联合卫星重力、卫星测高和海洋资料研究全球海平面变化

利用GRACE、卫星测高和海洋实测温盐数据,探讨了2003~2012年间全球海平面、比容海平面和海水质量等的变化特征,并讨论了南极冰盖和格陵兰冰盖消融对全球海平面变化的影响。全球海平面整体呈上升趋势,上升速度为2.72±0.07 mm/a,且存在显著的空间分布特征。全球海平面、比容海平面和海水质量等的变化还具有显著的季节性特征,其中全球海平面变化的年周期振幅为4.6±0.3 mm。使用经验正交函数分析(EOF)得到全球海平面和比容海平面的季节性变化在南北半球存在显著的差异,但海水质量季节性变化不存在这种差异。南极冰盖和格陵兰冰盖的消融速率分别为-75.7±12.3 Gt/a和-124.1±2.9 Gt/a,对海平面的长期趋势项贡献分别为0.21±0.03 mm/a和0.34±0.01 mm/a,仅占全球海水质量增加速度1.80±0.10 mm/a的12%和19%,总计占31%,因此,两极冰盖质量消融并不是2003-2012年间海水质量增加的最主要因素。     

Simulation study of a follow-on gravity mission to GRACE

The gravity recovery and climate experiment (GRACE) has been providing monthly estimates of the Earth’s time-variable gravity field since its launch in March 2002. The GRACE gravity estimates are used to study temporal mass variations on global and regional scales, which are largely caused by a redistribution of water mass in the Earth system. The accuracy of the GRACE gravity fields are primarily limited by the satellite-to-satellite range-rate measurement noise, accelerometer errors, attitude errors, orbit errors, and temporal aliasing caused by un-modeled high-frequency variations in the gravity signal. Recent work by Ball Aerospace & Technologies Corp., Boulder, CO has resulted in the successful development of an interferometric laser ranging system to specifically address the limitations of the K-band microwave ranging system that provides the satellite-to-satellite measurements for the GRACE mission. Full numerical simulations are performed for several possible configurations of a GRACE Follow-On (GFO) mission to determine if a future satellite gravity recovery mission equipped with a laser ranging system will provide better estimates of time-variable gravity, thus benefiting many areas of Earth systems research. The laser ranging system improves the range-rate measurement precision to ~0.6 nm/s as compared to ~0.2 μm/s for the GRACE K-band microwave ranging instrument. Four different mission scenarios are simulated to investigate the effect of the better instrument at two different altitudes. The first pair of simulated missions is flown at GRACE altitude (~480 km) assuming on-board accelerometers with the same noise characteristics as those currently used for GRACE. The second pair of missions is flown at an altitude of ~250 km which requires a drag-free system to prevent satellite re-entry. In addition to allowing a lower satellite altitude, the drag-free system also reduces the errors associated with the accelerometer. All simulated mission scenarios assume a two satellite co-orbiting pair similar to GRACE in a near-polar, near-circular orbit. A method for local time variable gravity recovery through mass concentration blocks (mascons) is used to form simulated gravity estimates for Greenland and the Amazon region for three GFO configurations and GRACE. Simulation results show that the increased precision of the laser does not improve gravity estimation when flown with on-board accelerometers at the same altitude and spacecraft separation as GRACE, even when time-varying background models are not included. This study also shows that only modest improvement is realized for the best-case scenario (laser, low-altitude, drag-free) as compared to GRACE due to temporal aliasing errors. These errors are caused by high-frequency variations in the hydrology signal and imperfections in the atmospheric, oceanographic, and tidal models which are used to remove unwanted signal. This work concludes that applying the updated technologies alone will not immediately advance the accuracy of the gravity estimates. If the scientific objectives of a GFO mission require more accurate gravity estimates, then future work should focus on improvements in the geophysical models, and ways in which the mission design or data processing could reduce the effects of temporal aliasing.     

Estimation of mass change trends in the Earth’s system on the basis of GRACE satellite data, with application to Greenland

The Gravity Recovery and Climate Experiment (GRACE) satellite mission measures the Earth’s gravity field since March 2002. We propose a new filtering procedure for post-processing GRACE-based monthly gravity field solutions provided in the form of spherical harmonic coefficients. The procedure is tuned for the optimal estimation of linear trends and other signal components that show a systematic behavior over long time intervals. The key element of the developed methodology is the statistically optimal Wiener-type filter which makes use of the full covariance matrices of noise and signal. The developed methodology is applied to determine the mass balance of the Greenland ice sheet, both per drainage system and integrated, as well as the mass balance of the ice caps on the islands surrounding Greenland. The estimations are performed for three 2-year time intervals (2003–2004, 2005–2006, and 2007–2008), as well as for the 6-year time interval (2003–2008). The study confirms a significant difference in the behavior of the drainage systems over time. The average 6-year rate of mass loss in Greenland is estimated as 165 ± 15 Gt/year. The rate of mass loss of the ice caps on Ellesmere Island (together with Devon Island), Baffin Island, Iceland, and Svalbard is found to be 22 ± 4, 21 ± 6, 17 ± 9, and 6 ± 2 Gt/year, respectively. All these estimates are corrected for the effect of glacial isostatic adjustment.     

Assessing Greenland ice mass loss by means of point-mass modeling: a viable methodology

Greenland ice mass loss is one of the most serious phenomena of present-day global climate change. In this context, both the quantification of overall deglaciation rates and its spatial localization are highly significant. We have thoroughly investigated the technique of point-mass modeling in order to derive mass-balance patterns from GRACE (Gravity Recovery And Climate Experiment) gravimetry. The method infers mass variations on the Earth’s surface from gravitational signals at satellite altitude. In order to solve for point-mass changes, we applied least-squares adjustment. Due to downward continuation, numerical stabilization of the inversion process gains particular significance. We stabilized the ill-posed problem by Tikhonov regularization. Our simulation and real data experiments show that point-mass modeling provides both rational deglaciation rates and high-resolution spatial mass variation patterns.     

Statistically optimal estimation of Greenland Ice Sheet mass variations from GRACE monthly solutions using an improved mascon approach

We present an improved mascon approach to transform monthly spherical harmonic solutions based on GRACE satellite data into mass anomaly estimates in Greenland. The GRACE-based spherical harmonic coefficients are used to synthesize gravity anomalies at satellite altitude, which are then inverted into mass anomalies per mascon. The limited spectral content of the gravity anomalies is properly accounted for by applying a low-pass filter as part of the inversion procedure to make the functional model spectrally consistent with the data. The full error covariance matrices of the monthly GRACE solutions are properly propagated using the law of covariance propagation. Using numerical experiments, we demonstrate the importance of a proper data weighting and of the spectral consistency between functional model and data. The developed methodology is applied to process real GRACE level-2 data (CSR RL05). The obtained mass anomaly estimates are integrated over five drainage systems, as well as over entire Greenland. We find that the statistically optimal data weighting reduces random noise by 35–69%, depending on the drainage system. The obtained mass anomaly time-series are de-trended to eliminate the contribution of ice discharge and are compared with de-trended surface mass balance (SMB) time-series computed with the Regional Atmospheric Climate Model (RACMO 2.3). We show that when using a statistically optimal data weighting in GRACE data processing, the discrepancies between GRACE-based estimates of SMB and modelled SMB are reduced by 24–47%.     

Improved GRACE science results after adjustment of geometric biases in the Level-1B K-band ranging data

The GRACE (Gravity Recovery and Climate Experiment) satellite mission relies on the inter-satellite K-band microwave ranging (KBR) observations. We investigate systematic errors that are present in the Level-1B KBR data, namely in the geometric correction. This correction converts the original ranging observation (between the two KBR antennas phase centers) into an observation between the two satellites’ centers of mass. It is computed from data on the precise alignment between both satellites, that is, between the lines joining the center of mass and the antenna phase center of either satellite. The Level-1B data used to determine this alignment exhibit constant biases as large as 1–2 mrad in terms of pitch and yaw alignment angles. These biases induce non-constant errors in the Level-1B geometric correction. While the precise origin of the biases remains to be identified, we are able to estimate and reduce them in a re-calibration approach. This significantly improves time-variable gravity field solutions based on the CNES/GRGS processing strategy. Empirical assessments indicate that the systematic KBR data errors have previously induced gravity field errors on the level of 6–11 times the so-called GRACE baseline error level. The zonal coefficients (from degree 14) are particularly affected. The re-calibration reduces their rms errors by about 50%. As examples for geophysical inferences, the improvement enhances agreement between mass variations observed by GRACE and in-situ ocean bottom pressure observations. The improvement also importantly affects estimates of inter-annual mass variations of the Antarctic ice sheet.     

Seasonal global mean sea level change from satellite altimeter, GRACE, and geophysical models

We estimate seasonal global mean sea level changes using different data resources, including sea level anomalies from satellite radar altimetry, ocean temperature and salinity from the World Ocean Atlas 2001, time-variable gravity observations from the Gravity Recovery and Climate Experiment (GRACE) mission, and terrestrial water storage and atmospheric water vapor changes from the NASA global land data assimilation system and National Centers for Environmental Prediction reanalysis atmospheric model. The results from all estimates are consistent in amplitude and phase at the annual period, in some cases with remarkably good agreement. The results provide a good measure of average annual variation of water stored within atmospheric, land, and ocean reservoirs. We examine how varied treatments of degree-2 and degree-1 spherical harmonics from GRACE, laser ranging, and Earth rotation variations affect GRACE mean sea level change estimates. We also show that correcting the standard equilibrium ocean pole tide correction for mass conservation is needed when using satellite altimeter data in global mean sea level studies. These encouraging results indicate that is reasonable to consider estimating longer-term time series of water storage in these reservoirs, as a way of tracking climate change.     

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.     

联合卫星测高、GRACE与温盐数据分析红海海平面变化季节性特征

本文利用卫星测高、GRACE与温盐数据监测2003-2014年红海海平面变化，并分析了蒸发降水以及亚丁湾-红海质量交换对红海质量变化的影响。红海地区单一的温盐数据存在覆盖不全或质量不佳的问题，综合CORA、SODA与ORAS4温盐数据估算结果得到平均比容海平面变化，以改善比容信号的精度。针对GRACE数据处理过程中截断与空间平滑滤波引起的泄漏误差，提出改进尺度因子纠正泄漏误差，利用卫星测高数据进行模拟实验验证了改进尺度因子的有效性。利用传统尺度因子和改进尺度因子反演的红海质量变化周年振幅分别为16.1±1.3 cm和20.5±1.7 cm，利用卫星测高和温盐数据估算的质量变化周年振幅为20.2±1.0 cm，表明改进尺度因子可有效减小泄漏误差的影响，改善GRACE模型反演红海质量变化的精度。卫星测高、GRACE卫星重力数据以及平均温盐数据具有较好的一致性，联合GRACE和温盐数据估算的红海综合海平面变化周年振幅为16.6±1.7 cm，与卫星测高估算的总海平面变化周年振幅（16.2±0.9 cm）基本一致，表明多源数据可构成完整的红海海平面监测手段。相比于降水-蒸发作用，红海质量变化受红海与亚丁湾的海水质量交换的影响更为显著，其主导了红海质量的季节性变化。     

利用卫星重力测量确定地球重力场模型的进展

卫星重力测量是当前探测全球一致、高精度和高分辨率地球重力场的高效技术手段,主要包括高低卫星跟踪卫星测量（satellite-to-satellite tracking in high-low mode, SST-hl）、低低卫星跟踪卫星测量（satellite-to-satellite tracking in low-low mode, SST-ll）和卫星重力梯度测量（satellite gravity gradiometry,SGG）。系统总结了利用卫星重力测量技术（包括SST-hl、SST-ll和SGG及多模式组合）反演地球重力场的主要方法,评述了利用挑战性小卫星有效载荷（challenging mini-satellite payload, CHAMP）、重力恢复与气候实验（gravity recovery and climate experiment, GRACE）/ GRACE继任者（GRACE follow-on, GRACE -FO）和地球重力场和海洋环流探索器（gravity field and steady-state ocean circulation explorer, GOCE）卫星重力数据构建静态和时变重力场模型的最新进展,并对当前具有代表性的地球重力场模型精度进行了分析和评估,以期对未来的地球重力场研究及其地学应用提供参考。     

国际重力卫星研究进展和我国将来卫星重力测量计划

本文首先分别介绍了国际已经成功发射的专用地球重力测量卫星CHAMP、GRACE以及即将发射的GOCE、GRACE Follow-On和专用月球重力探测卫星GRAIL的研制机构、轨道参数、关键载荷、跟踪模式、测量原理、科学目标和技术特征;其次,阐述了当前相关学科对地球重力场测量精度的需求;最后,建议我国在将来实施的卫星重力测量计划中首选卫星跟踪卫星高低\低低模式,尽快开展轨道参数优化选取的定量系统研究论证和重力卫星系统的误差分析,依据匹配精度指标先期开展重力卫星各关键载荷的研制以及尽早启动卫星重力测量系统的虚拟仿真研究。     

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。     

格陵兰地区GLASS反照率产品质量评价及反照率变化趋势分析

冰雪反照率是影响和评估全球气候变化的重要因子。北极格陵兰岛拥有世界第二大冰盖,定量获取该地区反照率是研究北半球能量收支变化的关键。全球陆表卫星(global land surface satellite,GLASS) 产品系统生产的反照率产品是目前国际上时间序列最长（1981—2017年）的全球反照率产品。利用格陵兰气候观测网络(Greenland climate network, GC-Net)与格陵兰冰架监测计划(programme for monitoring of the Greenland ice sheet, PROMICE)网络观测的反照率数据,评估了格陵兰地区GLASS地表反照率产品的精度;并基于2000—2017年的GLASS地表反照率产品,分析了格陵兰地区7月份反照率的年际变化趋势与空间分布特征。结果表明:GLASS与GC-Net反照率的均方根误差(root mean squared error, RMSE)为0.077 8(决定系数R2=0.490 7),与PROMICE反照率差异的RMSE为0.078 6(R2=0.899 9),GLASS产品的反照率数值呈现一定的低估现象,但已满足格陵兰地区冰雪反照率研究的需要。基于2000—2017年7月份格陵兰地区的GLASS反照率变化分析可以看出,格陵兰地区的反照率在此期间整体呈现变小的趋势,平均速率约为0.000 6 /a,变小的地区约占格陵兰总面积的64%;其中,位于格陵兰西部海拔750~1 500 m之间的区域对气候变化最为敏感,反照率变小速率也最大,达到了0.026 /a。     

Separation of global time-variable gravity signals into maximally independent components

The Gravity Recovery and Climate Experiment (GRACE) products provide valuable information about total water storage variations over the whole globe. Since GRACE detects mass variations integrated over vertical columns, it is desirable to separate its total water storage anomalies into their original sources. Among the statistical approaches, the principal component analysis (PCA) method and its extensions have been frequently proposed to decompose the GRACE products into space and time components. However, these methods only search for decorrelated components that on the one hand are not always interpretable and on the other hand often contain a superposition of independent source signals. In contrast, independent component analysis (ICA) represents a technique that separates components based on assumed statistical independence using higher-order statistical information. If one assumes that independent physical processes generate statistically independent signal components added up in the GRACE observations, separating them by ICA is a reliable strategy to identify these processes. In this paper, the performance of the conventional PCA, its rotated extension and ICA are investigated when applied to the GRACE-derived total water storage variations. These analyses have been tested on both a synthetic example and on the real GRACE level-2 monthly solutions derived from GeoForschungsZentrum Potsdam (GFZ RL04) and Bonn University (ITG2010). Within the synthetic example, we can show how imposing statistical independence in the framework of ICA improves the extraction of the ‘original’ signals from a GRACE-type super-position. We are therefore confident that also for the real case the ICA algorithm, without making prior assumptions about the long-term behaviour or on the frequencies contained in the signal, improves over the performance of PCA and its rotated extension in the separation of periodical and long-term components.     

现代低轨卫星对地球重力场探测的实践和进展

综述了现代低轨卫星对地球重力场测量的特点和近况，介绍了已经和即将发射的重力卫星CHAMP、GRACE、GOCE和新型测高卫星，讨论了作为现代重力卫星首次实践－－CHAMP卫星的进展和目前尚待解决的问题。     

GRACE-derived surface water mass anomalies by energy integral approach: application to continental hydrology

We propose an unconstrained approach to recover regional time-variations of surface mass anomalies using Level-1 Gravity Recovery and Climate Experiment (GRACE) orbit observations, for reaching spatial resolutions of a few hundreds of kilometers. Potential differences between the twin GRACE vehicles are determined along short satellite tracks using the energy integral method (i.e., integration of orbit parameters vs. time) in a quasi-inertial terrestrial reference frame. Potential differences residuals corresponding mainly to changes in continental hydrology are then obtained after removing the gravitational effects of the known geophysical phenomena that are mainly the static part of the Earth’s gravity field and time-varying contributions to gravity (Sun, Moon, planets, atmosphere, ocean, tides, variations of Earth’s rotation axis) through ad hoc models. Regional surface mass anomalies are restored from potential difference anomalies of 10 to 30-day orbits onto 1^◦ continental grids by regularization techniques based on singular value decomposition. Error budget analysis has been made by considering the important effects of spectrum truncation, the time length of observation (or spatial coverage of the data to invert) and for different levels of noise.     

Geocenter variations derived from GPS tracking of the GRACE satellites

Two 4.5-year sets of daily geocenter variations have been derived from GPS-LEO (Low-Earth Orbiter) tracking of the GRACE (Gravity Recovery And Climate Experiment) satellites. The twin GRACE satellites, launched in March 2002, are each equipped with a BlackJack global positioning system (GPS) receiver for precise orbit determination and gravity recovery. Since launch, there have been significant improvements in the background force models used for satellite orbit determination, most notably the model for the geopotential, which has resulted in significant improvements to the orbit determination accuracy. The purpose of this paper is to investigate the potential for determining seasonal (annual and semiannual) geocenter variations using GPS-LEO tracking data from the GRACE twin satellites. Internal comparison between the GRACE-A and GRACE-B derived geocenter variations shows good agreement. In addition, the annual and semiannual variations of geocenter motions determined from this study have been compared with other space geodetic solutions and predictions from geophysical models. The comparisons show good agreement except for the phase of the z-translation component.     

Mass evolution of Mediterranean,Black, Red,and Caspian Seas from GRACE and altimetry: accuracy assessment and solution calibration

We present new measurements of mass evolution for the Mediterranean, Black, Red, and Caspian Seas as determined by the NASA Goddard Space Flight Center (GSFC) GRACE time-variable global gravity mascon solutions. These new solutions are compared to sea surface altimetry measurements of sea level anomalies with steric corrections applied. To assess their accuracy, the GRACE- and altimetry-derived solutions are applied to the set of forward models used by GSFC for processing the GRACE Level-1B datasets, with the resulting inter-satellite range-acceleration residuals providing a useful metric for analyzing solution quality. We also present a differential correction strategy to calibrate the time series of mass change for each of the seas by establishing the strong linear relationship between differences in the forward modeled mass and the corresponding range-acceleration residuals between the two solutions. These calibrated time series of mass change are directly determined from the range-acceleration residuals, effectively providing regionally-tuned GRACE solutions without the need to form and invert normal equations. Finally, the calibrated GRACE time series are discussed and combined with the steric-corrected sea level anomalies to provide new measurements of the unmodeled steric variability for each of the seas over the span of the GRACE observation record. We apply ensemble empirical mode decomposition (EEMD) to adaptively sort the mass and steric components of sea level anomalies into seasonal, non-seasonal, and long-term temporal scales.     

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...     

Vertical deformations from homogeneously processed GRACE and global GPS long-term series

Temporal variations in the geographic distribution of surface mass cause surface displacements. Surface displacements derived from GRACE gravity field coefficient time series also should be observed in GPS coordinate time series, if both time series are sufficiently free of systematic errors. A successful validation can be an important contribution to climate change research, as the biggest contributors to mass variability in the system Earth include the movement of oceanic, atmospheric, and continental water and ice. In our analysis, we find that if the signals are larger than their precision, both geodetic sensor systems see common signals for almost all the 115 stations surveyed. Almost 80% of the stations have their signal WRMS decreased, when we subtract monthly GRACE surface displacements from those observed by GPS data. Almost all other stations are on ocean islands or small peninsulas, where the physically expected loading signals are very small. For a fair comparison, the data (79 months from September 2002 to April 2009) had to be treated appropriately: the GPS data were completely reprocessed with state-of-the-art models. We used an objective cluster analysis to identify and eliminate stations, where local effects or technical artifacts dominated the signals. In addition, it was necessary for both sets of results to be expressed in equivalent reference frames, meaning that net translations between the GPS and GRACE data sets had to be treated adequately. These data sets are then compared and statistically analyzed: we determine the stability (precision) of GRACE-derived, monthly vertical deformation data to be ~1.2 mm, using the data from three GRACE processing centers. We statistically analyze the mean annual signals, computed from the GPS and GRACE series. There is a detailed discussion of the results for five overall representative stations, in order to help the reader to link the displayed criteria of similarity to real data. A series of tests were performed with the goal of explaining the remaining GPS–GRACE residuals.