰地震台超导重力仪观测分析研究

连续重力观测和GPS的技术结合能够监测到物质迁移和地壳垂直形变之间的量化关系.和相对重力测量以及绝对重力测量技术相比,其避免了时间分辨率和观测精度低,无法精细描述观测周期内的物质迁移过程问题.本文利用武汉九峰地震台超导重力仪SGC053超过13000 h连续重力观测数据;同址观测的绝对重力仪观测结果;气压数据;周边GPS观测结果;GRACE卫星的时变重力场;全球水储量模型等资料,采用同址观测技术、调和分析法、相关分析方法在扣除九峰地震台潮汐、气压、极移和仪器漂移的基础上,利用重力残差时间序列和GPS垂直位移研究物质迁移和地壳垂直形变之间的量化关系.结果表明:在改正连续重力观测数据的潮汐、气压、极移的影响后,不仅准确观测到2009年的夏秋两季由于水负荷引起的约(6~8)×10^-8m·s^-2短期的重力变化.而且在扣除2.18×10^-8(m·s^-2)/a仪器漂移和水负荷的影响后,验证了本地区长短趋势垂直形变和重力变化之间具有一致的负相关性规律.同时长趋势表明该地区地壳处于下沉,重力处于增大过程,增加速率约为1.79×10^-8(m·s^-2)/a.武汉地区重力梯度关系约为-354×10^-8(m·s^-2)/m.     

Geodetic observation of sea-level change and crustal deformation in the Baltic Sea region

Based on tide gauge observations spanning almost 200 years, homogeneous time series of the mean relative sea level were derived for nine sites at the southern coast of the Baltic Sea. Our regionally concentrated data were complemented by long-term relative sea-level records retrieved from the data base of the Permanent Service for Mean Sea Level (PSMSL). From these records relative sea-level change rates were derived at 51 tide gauge stations for the period between 1908 and 2007. A minimum observation time of 60 years is required for the determination of reliable sea-level rates. At present, no anthropogenic acceleration in sea-level rise is detected in the tide gauge observations in the southern Baltic. The spatial variation of the relative sea-level rates reflects the fingerprint of GIA-induced crustal uplift. Time series of extreme sea levels were also inferred from the tide gauge records. They were complemented by water level information from historic storm surge marks preserved along the German Baltic coast. Based on this combined dataset the incidence and spatial variation of extreme sea levels induced by storm surges were analysed yielding important information for hazard assessments. Permanent GPS observations were used to determine recent crustal deformation rates for 44 stations in the Baltic Sea region. The GPS derived height change rates were applied to reduce the relative sea-level changes observed by tide gauges yielding an estimate for the eustatic sea-level change. For 13 tide gauge-GPS colocation sites a mean eustatic sea-level trend of 1.3 mm/a was derived for the last 100 years.     

利用GPS与GRACE监测陆地水负荷导致的季节性水平形变：以喜马拉雅山地区为例

地表陆地水负荷变化是引起重力场和地壳形变呈现季节性特征的主要因素,并且能够利用地表及空间大地测量技术对其进行有效的监测.本文通过对质量负荷形变效应的理论模拟,描述了水平分量的形变指向以及垂直与水平分量的幅值比可以提高对负荷区域的辨别程度,并且联合GPS坐标时间序列及GRACE模型对喜马拉雅山地区的季节性负荷形变进行了详细对比分析,研究结果显示两者垂直分量的季节性变化具有较好的一致性,且GPS周年项幅值要大于GRACE.而由GRACE解算得到的水平分量结果表明该地区季节性形变主要受东南亚及印度东北部地区的陆地水负荷控制,位于喜马拉雅山地区多数GPS台站的垂直分量及北向分量的初相位与GRACE模型解算结果相近,而部分GPS台站的东向分量与GRACE模型存在明显不同,由此导致GPS与GRACE监测到的形变指向存在差异.通过对GRACE估算精度以及GPS垂直与水平分量幅值比的深入分析,发现GPS对局部周边地区的河流、谷地及农田灌溉等负荷变化造成的形变效应较为敏感,而GRACE由于截断阶次及平滑滤波等影响因素,不仅造成在水平分量上的分辨率远低于垂直分量,而且整体估算精度要低于GPS观测得到的形变信息.     

Seasonal effects of non-tidal oceanic mass shifts in observations with superconducting gravimeters

In order to achieve a consistent combination of terrestrial and satellite-derived (GRACE) gravity field variations reductions of systematic perturbations must be applied to both data sets. At the same time evidence needs to be provided that these reductions are both necessary and sufficient. Based on the OMCT and the ECCO model the gravity effect of non-tidal oceanic mass shifts is computed for various sites equipped with a superconducting gravimeter (SG) and esp. the long-periodic contributions are studied. With these oceanic models the dynamic ocean response to atmospheric pressure loading is automatically computed, and thus goes beyond the more simplistic concepts of an inverted barometer, or alternately a rigid ocean, which is a clear advantage.The findings so far are ambiguous: for instance the systematic seasonal change of about 10 nm/s² in gravity for mid-European stations is presently not found in the observed gravity variations. Generally, the order of magnitude of the total effect of 22–27 nm/s² is surprisingly large for inland stations. In some data sections the reduction leads to the removal of some of the larger residuals. The results obtained for the South-African station Sutherland differ. Here the modelled seasonal variation caused by the non-tidal oceanic mass redistribution and gravity residuals generally correlate, and thus by the reduction an improvement of the signal-to-noise ratio in the gravity observations is achieved.An explanation for the different results might be found in the global hydrological models. Such a model is needed in order to remove the effect of large-scale variations in continental water storage in the gravity observations. This reduction plays a greater role for European stations than for the South African site. A critical impact of the land-sea-mask used in the oceanic models and the subsequent insufficient resolution of the North and Baltic Sea on the computations at the mid-European sites could not be confirmed.From a comparison between the OMCT and the ECCO model substantial discrepancies in some regions of the earth emerge, while both predict variations at inland stations in Europe, South Africa, and Asia of similar magnitude. We currently hesitate to recommend including this reduction in the routine processing of SG data because the seasonal order of magnitude for inland stations is unexpectedly large and partly significant deviations between the modelled oceanic effects exist. If the order of magnitude proves to be correct universally, this reduction has to be applied.     

The effect of the Baltic Sea level on gravity at the Metsähovi station

The loading effect of the Baltic Sea is immediately recognizable in the gravity record of the superconducting gravimeter T020 in Metsähovi, Finland, by simply inspecting residual gravity together with the tide gauge record at Helsinki 30 km away. The station is 10 km from the nearest bay of the Baltic Sea and 15 km from the open sea. Sea level variations in the Baltic are non-tidal and driven at short periods primarily by wind stress, at longer periods by water exchange through the Danish straits. Locally they can have a range of 2–3 m. Loading calculations show that a uniform layer of water covering the complete Baltic Sea increases the gravity in Metsähovi by 31 nm/s² per 1 m of water, and the vertical deformation is −11 mm. The observed gravity response to the local sea level is generally less, since the variations at short periods are far from uniform areally, the same water volume just being redistributed to different places. Regression of the whole gravity record (1994-2001) on local sea level gives 50–70% of the uniform layer response, as do loading calculations using actual water distributions derived from 11 tide gauges. However, both fits are dominated by some extreme values of short duration, and parts of the gravity record with long-period variations in sea level are close to the uniform layer response. The gravity observations can be used to test corrections for other co-located geodetic observations (GPS, satellite laser ranging) which are influenced by the load effect but not sensitive enough to discriminate between models.     

应用GPS数据和Slepian基函数反演川云渝地区陆地水储量变化

局部Slepian函数是将局部区域内的地球物理信号转化为空间谱的一种方法,其可以保证在球面上局部范围内获得最优谱平滑解,非常适用于局部范围地球物理信号的研究.本文利用中国陆态网西南地区72个测站的连续GPS观测资料分析川云渝地区陆地水负荷形变特征,并基于Slepian函数方法解算60阶的空间谱基函数,结合弹性质量负荷理论研究了川云渝地区2011年至2015年陆地水储量变化的时空分布模式.针对Slepian函数的边界效应问题,本文使用GLDAS格网数据计算得到站点处垂直负荷位移时间序列,然后利用该位移数据来进行水储量变化恢复实验,结果表明当边界扩充为3°时能较好地恢复GLDAS模型输出的陆地水储量变化.通过对比区域内GPS、GRACE、GLDAS得到的等效水高以及降雨数据,发现季节性降水是陆地水变化的一个重要驱动因子,GPS反演结果与GRACE和GLDAS数据具有较强的空间一致性.云南地区周年变化要强于川渝地区,其中云南西部的山区陆地水变化最大,约为30 cm,最小为川北以及重庆地区仅为7 cm.相较于GPS反演结果,GRACE与GLDAS明显低估了陆地水储量的季节性变化,分别达到24%和47%.比较分析地区内平均等效水高时间序列的相位发现,GPS得到的陆地水变化与降雨数据一致性较好,而GRACE与GLDAS存在一到两个月左右的时延.同时GPS能较好的探测出2015年1月左右南方地区大范围的强降水,而GRACE与GLDAS并没有体现出该现象,说明GPS能更为灵敏地探测到局部地区陆地水的变化.在站点等效水高时间序列上,GPS与GRACE的相关性总体上要优于GPS与GLDAS,陆地水周年变化较大的云南和四川西部地区站点三种数据间相关性较好,而其他季节性信号不明显的地区则相关性较差.本文的研究表明运用GPS-Slepian方法能够独立地监测高时空分辨率的陆地水储量变化,是作为当前补充GRACE观测资料空缺期的有益尝试.     

滇西地区GPS时间序列中陆地水载荷形变干扰的GRACE分辨与剔除

利用“中国大陆构造环境监测网络”在云南西部地区的13个连续GPS观测站和法国空间大地测量研究组Space Geodesy Research Group）的GRACE时变重力场资料,定量分析了该区域陆地水载荷所产生的非构造形变的量值和变化特点,探讨了利用GRACE分辨和剔除GPS观测中陆地水负荷所引起的非构造形变干扰的依据和模型.结果表明：滇西地区GPS坐标变化时间序列的垂向分量中,普遍包含有明显的年周期非构造形变波动,高值可达12mm,其中约42%源于陆地水迁徙变化所引起的负荷形变;通过主成份分析方法所获取的区域GPS共模误差与GRACE陆地水载荷形变序列的相关性高达0.87,若以GRACE扣除陆地水负荷形变,则滇西地区GPS网共模误差可消除约64%,且物理机制明确.然而,由于目前的GRACE只能有效分辨大约400km范围内陆地水载荷的整体变化,所以对于各GPS站点更加局部化的陆地水负荷非构造形变干扰,尚无法进行有效分辨.     

北京天津地区垂直形变剖面复测结果的GPS检验

利用北京和天津地区的28个GPS连续观测站资料（资料截至2008年8月）计算得到的垂直向时序结果,分析各个GPS连续观测站垂向分量的变化特征,计算得到2007～2008年北京天津地区GPS站垂直运动速率,并与水准测量计算得到的2007～2008首都圈地区垂直形变速率进行比较;通过寻找水准测量路线附近的GPS站点,相应于水准的初测和复测时段,计算得到GPS路线剖面图,将GPS与水准2个时段的剖面结果进行对比分析。通过水准和GPS结果的这种“由面到线”的综合比较分析,得出初步的结论：从趋势上看,GPS与水准的结果是相似的,GPS结果同样反映了2008年北京东南附近区域有隆升的迹象,但量值比水准结果小,水准结果所反映的“南升北降”的特征在GPS结果中得到一定程度的验证和体现。     

非构造形变对GPS连续站位置时间序列的影响和修正

GPS观测得到的地壳形变场通常包含有构造形变与非构造形变二类信息, 去除其中的非构造形变信息对于有效运用GPS数据研究构造形变场至关重要. 本文运用国际卫星对地观测资料及各类地球物理模型, 定量计算海潮、大气、积雪和土壤水、海洋非潮汐4项负荷效应造成的地壳非构造形变, 并以此研究和修正这些非构造形变对中国地壳运动观测网络GPS基准站位置时间序列的影响. 研究发现此4项负荷效应, 特别是大气、积雪和土壤水, 对于测站垂向位置的影响显著. 通过模型改正可以使测站垂向位置的RMS降低～1 mm, 占其总量的～11％. 对于垂向时间序列的周年项部分, 这一改正可降低其振幅的37％. 研究还表明经过地球物理模型改正和周年、半周年谐波拟合改正的时间序列比起仅经过周年、半周年谐波拟合改正的时间序列更为平滑, 表明地球物理模型改正对于消除非构造形变场的作用不是周年、半周年谐波拟合改正所能替代的.     

中国区域IGS基准站坐标时间序列非线性变化的成因分析

GPS坐标时间序列呈现显著的季节性变化,通常认为大气压、非潮汐海洋负载及水文负载(统称为地表质量负载)是引起测站谐波变化的主要因素.本文计算了不同地表质量负载造成的测站位移,以此修正中国区域11个IGS基准站的坐标时间序列.建立了地球物理现象与测站季节性变化及噪声特性之间的初步数值联系,认为其会造成测站的噪声特性变化,主要表现为带通及随机漫步噪声特征,且仅能减小测站U分量的周年运动,但并不是造成测站U分量半周年运动及水平方向周年运动的主要原因.深入分析了造成中国区域IGS基准站非线性变化的其他可能因素,重点探讨了周日(S1)、半周日(S2)大气潮汐对基准站周年振幅的贡献,由此提出S1、S2大气潮汐是造成中国区域IGS基准站周年运动,尤其是中南部测站垂向周年运动的主要因素之一.     

An estimate of the influence of loading effects on tectonic velocities in the Pyrenees

Surface displacements due to temporal changes in environmental mass redistributions are observable in the coordinate time series of many Global Navigation Satellite System (GNSS) sites. In this study, we investigated the effect of loading on estimates of tectonic velocity computed from campaign-style GNSS observations. The study region is in the Pyrenees mountain range between France and Spain (ResPyr campaigns). In this area, seismic activity is continuous and moderate and the expected amplitude of the horizontal tectonic velocity is less than 0.5 mm/yr. In order to determine the velocity, 4 sparse GNSS campaigns were carried out from 1995 to 2010. Considering this small rate of deformation, loading phenomena can contribute a non-negligible artifact to the velocity computation that could affect our geodynamical interpretation. In this investigation, we specifically considered the atmospheric, hydrological, and non-tidal ocean loading phenomena. The computed loading deformations for this region show the horizontal displacements are dominated by the non-tidal ocean loading (maximum 4 mm for the North and 3.1 mm for the East components); the main vertical contributions are due to the atmospheric and continental water storage loading (maximum 14.3 for the atmosphere and 8.1 mm for the hydrology, respectively). We have found that the dominant loading effect on the horizontal velocity is the non-tidal ocean loading (mean of 0.11 mm/yr), whereas the vertical component is dominated by the hydrological loading (mean of 0.21 mm/yr). Since the study area is in a mountainous region, we also analyzed the difference between the atmospheric and the topography dependent atmospheric loading models at our GNSS campaign sites. We did not find any significant difference between the two atmospheric loading models in terms of horizontal velocity. Finally, we performed simulations to identify the optimum timing and frequency of future GNSS campaigns in this area that would minimize the loading effects on tectonic velocity estimates.     

利用GPS与环境负荷形变数据研究台风引起的垂向地表位移

台风造成的强降雨、低气压、海面高度变化均会引起地表的形变.本文利用中国大陆构造环境监测网(陆态网)7个GPS台站每日的垂向位移和环境负荷形变模型分析2018年9月10—26日台风"山竹"期间不同负荷引起的区域垂向地表形变.结果表明,台风期间大气负荷和非潮汐海洋负荷垂向形变最大分别达到5.1 mm和-9.2 mm.模型能较好地反映河流区域地表水文负荷变化造成的垂向形变,但不同模型之间存在系统偏差.由于缺少地下水等信息,模型反映负荷长期形变效应的效果不佳,且形变的量级明显小于GPS观测的结果.迅速增加的水文负荷使北海GPS站从开始下沉到最低点(-15.6 mm)5天的下沉量达到25.7 mm;珠海、广州GPS站均观测到河流汇水作用造成地表的二次下沉,且珠海站一周后才抬升到正常位置;湛江和北海GPS站能较好地反映河流水位变化,相关系数分别为-0.66和-0.50.研究结果表明,相比于形变模型,GPS能更有效地监测台风短期水文负荷形变,可为台风洪水等灾害监测与预报提供有用的信息.     

Local and global hydrological contributions to gravity variations observed in Strasbourg

We investigate the contribution of local and global hydrology to the superconducting gravimeter (SG) installed in the Strasbourg observatory. A deterministic approach is presented to account for the contribution of water storage variations in the soils in the vicinity of the gravimeter: both amount and distribution of water masses are determined before calculating Newtonian attraction. No adjustment is performed on gravity time series.Two multi-depth Frequency Domain Reflectometer (FDR) probes have been installed to monitor the amount of water stored in the soil layer above the gravimeter. Since August 2005, they have been monitoring the variation of the water content of the entire soil thickness. Several investigations have been undertaken in order to estimate the distribution of water masses: a precise local DEM (Digital Elevation Model) has been determined using differential GPS. The geometry and heterogeneity of the soil layer have been evaluated thanks to geophysical and geomechanical prospections. The comparison between observed and modelled gravity variations shows that daily up to seasonal variations are in good agreement. For long-term variations, deep water storage and other processes have to be modelled to explain recorded gravity variations.     

Seasonal Water Storage Variations as Impacted by Water Abstractions: Comparing the Output of a Global Hydrological Model with GRACE and GPS Observations

Better quantification of continental water storage variations is expected to improve our understanding of water flows, including evapotranspiration, runoff and river discharge as well as human water abstractions. For the first time, total water storage (TWS) on the land area of the globe as computed by the global water model WaterGAP (Water Global Assessment and Prognosis) was compared to both gravity recovery and climate experiment (GRACE) and global positioning system (GPS) observations. The GRACE satellites sense the effect of TWS on the dynamic gravity field of the Earth. GPS reference points are displaced due to crustal deformation caused by time-varying TWS. Unfortunately, the worldwide coverage of the GPS tracking network is irregular, while GRACE provides global coverage albeit with low spatial resolution. Detrended TWS time series were analyzed by determining scaling factors for mean annual amplitude (f _GRACE) and time series of monthly TWS (f _GPS). Both GRACE and GPS indicate that WaterGAP underestimates seasonal variations of TWS on most of the land area of the globe. In addition, seasonal maximum TWS occurs 1 month earlier according to WaterGAP than according to GRACE on most land areas. While WaterGAP TWS is sensitive to the applied climate input data, none of the two data sets result in a clearly better fit to the observations. Due to the low number of GPS sites, GPS observations are less useful for validating global hydrological models than GRACE observations, but they serve to support the validity of GRACE TWS as observational target for hydrological modeling. For unknown reasons, WaterGAP appears to fit better to GPS than to GRACE. Both GPS and GRACE data, however, are rather uncertain due to a number of reasons, in particular in dry regions. It is not possible to benefit from either GPS or GRACE observations to monitor and quantify human water abstractions if only detrended (seasonal) TWS variations are considered. Regarding GRACE, this is mainly caused by the attenuation of the TWS differences between water abstraction variants due to the filtering required for GRACE TWS. Regarding GPS, station density is too low. Only if water abstractions lead to long-term changes in TWS by depletion or restoration of water storage in groundwater or large surface water bodies, GRACE may be used to support the quantification of human water abstractions.     

环境负载对云南地区基准站时间序列的噪声模型特性研究

以云南地区27个GPS基准站坐标时间序列为研究对象,使用赤池信息量和贝叶斯信息量估计准则（AIC/BIC）对其进行噪声分析,计算并扣除时间序列中大气负载、非潮汐海洋负载和水文负载3种环境负载引起的位移量,得到各基准站分量在环境负载改正前后的最优噪声模型。结果表明,部分基准站分量经过负载改正后最优噪声模型会发生变化,改正前后的大部分基准站噪声特性均体现为闪烁+白噪声和幂律噪声。环境负载对基准站的垂向位移影响比水平向更为显著,水文负载成为影响基准站的最大因素,最大位移量达到厘米级。分析环境负载改正前后噪声特性的变化表明,环境负载改正在U分量上的影响最大,N分量次之,E分量最小,噪声模型的变化在地域上并未呈现明显规律。     

利用GPS和GRACE分析四川地表垂向位移变化

陆地水储量的季节性变化是导致地表周期性负荷形变位移的主要因素,有效地剔除地表位移中的陆地水储量影响,是获取地壳构造垂向运动的必要过程.四川地处青藏高原东边缘,地形分区明显,境内以长江水系为主,水资源丰富,研究四川地区地表负荷形变位移,有助于分析陆地水储量的时空分布特性及地壳构造形变信息.本文利用研究区域内59个CORS站的GPS观测数据,计算了CORS站点的垂向位移,并将其与GRACE所得相应结果进行对比分析.结果显示,GPS和GRACE所得垂向位移时间序列的振幅大小整体相符,但存在明显的相位差.GPS站点振幅最大值为12.7 mm,对应HANY站,最小值为1.5 mm,对应SCMX站.GRACE所得的地表垂向位移振幅大小均为3~4 mm,且最大位移集中出现在7-9月份;而GPS站点出现最大位移的月份和地形相关,东部盆地、西北部高原和南部山地分别出现在7-8月份、10-11月份和10月份.GPS站点时间序列中的周年项与陆地水的季节性变化强相关,为了讨论陆地水储量对GPS站点位移的影响,本文利用改进的总体经验模态分解方法（MEEMD：Modified Ensemble Empirical Mode Decomposition）,从GPS垂向位移时间序列中提取出周年项及约2年的年际变化项.发现利用MEEMD获取的周年项改正原始GPS时间序列时可使其WRMS（Weight Root Mean Square）减少量减小约26%,结果优于最小二乘拟合方法提取的GPS周年项改正效果,验证了MEEMD方法在GPS坐标时间序列处理中的可行性及有效性.     

Determination of vertical displacements over the coastal area of Korea due to the ocean tide loading using GPS observations

This paper describes the GPS applicability for detecting the vertical displacements of ground stations caused by ocean tide loading effects. An experiment was carried out using 12 permanent GPS stations located in the coastal area of Korea using data in the period 1 July until 26 August 2003. The relative height differences were calculated from hourly DGPS data processing based on the carrier-phase observation. The power spectra of the M₂ and N₂ constituents of ocean tide loading were derived using the CLEAN algorithm. The differential vertical displacements generated by the ocean tide loading effect are typically 3–25 mm in coastal area of the Korea. We compared the results from GPS with those of the ocean tide models, NAO.99Jb regional model and GOT00.2, FES99 global models. The M₂ (N₂) amplitude differences of vertical displacements between GPS and GOT00.2 is 1.22 ± 3.61 mm (1.01 ± 1.48 mm), and that of the M₂ (N₂) amplitude difference between GPS and FES99 is 0.04 ± 4.64 mm (0.64 ± 1.75 mm), whereas the M₂ (N₂) amplitude difference between GPS and NAO.99Jb are 0.05 ± 1.03 mm (0.86 ± 1.18 mm). The highest vertical displacements at the PALM station are found for 24.5 ± 0.7 mm from GPS observation, and 22.9 mm from the regional model NAO.99Jb and 13.17 and 10.00 mm from the global models GOT00.2 and FES99, respectively. These values show that the vertical displacements derived from GPS are in good agreement with those of the regional model NAO.99Jb around Korea, more than with the global models. This result indicated that GPS is an effective tool to measure the vertical displacement caused by the ocean tide loading effect in the coastal area, and we need to use the NAO.99Jb ocean tide model rather than the global ocean tide models in and around the Korean peninsula for position determination with permanent GPS installations. This work demonstrates that vertical displacement caused by the M₂ and N₂ constituents of ocean tide loading can be measured by carrier-phase DGPS.