Simulated estimation of hydrological loads from GRACE

Four different basin functions are developed to estimate water storage variations within individual river basins from time variations in the Stokes coefficients now available from the GRACE mission. The four basin functions are evaluated using simulated data. Basin functions differ in how they minimize effects of three major error sources: measurement error; leakage of signal from one region to another; and errors in the atmospheric pressure field removed during GRACE data processing. Three of the basin functions are constant in time, while the fourth changes monthly using information about the signal (hydrologic and oceanic load variations). To test basin functions performance, Stokes coefficient variations from land and ocean models are synthesized, and error levels 50 and 100 times greater than pre-launch GRACE error estimate are used to corrupt them. Errors at 50 times pre-launch estimates approximately simulate current GRACE data. GRACE recovery of water storage variations is attempted for five different river basins (Amazon, Mississippi, Lena, Huang He and Oranje), representing a variety of sizes, locations, and signal variance. In the large basins (Amazon, Mississippi and Lena), water storage variations are recovered successfully at both error levels. As the error level increases from 50 to 100 times, basin functions change their shape, yielding less atmospheric pressure error and more leakage error. Amplitude spectra of measurement and atmospheric pressure errors have different shapes, but the best results are obtained when both are used in basin function design. When high-quality information about the signal is available, for example from climate and ocean models, changing the basin function each month can reduce leakage error and improve estimates of time variable water storage within basins.     

利用高分辨率水文模型提高GRACE卫星的空间分辨率

为克服GRACE卫星数据空间分辨率粗糙的局限性,本文以高空间分辨率的PCR-GLOBWB数据为基础,构建了加权、乘权及误差分配降尺度方法,将GRACE卫星在河北省的水储量变化数据的空间分辨率由0.50°提高至0.05°。结果表明：加权降尺度方法不仅保留了GRACE数据的原始空间分布特征,还刻画了局部细节特征;误差分配降尺度方法结果较为理想,但在格网交界处的信号存在跳跃现象;乘权降尺度方法表现最差,与GRACE存在明显差异。经实测数据验证可知,加权降尺度方法与实测值拟合程度最好,相关系数最高可达0.81。本文为获取河北省高空间分辨率地下水储量数据提供了有效保障。     

Decorrelated GRACE time-variable gravity solutions by GFZ,and their validation using a hydrological model

We have analyzed recent gravity recovery and climate experiment (GRACE) RL04 monthly gravity solutions, using a new decorrelating post-processing approach. We find very good agreement with mass anomalies derived from a global hydrological model. The post-processed GRACE solutions exhibit only little amplitude damping and an almost negligible phase shift and period distortion for relevant hydrological basins. Furthermore, these post-processed GRACE solutions have been inspected in terms of data fit with respect to the original inter-satellite ranging and to SLR and GPS observations. This kind of comparison is new. We find variations of the data fit due to solution post-processing only within very narrow limits. This confirms our suspicion that GRACE data do not firmly ‘pinpoint’ the standard unconstrained solutions. Regarding the original Kusche (J Geod 81:733–749, 2007) decorrelation and smoothing method, a simplified (order-convolution) approach has been developed. This simplified approach allows to realize a higher resolution—as necessary, e.g., for generating computed GRACE observations—and needs far less coefficients to be stored.     

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%.     

利用GRACE轨道和加速度数据恢复地球重力场

本文基于高低卫卫跟踪的模式，用积分方法研究了不同重力场模型对于轨道的影响，并用3个月的GRACE轨道数据计算了新的60阶地球重力场模型，为了分析其精度，与EGM96和EIGENIS作了比较．结果表明新模型在40阶前更接近GGM02C模型。     

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.     

用GRACE星间速度恢复地球重力场

本文首先给出了用星间速度恢复地球重力场的数学模型,然后用GRACE卫星30天的星间速度观测值计算了一个100阶的地球重力场模型DQM2006S2。为了对这一模型的精度进行评述,将它与EGM 96,EIGEN-CHAMP03S和GGM01S3个地球重力场模型作了比较,并用这一模型计算了高程异常与GPS/水准实际观测值进行了比较,结果表明:DQM2006S2模型精度优于EGM 96和EIGEN-CHAMP03S模型精度,但是不及GGM01S模型精度。精度不及GGM01S的原因是GGM01S模型使用了111天的星间速度数据,其数据量约为DQM2006S2模型使用数据量的4倍。     

Inter-annual water mass variations from GRACE in central Siberia

Our study analyses satellite and land-based observations of the Yakutsk region centred at the Lena watershed, an area characterised mainly by continuous permafrost. Using monthly solutions of the Gravity Recovery And Climate Experiment satellite mission, we detect a mass increase over central Siberia from 2002 to 2007 which reverses into a mass decrease between 2007 and 2011. No significant mass trend is visible for the whole observation period. To further quantify this behaviour, different mass signal components are studied in detail: (1) inter-annual variation in the atmospheric mass, (2) a possible effect of glacial isostatic adjustment (GIA), and (3) hydrological mass variations. In standard processing the atmospheric mass signal is reduced based on the data from numerical weather prediction models. We use surface pressure observations in order to validate this atmospheric reduction. On inter-annual time scale the difference between the atmospheric mass signal from model prediction and from surface pressure observation is $<$ 4 mm in equivalent water height. The effect of GIA on the mass signal over Siberia is calculated using a global ice model and a spherically symmetric, compressible, Maxwell-viscoelastic earth model. The calculation shows that for the investigated area any effect of GIA can be ruled out. Hence, the main part of the signal can be attributed to hydrological mass variations. We briefly discuss potential hydrological effects such as changes in precipitation, river discharge, surface and subsurface water storage.     

利用GRACE反演陕甘晋高原地下水储量变化

采用GRACE时变重力场模型和GLDAS水文模型反演了陕甘晋高原地下水储量的时空变化,并与TRMM降雨资料及实测水井数据进行了对比分析。研究结果表明：在时间域上,整个区域的地下水在2005-2014年大约以3.6±0.7 mm/a的速率递减;在空间域上,整个区域自西向东10年内的递减速率依次增大,其中山西中部地区最大。与TRMM降雨资料的对比发现,降雨与地下水储量变化强相关,但不是引起地下水储量减少的原因。与水井实测数据对比发现,除特殊情况外,本文反演得到的结果与水井水位变化趋势基本一致。     

应用卫星重力数据监测维多利亚湖流域水储量变化

维多利亚湖是非洲第一大淡水湖,也是全球十大湖泊中纬度最低的淡水湖,有利于GRACE的监测。维多利亚湖为其流域内的居民提供了赖以生存的淡水资源,监测其水储量变化有重要意义。利用2003年1月至2016年12月间的GRACE时变重力场数据反演其水储量变化,针对GRACE数据处理过程中产生的信号泄漏问题,采用Forward Modeling的方法恢复信号,结果表明:此方法能有效地减小泄漏误差,恢复初始信号;通过分析维多利亚湖流域水储量的变化趋势,发现其水储量在2003年至2016年有明显的阶段性变化,并且水储量易受到自然因素和人为因素影响;联合GRACE、卫星测高和GLDAS计算了流域内的地下水变化,其趋势与WGHM模式输出结果具有很好的一致性。     

Combination of GRACE monthly gravity field solutions from different processing strategies

We combine the publicly available GRACE monthly gravity field time series to produce gravity fields with reduced systematic errors. We first compare the monthly gravity fields in the spatial domain in terms of signal and noise. Then, we combine the individual gravity fields with comparable signal content, but diverse noise characteristics. We test five different weighting schemes: equal weights, non-iterative coefficient-wise, order-wise, or field-wise weights, and iterative field-wise weights applying variance component estimation (VCE). The combined solutions are evaluated in terms of signal and noise in the spectral and spatial domains. Compared to the individual contributions, they in general show lower noise. In case the noise characteristics of the individual solutions differ significantly, the weighted means are less noisy, compared to the arithmetic mean: The non-seasonal variability over the oceans is reduced by up to 7.7% and the root mean square (RMS) of the residuals of mass change estimates within Antarctic drainage basins is reduced by 18.1% on average. The field-wise weighting schemes in general show better performance, compared to the order- or coefficient-wise weighting schemes. The combination of the full set of considered time series results in lower noise levels, compared to the combination of a subset consisting of the official GRACE Science Data System gravity fields only: The RMS of coefficient-wise anomalies is smaller by up to 22.4% and the non-seasonal variability over the oceans by 25.4%. This study was performed in the frame of the European Gravity Service for Improved Emergency Management (EGSIEM; http://www.egsiem.eu) project. The gravity fields provided by the EGSIEM scientific combination service (ftp://ftp.aiub.unibe.ch/EGSIEM/) are combined, based on the weights derived by VCE as described in this article.     

中国西部区域GRACE卫星重力变化

针对研究中国西部长期重力变化的问题,该文利用GRACE月重力场模型,基于Slepian变换构建中国西部区域局部重力场,并采用GIA和GLDAS等模型扣除相应误差,通过时间序列分析方法得到该区域2003—2013年卫星重力变化。结果表明,东天山呈现负重力变化,可能由区域冰川消融引起的;西天山的正重力变化,应与冰川小幅增加和构造运动引起的壳幔物质积累有关;青藏高原内陆正重力变化可能由区域地壳抬升、粘弹性地壳的构造应变以及壳幔物质的质量迁移与积累引起;青藏高原边界区域的负重力变化,应与冰川加速消融以及地下水抽取有关。Slepian方法较好地克服了滤波平滑处理带来的重力变化信号压制及细节平滑,可为中国西部的地壳运动、地震活动和气候变化等研究提供数据支撑。     

水文资料缺乏区河流流量遥感估算模型研究

针对偏远地区河流上无水文站点,缺乏河川径流量监测数据的问题,该文以黑河中游地区为例,利用2005—2010年夏、秋两季的Landsat TM/ETM+/OLI影像,提取黑河中游S213桥断面的河水边界及河流宽度,结合已有的断面流量数据,通过建立宽度-流量曲线得到河流流量估测模型,模型估测和实测径流量具有较好的一致性(R2=0.82)。该文同时对河宽提取误差进行精度验证,结果表明提取误差对模型的影响较小(R2在0.81～0.83,绝对误差<2%)。为了证明模型的外推性,该文将模型应用于S213桥断面2011—2015年和高崖断面2005—2014年的流量估测,结果表明,两个断面的模拟结果与实测数据均具有较高相关性。综上结果表明,该文的河川径流遥感估算方法具有较好的精度和外推适用性。     

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.     

联合Jason-1与GRACE卫星数据研究全球海平面变化

海平面变化主要由海水质量变化和比容海平面变化组成。联合GRACE时变重力场与Jason-1卫星测高数据分别研究了全球平均海平面及其质量分量与比容分量的季节性变化(2002-09—2008-04),联合两种卫星数据所得平均海平面变化在周年振幅和相位上与WOA05海洋模型结果具有一致性。估算出研究时间段内全球平均海平面变化及其两个主要分量的长期性趋势,在超过6.5a的时间尺度上,全球平均海平面以+2.0±0.4mm/a的速率上升,其中海水质量变化分量的贡献为+1.4±0.4mm/a,比容变化分量的贡献为+0.5±0.3mm/a。     

GGM02 – An improved Earth gravity field model from GRACE

A new generation of Earth gravity field models called GGM02 are derived using approximately 14 months of data spanning from April 2002 to December 2003 from the Gravity Recovery And Climate Experiment (GRACE). Relative to the preceding generation, GGM01, there have been improvements to the data products, the gravity estimation methods and the background models. Based on the calibrated covariances, GGM02 (both the GRACE-only model GGM02S and the combination model GGM02C) represents an improvement greater than a factor of two over the previous GGM01 models. Error estimates indicate a cumulative error less than 1 cm geoid height to spherical harmonic degree 70, which can be said to have met the GRACE minimum mission goals. Electronic Supplementary Material Supplementary material is available in the online version of this article at     

青藏高原GRACE卫星重力长期变化研究

青藏高原隆升是地球上新生代以来最壮观的地质事件之一,对东亚乃至全球大陆动力学研究具有举足轻重的作用,一直是国际地球科学研究的热点区域.随着近年来现代大地测量技术(如GPS、卫星测高、绝对重力、雷达干涉测量等)的蓬勃发展,特别是2002年GRACE重力卫星的成功发射,为研究全球物质分布和季节性变化提供了重要参考依据,同时也为研究青藏高原动力学提供了可靠的观测数据和便捷的观测手段.GRACE卫星发射至今已超过13年,随着资料的累积和数据处理方法的改进与成熟,用GRACE卫星资料研究长期性变化成为新的热点.