基于GRACE卫星RL05数据的南极冰盖质量变化分析

CSR(Centre for Space Research)最近发布了RL05数据,其空间分辨率、精度和周期变化特性等都优于RL04数据.本文采用300 km的扇形滤波及P5M11去相关滤波削弱南北条带等重力场模型误差,并采用Paulson2007模型进行冰川均衡模型改正,利用CSR RL05与RL04数据计算分析了南极2002年到2012年的质量变化序列及其变化趋势的空间分布特性,并选取8个特征点进一步分析了其质量变化序列.同时,对CSR、JPL(Jet Propulsion Laboratory)、GFZ (GeoForschungsZentrum)三个机构发布的RL05数据采用相同的滤波方法进行计算,得到整个南极的质量变化分别为-195.7±20.5 Gt/a、-203.8±23.1 Gt/a、-133.2±29.9 Gt/a,对全球海平面变化的影响分别为0.54±0.06 mm/a、0.56±0.06 mm/a、0.37±0.09 mm/a.     

基于GRACE RL06数据监测和分析南极冰盖27个流域质量变化

本文基于CSR最新公布的GRACE RL06版本数据,采用Slepian空域反演法估算了南极冰盖27个流域的质量变化.Slepian空域反演法结合了Slepian空间谱集中法和空域反演法的技术优势,能够有效降低GRACE在小区域反演时信号出现的严重泄漏和衰减,进而精确获得南极冰盖在每个流域的质量变化.相对于GRACE RL05版本数据,RL06在条带误差的控制上要更加优化,获得的南极冰盖质量变化时间序列也更加平滑,但在趋势估算上差别并不明显(小于10Gt/a).本文的估算结果显示:在2002年4月至2016年8月期间,整个南极冰盖质量变化速率为-118.6±16.3Gt/a,其中西南极为-142.4±10.5Gt/a,南极半岛为-29.2±2.1Gt/a,东南极则为52.9±8.6Gt/a.南极冰盖损失最大的区域集中在西南极Amundsen Sea Embayment(流域20-23),该地区质量变化速率为-203.5±4.1Gt/a,其次为南极半岛(流域24-27)以及东南极Victoria-Wilkes Land (流域13-15),质量变化速率分别为-29.2±2.1Gt/a和-19.0±4.7Gt/a,其中Amundsen Sea Embayment和南极半岛南部两个地区的冰排放呈现加速状态.南极冰盖质量显著增加的区域主要有西南极的Ellsworth Land(流域1)和Siple Coast(流域18和19)以及东南极的Coats-Queen Maud-Enderby Land (流域3-8),三个地区质量变化速率分别为17.2±2.4Gt/a、43.9±1.9Gt/a和62.7±3.8Gt/a,质量增加大多来自降雪累积,比如:Coats-Queen Maud-Enderby Land在2009年和2011年发生的大规模降雪事件,但也有来自冰川的增厚,如:Siple Coast地区Kamb冰流的持续加厚.此外,对GRACE估算的南极冰盖质量变化年际信号进行初步分析发现,GRACE年际信号与气候模型估算的冰盖表面质量平衡年际信号存在显著的线性相关关系,但与主要影响南极气候年际变化的气候事件之间却不存在线性相关关系,这说明南极冰盖质量变化的年际信号主要受冰盖表面质量平衡的支配,而气候事件对冰盖表面质量平衡的影响可能是复杂的非线性耦合过程.     

Water Storage Changes over the Tibetan Plateau Revealed by GRACE Mission

We use GRACE gravity data released by the Center for Space Research (CSR) and the Groupe de Recherches en Geodesie Spatiale (GRGS) to detect the water storage changes over the Tibetan Plateau (TP). A combined filter strategy is put forward to process CSR RL05 data to remove the effect of striping errors. After the correction for GRACE by GLDAS and ICE-5G, we find that TP has been overall experiencing the water storage increase during 2003–2012. During the same time, the glacier over the Himalayas was sharply retreating. Interms of linear trends, CSR’s results derived by the combined filter are close to GRGS RL03 with the Gaussian filter of 300-km window. The water storage increasing rates determined from CSR’s RL05 products in the interior TP, Karakoram Mountain, Qaidam Basin, Hengduan Mountain, and middle Himalayas are 9.7, 6.2, 9.1,–18.6, and–20.2 mm/yr, respectively. These rates from GRGS’s RL03 products are 8.6, 5.8, 10.5,–19.3 and–21.4 mm/yr, respectively.     

高亚洲冰川质量变化趋势的卫星重力探测

利用高亚洲地区32个Mascon,基于GRACE RL05时变重力场模型频域和空域上的两种计算方法有效分离并提取出高亚洲冰川及其毗邻地区的等效水质量变化,得到2002—2013年期间高亚洲地区更为可靠的Mascon质量变化.高亚洲冰川质量变化的空间特征是:青藏高原内陆地区以正增长为主,边缘地区以负增长为主,在藏东南的最边缘地区冰川质量损失最为严重.天山地区、帕米尔和昆仑山地区、喜马拉雅山和喀喇昆仑山地区、青藏高原内陆地区冰川质量的平均变化趋势分别为-2.8±0.9Gt/a、-3.3±1.5Gt/a、-9.9±2.1Gt/a和5.0±0.8Gt/a,高亚洲冰川质量整体的平均变化趋势为-11.0±2.9Gt/a.印度等北部平原地区地下水平均变化趋势为-35.0±4.2Gt/a,该地区地下水信号泄漏是影响GRACE研究高亚洲冰川质量变化的关键因素,频域法和空域法能有效改正该地区地下水信号泄漏的影响.     

利用GRACE重力卫星观测数据反演全球时变地球重力场模型

本文基于短弧长法开发了一套由低轨卫星数据解算重力场的系统ANGELS（ANalyst of Gravity Estimation with Low-orbit Satellites）,成功用GRACE Level1B数据解算出全球时变重力场模型（第一版IGG-CAS系列模型）,并与国际三大知名重力卫星相关研究机构：美国德克萨斯大学空间中心CSR （Center for Space Research）、德国GFZ地学研究中心（GeoForschungsZentrum）和美国宇航局JPL喷气推进实验室（Jet Propulsion Laboratory）发布的全球时变重力场模型（RL05模型）进行了详细的比较分析.通过每阶大地水准面差距的对比结果表明,IGG-CAS模型的精度接近RL05模型的精度.对以上四家机构在2004-2010年的时变重力场模型经过相同的去条带和高斯滤波处理,可以发现四家GRACE反演陆地水时变信号的空间分布十分接近,在长江流域反演的陆地水时变信号,两两之间的相关系数均大于0.8.通过反演撒哈拉沙漠干旱地区的时变信号来评估反演的精度水平,IGG-CAS、CSR-RL05、GFZ-RL05和JPL-RL05反演结果的均方差分别为1.5 cm、1.1 cm、1.1 cm和1.2 cm等效水柱高.综合表明IGG-CAS时变重力场反演模型的精度接近于目前国外主要机构最新公布的时变重力场模型.     

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.     

Mass budgets of the Lambert, Mellor and Fisher Glaciers and basal fluxes beneath their flowbands on Amery Ice Shelf

We used in situ measurements and remote-sensing data sets to evaluate the mass budgets of the Lambert, Mellor and Fisher Glaciers and the basal melting and freezing rates beneath their flowbands on the Amery Ice Shelf. Our findings show the Lambert and Mellor Glaciers upstream of the ANARE Lambert Glacier Basin (LGB) traverse may have positive imbalances of 3.9±2.1 Gt a-1 and 2.1±2.4 Gt a-1, respectively, while the Fisher Glacier is approximately in balance. The upstream region as a whole has a positive imbalance of 5.9±4.9 Gt a-1. The three same glaciers downstream of the ANARE LGB traverse line are in negative imbalance, where the whole downstream region has a negative imbalance of -8.5±5.8 Gt a-1. Overall the mass budgets of the Lambert, Mellor, and Fisher Glaciers are close to bal-ance, and the collective three-glacier system is also nearly in balance with a mass budget of -2.6±6.5 Gt a-1. The significant positive imbalances for the interior basin upstream of the ice-movement stations established in the early 1970s (GL line) reported previously are possibly due to an overestimate of the total accumulation and an underestimate of the ice flux through the GL line. The mean melting rate is -23.0±3.5 m ice a-1 near the southern grounding line, which decreases rapidly downstream, and transitions to refreezing at around 300 km from the southern extremity of the Amery Ice Shelf. Freezing rates along the flowbands are around 0.5±0.1 to 1.5±0.2 m ice a-1. The per-centage of ice lost from the interior by basal melting beneath the flowbands is about 80%±5%. The total basal melting and refreezing beneath the three flowbands is 50.3±7.5 Gt ice a-1 and 7.0±1.1 Gt ice a-1, respectively. We find a much larger total basal melting and net melting than the results for the whole Amery Ice Shelf derived from previous modeling and oceanographic measurements.     

Wiener optimal filtering of GRACE data

We present a spatial averaging method for Gravity Recovery and Climate Experiment (GRACE) gravity-field solutions based on the Wiener optimal filtering. The optimal filter is designed from the least-square minimization of the difference between the desired and filtered signals. It requires information about the power spectra of the desired gravitational signal and the contaminating noise, which is inferred from the average GRACE degree-power spectrum. We show that the signal decreases with increasing spherical harmonic degree j with approximately j^−b, where b = 1.5 for GRACE data investigations. This is termed the Second Kaula rule of thumb for temporal variations of the Earth’s gravity field. The degree power of the noise increases, in the logarithmic scale, linearly with increasing j. The Wiener optimal filter obtained for the signal model with b = 1.5 closely corresponds to a Gaussian filter with a spatial half width of 4° (∼440 km). We find that the filtered GRACE gravity signal is relatively insensitive to the exponent b of the signal model, which indicates the robustness of Wiener optimal filtering. This is demonstrated using the GFZ-GRACE gravity-field solution for April 2004.     

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.     

利用广义三角帽方法评估GRACE反演中国大陆地区水储量变化的不确定性

在无真实观测值的情况下,本文利用广义三角帽方法评估了五种GRACE时变重力场模型（CSR、GFZ、GRGS、HUST发布的球谐系数解和JPL发布的Mascon解）反演中国大陆地区2003-2013年水储量变化的不确定性.研究结果表明,CSR、GFZ、JPL、HUST和GRGS反演月水储量变化不确定性的区域平均RMS分别为14.4 mm、26.3 mm、25.3 mm、26.6 mm和56.1 mm,其中GRGS的结果未恢复泄漏信号;在季和年尺度上,模型的不确定性均小于月尺度;扣除周期和趋势信号后,各模型反演结果更为一致.除长江流域外,CSR在13个流域的不确定性均小于其他模型,GRGS反演各流域水储量变化的不确定性通常较大,且可能高估了温带大陆性气候地区水储量的波动;CSR和JPL的不确定性受流域周边水文特征、气候类型、流域面积和形状的影响相对较小,不确定性变化范围分别为2.3~17.1 mm和5.6~22.5 mm,GFZ和HUST受影响较大,不确定性变化范围分别为5.5~35.1 mm和4.0~40.6 mm.本文的研究结果为GRACE产品不确定性评估提供了新的途径,为GRACE时变重力场模型的选取提供参考.     

Low-degree gravity change from GPS data of COSMIC and GRACE satellite missions

This paper demonstrates estimation of time-varying gravity harmonic coefficients from GPS data of COSMIC and GRACE satellite missions. The kinematic orbits of COSMIC and GRACE are determined to the cm-level accuracy. The NASA Goddard's GEODYN II software is used to model the orbit dynamics of COSMIC and GRACE, including the effect of a static gravity field. The surface forces are estimated per one orbital period. Residual orbits generated from kinematic and reference orbits serve as observables to determine the harmonic coefficients in the weighted-constraint least-squares. The monthly COSMIC and GRACE GPS data from September 2006 to December 2007 (16 months) are processed to estimate harmonic coefficients to degree 5. The geoid variations from the GPS and CSR RL04 (GRACE) solutions show consistent patterns over space and time, especially in regions of active hydrological changes. The monthly GPS-derived second zonal coefficient closely resembles the SLR-derived and CSR RL04 values, and third and fourth zonal coefficients resemble the CSR RL04 values.     

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.     

GRACE重力卫星探测南极冰盖质量平衡及其不确定性

2002年GRACE重力卫星的成功发射为南极冰盖质量平衡的研究提供了重力探测的新纪元.本文利用美国德克萨斯大学CSR公布的2003年1月到2013年12月期间的RL05版本GRACE月重力场数据,采用最优平均核函数法和组合滤波法两种GRACE后处理方法反演了南极冰盖质量的时空变化.结果表明:在2003—2013年期间南极冰盖物质平衡呈明显的负增长状态,质量变化趋势为-163±50Gt/a(GW13)、-129±41Gt/a(IJ05)、-81±27Gt/a(W12a),加速度为-8±10Gt/a2,质量消融的主要区域分布在西南极阿蒙森海岸和南极半岛的北部.另外本文还重点探讨了可能影响到估算结果的各项误差及不确定性,分析结果显示影响南极冰盖质量平衡估算结果的最大误差源为GIA改正.通过假设检验和信息准则对时间序列分析中拟合参数的合理选取进行了探讨和分析,在联合周年项、半年项和S2、K2、K1潮汐混频项进行拟合分析时发现K1项对拟合结果的加速度影响比其他周期项稍大,尽管考虑该项的合理性因当前GRACE数据时间序列长度有限而无法确切证实,但K1项的影响值得后续关注.对比两种GRACE后处理方法的结果发现:当采用的数据时间跨度一致,误差改正方法相同,两种相异的后处理方法,其估算结果也具有较好的一致性.     

利用径向基函数RBF解算GRACE全球时变重力场

本文利用GRACE(Gravity Recovery And Climate Experiment)level 1b数据和径向基函数RBF(radial basis function)方法解算了全球时变地球重力场.RBF基函数相比传统球谐(spherical harmonic)基函数,其高度的空域局部特性使得正则化过程易于添加先验协方差信息,从而可能揭示更加准确的重力场信号.本文研究表明,RBF基函数算法在精化现有的GRACE全球时变重力场模型,如提升部分区域信号幅度等方面具有一定优势.本文通过将RBF的尺度因子作为待解参数,基于GRACE卫星的Level 1b数据和变分方程法,成功获取了2009-2010年90阶无约束全球时变重力场RBF模型Hust-IGG03,以及正则化全球时变重力场RBF模型Hust-IGG04.通过与GRACE官方数据处理中心GFZ发布的最新90阶球谐基时变模型RL05a进行对比,结果表明:(1)无约束RBF模型Hust-IGG03和GFZ RL05a在空域和频域表现基本一致;(2)正则化RBF模型Hust-IGG04无需进行后处理滤波已经显示较高信噪比,噪音水平接近于球谐基模型GFZ RL05a经400 km高斯滤波后的效果;(3)HustIGG04相比400 km高斯滤波GFZ RL05a在周年振幅图和趋势图上显示出更多的细节信息,并且呈现出更强的信号幅度,如在格陵兰冰川融化趋势估计上Hust-IGG04比GFZ RL05a提高了24.2%.以上结果均显示RBF方法有助于进一步挖掘GRACE观测值所包含的时变重力场信息.     

GRACE detection of the medium- to far-field coseismic gravity changes caused by the 2004 MW9.3 Sumatra-Andaman earthquake

Large earthquakes cause observable changes in the Earth's gravity field, which have been detected by the Gravity Recovery and Climate Experiment (GRACE). Since most previous studies focus on the detection of near-field gravity effects, this study provides the results from the medium- to far-field gravity changes caused by the 2004 Sumatra-Andaman earthquake that are recorded within GRACE monthly solutions. Utilizing a spherical-earth dislocation model we documented that large-scale signals predominate in the global field of the coseismic gravity changes caused by the earthquake. After removing the near-field effects, the coseismic gravity changes show a negative anomaly feature with an average magnitude of -0.18×10^-8 m·s^-2 in the region ranging ~40° from the epicenter, which is considered as the "medium field" in this study. From the GRACE data released by Center for Space Research from August 2002 to December 2008, we retrieved the large-scale gravity changes smoothed with 3 000 km Gaussian filter. The results show that the coseismic gravity changes detected by GRACE in the medium field have an average of (-0.20€±0.06)×10^-8 m·s^-2, which agrees with the model prediction. The detection confirms that GRACE is sensitive to large-scale medium-field coseismic gravitational effects of mega earthquakes, and also validates the spherical-earth dislocation model in the medium field from the perspective of satellite gravimetry.     

On the computation of mass-change trends from GRACE gravity field time-series

Time-variable GRACE (Gravity Recovery and Climate Experiment) gravity field solutions are routinely exploited to derive secular and seasonal mass changes on and near the Earth's surface. However, the quantification of mass redistribution from space gravimetry is not a straightforward process. For instance, published linear deglaciation rates of the Greenland ice sheets vary from ≈100 Gt/yr to ≈300 Gt/yr; the discrepancies are subject to applied methodologies, the considered gravity field time-series and the period of investigation. Furthermore, in the recent past discussion has come to the fore whether the temporal behavior of mass variation might be better represented by a second-order polynomial rather than a linear regression model. In summary, the degrees of freedom inherent to GRACE analysis make the detection of mass trends to become a delicate topic. This contribution sensitizes for a more careful review of trends derived from GRACE mass-variation time-series. We point to possible misinterpretation and propose “rules” that improve the consistency of results.     

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.     

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.     

GRACE估算陆地水储量季节和年际变化

利用最新公布的GRACE GFZ RL04数据,分析了2003年1月～2007年12月全球27条流域和陆地水储量的季节性和年际变化.结果表明,相近流域季节性变化相位接近.2003年1月～2007年12月陆地水储量季节性变化为1572.4 km3,其中变化最大流域为亚马逊河,其次分别为鄂毕河、尼罗河和尼日尔河等流域.5年来 GRACE陆地水储量的年际变化为-75.4±40.3 km3/a,其中亚马逊河、勒拿河和马更些河等流域的年际变化呈现正增长,而刚果河、密西西比河、恒河、育空河和雅鲁藏布江等流域则相反.GRACE与GLDAS数据均表明2006年后陆地水储量年际变化存在明显增加.     

Assessment of terrestrial water contributions to polar motion from GRACE and hydrological models

The hydrological contribution to polar motion is a major challenge in explaining the observed geodetic residual of non-atmospheric and non-oceanic excitations since hydrological models have limited input of comprehensive global direct observations. Although global terrestrial water storage (TWS) estimated from the Gravity Recovery and Climate Experiment (GRACE) provides a new opportunity to study the hydrological excitation of polar motion, the GRACE gridded data are subject to the post-processing de-striping algorithm, spatial gridded mapping and filter smoothing effects as well as aliasing errors. In this paper, the hydrological contributions to polar motion are investigated and evaluated at seasonal and intra-seasonal time scales using the recovered degree-2 harmonic coefficients from all GRACE spherical harmonic coefficients and hydrological models data with the same filter smoothing and recovering methods, including the Global Land Data Assimilation Systems (GLDAS) model, Climate Prediction Center (CPC) model, the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis products and European Center for Medium-Range Weather Forecasts (ECMWF) operational model (opECMWF). It is shown that GRACE is better in explaining the geodetic residual of non-atmospheric and non-oceanic polar motion excitations at the annual period, while the models give worse estimates with a larger phase shift or amplitude bias. At the semi-annual period, the GRACE estimates are also generally closer to the geodetic residual, but with some biases in phase or amplitude due mainly to some aliasing errors at near semi-annual period from geophysical models. For periods less than 1-year, the hydrological models and GRACE are generally worse in explaining the intraseasonal polar motion excitations.