Significance of secular trends of mass variations determined from GRACE solutions

Since 2002 the Earth’s gravity field is globally observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission. The GRACE monthly gravity field solutions, available from several analysis centres, reflect mass variations in the atmosphere, hydrosphere and geosphere. Due to correlated noise contained in these solutions, it is, however, first necessary to apply an appropriate filtering technique. The resulting, smoothed time series are applied not only to determine variations with different periodic signatures (e.g., seasonal, short and medium-term), but to derive long-periodic mass variations and secular trends as well. As the GRACE monthly solutions always show the integral effect of all mass variations, for separation of single processes, like the GIA (Glacial isostatic adjustment)-related mass increase in Fennoscandia, appropriate reduction models (e.g. from hydrology) are necessary.In this study we show for the example of the Fennoscandian uplift area that GRACE solutions from different analysis centres yield considerably different secular trends. Furthermore, it turns out that the inevitable filtering of the monthly gravity field models affects not only the amplitudes of the signals, but also their spatial resolution and distribution such as the spatial form of the detected signals. It also becomes evident that the determination of trends has to be performed together with the determination of periodic components. All periodic terms which are really contained in the data, and only such, have to be included. The restricted time span of the available GRACE measurements, however, limits the separation of long-periodic and secular signals. It is shown that varying the analysis time span affects the results considerably. Finally, a reduction of hydrological signals from the detected integral secular trends using global hydrological models (WGHM, LaDWorld, GLDAS) is attempted. The differences among the trends resulting from different models illustrate that the state-of-the-art hydrology models are not suitable for this purpose as yet. Consequently, taking the GRACE monthly gravity field solutions from one centre, choosing a single filter and applying an insufficiently reliable reduction model leads sometimes to a misinterpretation of considered geophysical processes. Therefore, one has to be cautious with the final interpretation of the results.     

Seismologic applications of GRACE time-variable gravity measurements

The Gravity Recovery and Climate Experiment (GRACE) has been measuring temporal and spatial variations of mass redistribution within the Earth system since 2002. As large earthquakes cause significant mass changes on and under the Earth’s surface, GRACE provides a new means from space to observe mass redistribution due to earthquake deformations. GRACE serves as a good complement to other earthquake measurements because of its extensive spatial coverage and being free from terrestrial restriction. During its over 10 years mission, GRACE has successfully detected seismic gravitational changes of several giant earthquakes, which include the 2004 Sumatra–Andaman earthquake, 2010 Maule (Chile) earthquake, and 2011 Tohoku-Oki (Japan) earthquake. In this review, we describe by examples how to process GRACE time-variable gravity data to retrieve seismic signals, and summarize the results of recent studies that apply GRACE observations to detect co- and post-seismic signals and constrain fault slip models and viscous lithospheric structures. We also discuss major problems and give an outlook in this field of GRACE application.     

Retrieval of Large-Scale Hydrological Signals in Africa from GRACE Time-Variable Gravity Fields

Since its launch in April 2002, the Gravity Recovery and Climate Experiment (GRACE) mission is recording the Earth’s time-variable gravity field with temporal and spatial resolutions of typically 7–30?days and a few hundreds of kilometers, allowing the monitoring of continental water storage variations from both continental and river-basin scales. We investigate here large scale hydrological variations in Africa using different GRACE spherical harmonic solutions, using different processing strategies (constrained and unconstrained solutions). We compare our GRACE estimates to different global hydrology models, with different land-surface schemes and also precipitation forcing. We validate GRACE observations through two different techniques: first by studying desert areas, providing an estimate of the precision. Then we compare GRACE recovered mass variations of main lakes to volume changes derived from radar altimetry measurements. We also study the differences between different publicly available precipitation datasets from both space measurements and ground rain gauges, and their impact on soil-moisture estimates.     

利用SWARM卫星高低跟踪探测格陵兰岛时变重力信号

GRACE重力卫星任务即将结束,后续GRACE Follow-On卫星计划于2017年发射,在此期间,迫切需要一个新的卫星计划继续对全球时变重力场进行连续监测,以保证时变重力场信息时间序列的连贯性.SWARM计划包括三颗轨道高为300~500 km的近极轨卫星星座,类似于三颗CHAMP卫星,具有接替时变重力场探测的潜力.本文首先分析SWARM(模拟)、CHAMP、GRACE反演至60阶时变重力场球谐系数的误差特性及不同高斯平滑半径对高频误差的抑制效果,然后分别利用SWARM、CHAMP、GRACE的时变重力场模型恢复全球质量变化,结果表明,SWARM模拟观测数据的高频误差低于CHAMP观测数据,探测时变重力场的整体精度优于CHAMP,略低于GRACE探测精度;其次,对比2003年1月—2009年12月期间CHAMP(hl-SST)和GRACE(ll-SST)时变重力场模型反演格陵兰岛冰盖质量变化趋势,结果显示,CHAMP数据得到格陵兰岛冰盖质量变化趋势为-50.2±2.0 Gt/a,GRACE所得结果为-41.2±1.6 Gt/a,两者相差21.8%;最后,对比2000年1月—2004年12月间SWARM模拟数据和"真实"模型数据反演的格陵兰岛冰盖质量变化趋势,结果表明,两者相差19.2%.本文研究表明,利用SWARM hl-SST数据探测时变重力场可以达到20%相对精度水平,有潜力用于填补GRACE和GRACE Follow-On期间探测地球时变重力场的空白.     

利用动力学方法解算GRACE时变重力场研究

本文利用动力学方法建立GRACE(Gravity Recovery And Climate Experiment)K波段距离变率(KBRR)观测、轨道观测与重力场系数的观测方程,通过GRACE Level 1B观测数据,成功解算出全球月时变重力场模型——IGG时变重力场模型,并将2008—2009年的解算结果与GRACE三大数据处理机构美国德克萨斯大学空间中心CSR(Center for Space Research)、美国宇航局喷气推进实验室JPL(Jet Propulsion Laboratory)和德国地学研究中心GFZ(GeoForschungs Zentrum)发布的最新全球时变重力场模型进行详细对比分析.结果表明:IGG结果在全球质量异常、中国及周边地区质量异常的趋势变化、全球质量异常均方差、2~60每阶位系数差值以及亚马逊流域和撒哈拉沙漠等典型区域平均质量异常等方面与CSR、JPL和GFZ解算的RL05结果较为一致.其中,IGG解算结果在2~20阶与CSR、GFZ和JPL最新解算结果基本一致,20~40阶IGG解算结果与GFZ、JPL单位最新解算结果较为接近,大于40阶IGG结果介于CSR与GFZ、JPL之间;亚马逊流域平均质量异常周年振幅IGG、CSR、GFZ和JPL获取到的结果分别为17.6±1.1cm、18.9±1.2cm、17.8±0.9cm和18.9±1.0cm等效水柱高.利用撒哈拉沙漠地区的平均质量异常做反演精度评定,IGG、CSR、GFZ和JPL的时变重力场获取到的平均质量异常均方差分别为1.1cm、0.9cm、0.8cm和1.2cm,表明IGG解算结果与CSR、GFZ和JPL最新发布的RL05结果在同一精度水平.     

Tackling mass redistribution phenomena by time-dependent GRACE- and terrestrial gravity observations

Time variable gravity field models derived from the satellite mission GRACE have been demonstrated to be consistent with water mass variations in the global hydrological cycle. Independent observations are provided by terrestrial measurements. In order to achieve a maximum of reliability and information gain, ground-based gravity observations may be deployed for comparison with the gravity field variations derived from the GRACE satellite mission. In this context, the data of the network of superconducting gravimeters (SG) of the ‘Global Geodynamics Project’ (GGP) are of particular interest. This study is focused on the dense SG network in Central Europe with its long-term gravity observations. It is shown that after the separation and reduction of local hydrological effects in the SG observations especially for subsurface stations, the time-variable gravity signals from GRACE agree well with the terrestrial observations from the SG station cluster.Station stability of the SG sites with respect to vertical deformations was checked by GNSS based observations. Most of the variability can be explained by loading effects due to changes in continental water storage, and, in general, the stability of all stations has been confirmed.From comparisons based on correlation and coherence analyses in combination with the root mean square (RMS) variability of the time series emerges, that the maximum correspondence between the SG and GRACE time series is achieved when filtering the GRACE data with Gaussian filters of about 1000 km filter length, which is in accordance with previous publications.Empirical Orthogonal Functions (EOF) analysis was applied to the gravity time series in order to identify common characteristic spatial and temporal patterns. The high correspondence of the first modes for GRACE and SG data implies that the first EOF mode represents a large-scale (Central European) time-variable gravity signal seen by both the GRACE satellites and the SG cluster.     

Gravity field variations from superconducting gravimeters for GRACE validation

The network of superconducting gravimeters (SG) of the ‘Global Geodynamics Project’ (GGP) offers the unique opportunity to supplement and validate the gravity field variations derived from the GRACE satellite mission. Because of the different spatial and temporal resolutions of the gravity data a combination of all datasets can be used to retrieve a maximum of information regarding mass transfers especially related to hydrology which is deployable as constraint for hydrological modelling.For a consistent combination of the datasets the gap between terrestrial data of superconducting and absolute gravimeters (AG) and from satellite data has to be bridged. A successful combination of SG and AG data could be realized for several stations which resulted in time series of the highest accuracy and long-term stability.In principle, the same reductions applied to GRACE data have to be taken into account for the terrestrial data. The separation of local hydrological effects in SG observations is crucial for the comparison with satellite-derived gravity data. It is shown that even for stations with a hydrological challenging situation such as Moxa/Germany local hydrology-induced effects can be successfully modelled.Currently, the study focuses on Europe with its dense and long-term observation network. Regarding the consistency of the SG gravity variations they are representative for a larger region. From a comparison with GRACE-derived gravity field changes, and the variations due to hydrological models a principle good agreement emerges.     

Seasonal water storage change of the Yangtze River basin detected by GRACE

1 Introduction Large-scale mass redistribution, or temporal varia- tion of mass within the Earth system, the driving force of interactions between solid Earth and geophysical fluids envelope (i.e., atmosphere, ocean, and hydro- sphere), is an important geophysical process critical to human life. Most of the interactions between solid Earth and the atmosphere/oceans happen at seasonal and inter-annual time scales. One important contribu- tor of mass redistribution at seasonal and inter-annual …     

Comparison of Daily GRACE Gravity Field and Numerical Water Storage Models for De-aliasing of Satellite Gravimetry Observations

Reducing aliasing effects of insufficiently modelled high-frequent, non-tidal mass variations of the atmosphere, the oceans and the hydrosphere in gravity field models derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission is the topic of this study. The signal content of the daily GRACE gravity field model series (ITG-Kalman) is compared to high-frequency bottom pressure variability and terrestrially stored water variations obtained from recent numerical simulations from an ocean circulation model (OMCT) and two hydrological models (WaterGAP Global Hydrology Model, Land Surface Discharge Model). Our results show that daily estimates of ocean bottom pressure from the most recent OMCT simulations and the daily ITG-Kalman solutions are able to explain up to 40 % of extra-tropical sea-level variability in the Southern Ocean. In contrast to this, the daily ITG-Kalman series and simulated continental total water storage variability largely disagree at periods below 30 days. Therefore, as long as no adequate hydrological model will become available, the daily ITG-Kalman series can be regarded as a good initial proxy for high-frequency mass variations at a global scale. As a second result of this study, based on monthly solutions as well as daily observation residuals, it is shown that applying this GRACE-derived de-aliasing model supports the determination of the time-variable gravity field from GRACE data and the subsequent geophysical interpretation. This leads us to the recommendation that future satellite concepts for determining mass variations in the Earth system should be capable of observing higher frequeny signals with sufficient spatial resolution.     

Detection of Continental Hydrology and Glaciology Signals from GRACE: A Review

Since its launch in March 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided a global mapping of the time-variations of the Earth’s gravity field. Tiny variations of gravity from monthly to decadal time scales are mainly due to redistributions of water mass inside the surface fluid envelops of our planet (i.e., atmosphere, ocean and water storage on continents). In this article, we present a review of the major contributions of GRACE satellite gravimetry in global and regional hydrology. To date, many studies have focused on the ability of GRACE to detect, for the very first time, the time-variations of continental water storage (including surface waters, soil moisture, groundwater, as well as snow pack at high latitudes) at the unprecedented resolution of ~400–500 km. As no global complete network of surface hydrological observations exists, the advances of satellite gravimetry to monitor terrestrial water storage are significant and unique for determining changes in total water storage and water balance closure at regional and continental scales.     

GOCE, Satellite Gravimetry and Antarctic Mass Transports

In 2009 the European Space Agency satellite mission GOCE (Gravity Field and Steady-State Ocean Circulation Explorer) was launched. Its objectives are the precise and detailed determination of the Earth’s gravity field and geoid. Its core instrument, a three axis gravitational gradiometer, measures the gravity gradient components V _xx , V _yy , V _zz and V _xz (second-order derivatives of the gravity potential V) with high precision and V _xy , V _yz with low precision, all in the instrument reference frame. The long wavelength gravity field is recovered from the orbit, measured by GPS (Global Positioning System). Characteristic elements of the mission are precise star tracking, a Sun-synchronous and very low (260 km) orbit, angular control by magnetic torquing and an extremely stiff and thermally stable instrument environment. GOCE is complementary to GRACE (Gravity Recovery and Climate Experiment), another satellite gravity mission, launched in 2002. While GRACE is designed to measure temporal gravity variations, albeit with limited spatial resolution, GOCE is aiming at maximum spatial resolution, at the expense of accuracy at large spatial scales. Thus, GOCE will not provide temporal variations but is tailored to the recovery of the fine scales of the stationary field. GRACE is very successful in delivering time series of large-scale mass changes of the Antarctic ice sheet, among other things. Currently, emphasis of respective GRACE analyses is on regional refinement and on changes of temporal trends. One of the challenges is the separation of ice mass changes from glacial isostatic adjustment. Already from a few months of GOCE data, detailed gravity gradients can be recovered. They are presented here for the area of Antarctica. As one application, GOCE gravity gradients are an important addition to the sparse gravity data of Antarctica. They will help studies of the crustal and lithospheric field. A second area of application is ocean circulation. The geoid surface from the gravity field model GOCO01S allows us now to generate rather detailed maps of the mean dynamic ocean topography and of geostrophic flow velocities in the region of the Antarctic Circumpolar Current.     

GRACE terrestrial water storage data assimilation based on the ensemble four-dimensional variational method PODEn4DVar:Method and validation

Seasonal and interannual changes in the Earth's gravity field are mainly due to mass exchange among the atmosphere,ocean,and continental water sources.The terrestrial water storage changes,detected as gravity changes by the Gravity Recovery and Climate Experiment(GRACE) satellites,are mainly caused by precipitation,evapotranspiration,river transportation and downward infiltration processes.In this study,a land data assimilation system LDAS-G was developed to assimilate the GRACE terrestrial water storage(TWS) data into the Community Land Model(CLM3.5) using the POD-based ensemble four-dimensional variational assimilation method PODEn4 DVar,disaggregating the GRACE large-scale terrestrial water storage changes vertically and in time,and placing constraints on the simulation of vertical hydrological variables to improve land surface hydrological simulations.The ideal experiments conducted at a single point and assimilation experiments carried out over China by the LDAS-G data assimilation system showed that the system developed in this study improved the simulation of land surface hydrological variables,indicating the potential of GRACE data assimilation in large-scale land surface hydrological research and applications.     

Performance of GOCE and GRACE-derived mean dynamic topographies in resolving Antarctic Circumpolar Current fronts

Presently, two satellite missions, Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady-state Ocean Circulation Explorer (GOCE), are making detailed measurements of the Earth’s gravity field, from which the geoid can be obtained. The mean dynamic topography (MDT) is the difference between the time-averaged sea surface height and the geoid. The GOCE mission is aimed at determining the geoid with superior accuracy and spatial resolution, so that a more accurate MDT can be estimated. In this study, we determine the mean positions of the Antarctic Circumpolar Current fronts using the purely geodetic estimates of the MDT constructed from an altimetric mean sea surface and GOCE and GRACE geoids. Overall, the frontal positions obtained from the GOCE and GRACE MDTs are close to each other. This means that these independent estimates are robust and can potentially be used to validate frontal positions obtained from sparse and irregular in situ measurements. The geodetic frontal positions are compared to earlier estimates as well as to those derived from MDTs based on satellite and in situ measurements and those obtained from an ocean data synthesis product. The position of the Sub-Antarctic Front identified in the GOCE MDT is found to be in better agreement with the previous estimates than that identified in the GRACE MDT. The geostrophic velocities derived from the GOCE MDT are also closer to observations than those derived from the GRACE MDT. Our results thus show that the GOCE mission represents an improvement upon GRACE in terms of the time-averaged geoid.     

GRACE和地面重力测量监测到的中国大陆长期重力变化

自2002年以来,GRACE卫星探测计划可提供高精度的时变地球重力场,用以探测地球系统的物质分布.自1998年中国大陆重力监测网建立以来,利用FG5绝对重力仪和LCR-G型相对重力仪每2年对该网进行重复测量获取重力场时变信息.基于此,本文利用GRACE和地面重力测量获得了中国大陆重力场的长期年变率,利用位错理论根据USGS发布的断层模型计算了2008年汶川M_s8.0级地震的同震重力变化并进行了300 km高斯滤波.GRACE卫星重力和地面重力结果均表明华北地区地下水流失严重,在绝对重力基准站上,GRACE卫星重力与绝对重力变化率较为一致,汶川区域的地面重力变化结果可视为大地震前兆信息.     

GRACE星体和SuperSTAR加速度计的质心调整精度对地球重力场精度的影响

本文利用改进的能量守恒法开展了GRACE星体和星载加速度计检验质量的不同质心调整精度影响地球重力场精度的模拟研究论证. 结果表明：第一,在120阶处,当质心调整精度设计为0 m,恢复累计大地水准面精度为17.616 cm;当质心调整精度分别设计为5×10^-5 m、1×10^-4 m和5×10^-4 m时,恢复精度各自降低至18.106 cm、19.033 cm和27.329 cm. 第二,以德国GFZ公布的EIGEN-GRACE02S地球重力场模型的实测累计大地水准面精度为标准,当质心调整精度设计为(5～10)×10^-5 m时,其和K波段星间测量系统、GPS接收机、SuperSTAR加速度计、恒星敏感器等GRACE核心载荷的精度指标相匹配,对地球重力场恢复精度的影响较小,因此建议我国将来研制的首颗重力卫星的星体和星载加速度计检验质量的质心调整精度设计为(5～10)×10^-5 m较优.     

Glacial isostatic adjustment in Fennoscandia from GRACE data and comparison with geodynamical models

The Earth’s gravity field observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission shows variations due to the integral effect of mass variations in the atmosphere, hydrosphere and geosphere. Several institutions, such as the GeoForschungsZentrum (GFZ) Potsdam, the University of Texas at Austin, Center for Space Research (CSR) and the Jet Propulsion Laboratory (JPL), Pasadena, provide GRACE monthly solutions, which differ slightly due to the application of different reduction models and centre-specific processing schemes. The GRACE data are used to investigate the mass variations in Fennoscandia, an area which is strongly influenced by glacial isostatic adjustment (GIA). Hence the focus is set on the computation of secular trends. Different filters (e.g. isotropic and non-isotropic filters) are discussed for the removal of high frequency noise to permit the extraction of the GIA signal. The resulting GRACE based mass variations are compared to global hydrology models (WGHM, LaDWorld) in order to (a) separate possible hydrological signals and (b) validate the hydrology models with regard to long period and secular components. In addition, a pattern matching algorithm is applied to localise the uplift centre, and finally the GRACE signal is compared with the results from a geodynamical modelling. The GRACE data clearly show temporal gravity variations in Fennoscandia. The secular variations are in good agreement with former studies and other independent data. The uplift centre is located over the Bothnian Bay, and the whole uplift area comprises the Scandinavian Peninsula and Finland. The secular variations derived from the GFZ, CSR and JPL monthly solutions differ up to 20%, which is not statistically significant, and the largest signal of about 1.2 Gal/year is obtained from the GFZ solution. Besides the GIA signal, two peaks with positive trend values of about 0.8 Gal/year exist in central eastern Europe, which are not GIA-induced, and also not explainable by the hydrology models. This may indicate that the recent global hydrology models have to be revised with respect to long period and secular components. Finally, the GRACE uplift signal is also in quite good agreement with the results from a simple geodynamical modelling.     

模拟分析低低跟踪模式重力卫星反演地球重力场的精度

本文利用卫星重力反演与模拟软件ANGELS系统(ANalyst of Gravity Estimation with Low-orbit Satellites)对低低跟踪模式的重力卫星的关键载荷精度指标进行了深入分析.模拟结果表明:(1)对短弧长积分法而言,在低低跟踪模式的关键载荷精度指标中,重力场反演精度对星间距离变率精度最为敏感;(2)通过对目前在轨运行GRACE的载荷指标进行分析,发现轨道数据的误差主要影响重力场的低阶部分(约小于25阶),较高阶次部分(约大于26阶)主要受星间距离变率的误差限制;(3)如果下一代低低跟踪模式的重力卫星的目标之一是把重力异常反演精度较GRACE提高约10倍,则在保持轨道高度和GRACE相同的前提下,轨道、星间距离变率和星载加速度计等关键载荷指标需要达到的最低精度分别约为2cm、10nm·s-1和3.0×10-10 m·s-2;(4)轨道精度和混频误差将是影响下一代低低跟踪模式重力卫星重力场恢复能力进一步提高的主要制约因素,距离变率精度和加速度计精度存在盈余.     

Improvement of Global Hydrological Models Using GRACE Data

After about 6 years of GRACE (Gravity Recovery and Climate Experiment) satellite mission operation, an unprecedented global data set on the spatio-temporal variations of the Earth’s water storage is available. The data allow for a better understanding of the water cycle at the global scale and for large river basins. This review summarizes the experiences that have been made when comparing GRACE data with simulation results of global hydrological models and it points out the prerequisites and perspectives for model improvements by combination with GRACE data. When evaluated qualitatively at the global scale, water storage variations on the continents from GRACE agreed reasonably well with model predictions in terms of their general seasonal dynamics and continental-scale spatial patterns. Differences in amplitudes and phases of water storage dynamics revealed in more detailed analyses were mainly attributed to deficiencies in the meteorological model forcing data, to missing water storage compartments in the model, but also to limitations and errors of the GRACE data. Studies that transformed previously identified model deficiencies into adequate modifications of the model structure or parameters are still rare. Prerequisites for a comprehensive improvement of large-scale hydrological models are in particular the consistency of GRACE observation and model variables in terms of filtering, reliable error estimates, and a full assessment of the water balance. Using improvements in GRACE processing techniques, complementary observation data, multi-model evaluations and advanced methods of multi-objective calibration and data assimilation, considerable progress in large-scale hydrological modelling by integration of GRACE data can be expected.     

联合星载GPS和KBRR星间测速数据反演GRACE时变重力场模型

高精度GRACE卫星时变重力场反演一直是卫星重力测量中的难题.为了恢复高精度的时变地球重力场模型,本文联合GRACE卫星的星载GPS和KBR星间测速观测数据,在对GRACE卫星进行精密定轨的同时,解算出60阶月平均地球重力场模型.通过对GRACE卫星的定轨精度、星载GPS相位和KBR星间测速数据的拟合残差以及时变地球重力场模型解算精度等分析,表明:(1)与美国宇航局喷气推进实验室(JPL)发布的约化动力学精密轨道相比,本文确定GRACE卫星轨道三维位置误差小于5 cm.(2)星载GPS相位数据拟合残差为5~8 mm,KBR星间测速数据拟合残差为0.18~0.30μm·s~(-1).(3)解算的月平均重力场模型与美国德克萨斯大学空间研究中心(CSR)、德国地学研究中心(GFZ)和JPL发布的RL05模型精度接近,时变信号在全球范围内具有很好的空间分布一致性.通过计算亚马逊流域和长江流域的水储量变化,本文与上述三个机构的计算结果无明显差异,且相关系数均达0.9以上.可见,本文建立的卫星轨道与重力场同解算法具有反演高精度GRACE时变重力场能力,为我国卫星重力场反演提供了重要的技术支持.     

基于GRACEKBRR数据的动力积分法反演时变重力场模型

基于动力积分法恢复了一组60阶的时变重力场模型WHU-Grace01s,且在位系数解算过程中仅使用KBRR数据.通过与CSR、GFZ和JPL发布的Release 05模型的阶方差和位系数误差谱对比可知,WHU-Grace01s模型在高阶次部分的阶方差较小,且对轨道共振现象不敏感.将WHU-Grace01s时变重力场模型与CSR、GFZ、JPL、DEOS、Tongji、ITG、AIUB和GRGS等8家机构发布模型通过相同的滤波处理,获得了全球地表质量变化的时空分布,从结果可以看出:各个模型计算的时变信号在空域上分布十分接近,且WHU-Grace01s模型计算的太平洋中心和撒哈拉沙漠区域的质量变化较小;对比几个典型质量变化区域,WHU-Grace01s模型和JPL模型计算的长江流域和珠江流域时变信号呈强相关,其相关系数分别为0.948和0.976,且与上述8个模型计算的两个流域时变信号的相关系数均达到0.9以上;在南极区域和格陵兰岛,WHU-Grace01s模型和其他各个模型均能反映区域冰川质量的积累或消融,且各模型计算获得的长期趋势变化结果相当.研究结果表明,WHU-Grace01s模型和国内外已发布机构模型具有很好的一致性,且受到轨道共振影响较小.