Attenuation effect on seasonal basin-scale water storage changes from GRACE time-variable gravity

In order to effectively recover surface mass or geoid height changes from the gravity recovery and climate experiment (GRACE) time-variable gravity models, spatial smoothing is required to minimize errors from noise. Spatial smoothing, such as Gaussian smoothing, not only reduces the noise but also attenuates the real signals. Here we investigate possible amplitude attenuations and phase changes of seasonal water storage variations in four drainage basins (Amazon, Mississippi, Ganges and Zambezi) using an advanced global land data assimilation system. It appears that Gaussian smoothing significantly affects GRACE-estimated basin-scale seasonal water storage changes, e.g., in the case of 800 km smoothing, annual amplitudes are reduced by about 25–40%, while annual phases are shifted by up to 10°. With these effects restored, GRACE-estimated water storage changes are consistently larger than model estimates, indicating that the land surface model appears to underestimate terrestrial water storage change. Our analysis based on simulation suggests that normalized attenuation effects (from Gaussian smoothing) on seasonal water storage change are relatively insensitive to the magnitude of the true signal. This study provides a numerical approach that can be used to restore seasonal water storage change in the basins from spatially smoothed GRACE data.     

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.     

根据人卫激光测距、GRACE和地球物理模型求解地球低阶重力场季节变化

本文利用2002年4月至2010年10月的Lageos1和Lageos2两颗激光卫星观测数据、GRACE以及地球物理模型三种独立的方法计算地球低阶重力场系数J 的变化,根据大气压强数据计算 J 时分别按反变气压计（IB）和非反变气压计(NIB)两种假设进行计算。通过分析 J 的季节特性表明,大气在NIB假设下得到的周年振幅比在IB假设下得到的振幅大3倍左右,相位相差47°;大气和陆地水的质量变化对 J 周年变化的贡献占主导地位,海洋的影响最小;大气、海洋和陆地水得到 J 半年振幅和相位值与SLR得到的振幅和相位值吻合较差,尤其是在IB假设下大气得到的结果与SLR结果相差最大; SLR、GRACE和地球物理模型三种独立方法得到的 J 周年项之间吻合相对较好,GRACE得到的周年振幅比SLR得到的周年振幅大50%左右, SLR观测得到的 J 周年振幅介于在NIB和IB两种假设下地球物理模型得到的结果之间;GRACE与SLR得到的 J 半年项的振幅相同,在IB假设下AOW得到的 J 半年振幅和相位与SLR结果差异最大。     

Annual variations in water storage and precipitation in the Amazon Basin

We combine satellite gravity data from the gravity recovery and climate experiment (GRACE) and precipitation measurements from the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center’s (CPC) Merged Analysis of Precipitation (CMAP) and the Tropical Rainfall Measuring Mission (TRMM), over the period from mid-2002 to mid-2006, to investigate the relative importance of sink (runoff and evaporation) and source (precipitation) terms in the hydrological balance of the Amazon Basin. When linear and quadratic terms are removed, the time-series of land water storage variations estimated from GRACE exhibits a dominant annual signal of 250 mm peak-to-peak, which is equivalent to a water volume change of ~1,800 km³. A comparison of this trend with accumulated (i.e., integrated) precipitation shows excellent agreement and no evidence of basin saturation. The agreement indicates that the net runoff and evaporation contributes significantly less than precipitation to the annual hydrological mass balance. Indeed, raw residuals between the de-trended water storage and precipitation anomalies range from ±40 mm. This range is consistent with stream-flow measurements from the region, although the latter are characterized by a stronger annual signal than our residuals, suggesting that runoff and evaporation may act to partially cancel each other.     

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.     

High-frequency signal and noise estimates of CSR GRACE RL04

A sliding window technique is used to create daily-sampled Gravity Recovery and Climate Experiment (GRACE) solutions with the same background processing as the official CSR RL04 monthly series. By estimating over shorter time spans, more frequent solutions are made using uncorrelated data, allowing for higher frequency resolution in addition to daily sampling. Using these data sets, high-frequency GRACE errors are computed using two different techniques: assuming the GRACE high-frequency signal in a quiet area of the ocean is the true error, and computing the variance of differences between multiple high-frequency GRACE series from different centers. While the signal-to-noise ratios prove to be sufficiently high for confidence at annual and lower frequencies, at frequencies above 3 cycles/year the signal-to-noise ratios in the large hydrological basins looked at here are near 1.0. Comparisons with the GLDAS hydrological model and high frequency GRACE series developed at other centers confirm CSR GRACE RL04’s poor ability to accurately and reliably measure hydrological signal above 3–9 cycles/year, due to the low power of the large-scale hydrological signal typical at those frequencies compared to the GRACE errors.     

Black sea annual and inter-annual water mass variations from space

This study evaluates the performance of two widely used GRACE solutions (CNES/GRGS RL02 and CSR RL04) in deriving annual and inter-annual water mass variations in the Black Sea for the period 2003–2007. It is demonstrated that the GRACE derived water mass variations in the Black Sea are heavily influenced by the leakage of hydrological signals from the surrounding land. After applying the corresponding correction, we found a good agreement with water mass variations derived from steric-corrected satellite altimetry observations. Both GRACE and altimetry show significant annual water mass variations of roughly 7 cm amplitude peaking in May and a semi-annual signal of roughly 3 cm peaking in June and in December. The amplitude of the annual water mass signal varies significantly from year to year and is significantly larger during 2004–2006 than in 2003 and 2007. This is also in agreement with the steric corrected altimetry.     

利用卫星观测数据评估GLDAS与WGHM水文模型的适用性

利用2002—2012年的GLDAS和WGHM模型模拟水文产品，以及重力恢复与气候试验卫星（Gravity Recovery and Climate Experiment，GRACE）观测数据，计算了全球范围内30个主要流域的水储量变化时间序列，从模拟数据与观测数据的年周期振幅、长期趋势项及时空分布一致性等几个方面，对GLDAS和WGHM进行了评估。结果表明，GLDAS的4个子模型都表现出了明显的季节性变化，CLM年周期振幅输出最小，MOSAIC和VIC最大，NOAH居中，且最接近4个子模型的平均值。与GRACE结果相比，约80%流域的GLDAS与WGHM模型年周期振幅输出呈明显低估现象，且GLDAS的低估程度大于WGHM，但靠近北极高纬度地区的流域有相反的情况出现。在长期趋势项方面，三者结果差异较大，尤其是对于面积较小且人类活动影响较大的流域，GLDAS与WGHM模型不能充分反映人类活动的影响，模型输出表现较差，GRACE结果更接近实际情况。此外，还研究了流域水储量长期变化趋势与灌溉率的关系，发现呈现明显下降趋势的流域主要集中在高灌溉率（>10%）地区，而灌溉率是影响流域水储量变化的重要因素之一。     

Comparisons of atmospheric mass variations derived from ECMWF reanalysis and operational fields,over 2003–2011

There are two spurious jumps in the atmospheric part of the Gravity Recovery and Climate Experiment-Atmosphere and Ocean De-aliasing level 1B (GRACE-AOD1B) products, which occurred in January-February of the years 2006 and 2010, as a result of the vertical level and horizontal resolution changes in the ECMWFop (European Centre for Medium-Range Weather Forecasts operational analysis). These jumps cause a systematic error in the estimation of mass changes from GRACE time-variable level 2 products, since GRACE-AOD1B mass variations are removed during the computation of GRACE level 2. In this short note, the potential impact of using an improved set of 6-hourly atmospheric de-aliasing products on the computations of linear trends as well as the amplitude of annual and semi-annual mass changes from GRACE is assessed. These improvements result from 1) employing a modified 3D integration approach (ITG3D), and 2) using long-term consistent atmospheric fields from the ECMWF reanalysis (ERA-Interim). The monthly averages of the new ITG3D-ERA-Interim de-aliasing products are then compared to the atmospheric part of GRACE-AOD1B, covering January 2003 to December 2010. These comparisons include the 33 world largest river basins along with Greenland and Antarctica ice sheets. The results indicate a considerable difference in total atmospheric mass derived from the two products over some of the mentioned regions. We suggest that future GRACE studies consider these through updating uncertainty budgets or by applying corrections to estimated trends and amplitudes/phases.     

利用GRACE时变重力场反演黑河流域水储量变化

黑河流域水储量变化对该区域的生态环境和经济建设等具有重要影响。本文利用2002年8月至2011年6月GRACE（Gravity Recovery and Climate Experiment）时变重力场模型GRGS-EIGEN-GL04,采用去相关滤波P3M6与300km高斯滤波相结合的滤波方法反演了黑河流域陆地水储量变化,扣除GLDAS（Global Land Data Assimilation System）水文模型计算的土壤水和冰雪变化,给出了黑河流域地下水储量的时空变化,并利用张掖地区23口地下水测井数据对地下水反演结果进行了初步验证。研究结果表明：（1）黑河流域陆地水储量整体上呈现减少趋势,与该流域气候变化和CPC水文模型的计算结果具有较好的一致性,其减少速率为2.3cm/a等效水高;（2）黑河流域地下水储量呈现长期减少趋势,其减少速率为2.5cm/a等效水高,上、中游区域地下水储量减少速率相当,下游区域地下水储量减少速率明显小于中上游区域。     

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.     

Accuracy assessment of the monthly GRACE geoids based upon a simulation

The purpose of this paper is to demonstrate the effect of geophysical background model errors that affects temporal gravity solutions provided by the Gravity Recovery And Climate Experiment (GRACE). Initial performance estimates by Dickey et al. (1997) suggested a formal geoid RMS error better than 0.1 mm up to spherical harmonic degree 5. Now that the GRACE gravity models and data are available, it is evident that these original expectations were too optimistic. Our hypothesis is that this is partially explained by errors in geophysical background models that need to be applied in the GRACE data reduction, and that this effect was not considered by Dickey et al. (1997). We discuss the results of a closed-loop simulation, where satellite trajectory prediction software is used for the generation of GRACE range-rate data and GRACE orbit solutions with the help of the Global Positioning System (GPS). During the recovery step in our closed-loop simulation, we show that simulated nuisance signals (based on tide and air pressure model differences) map to a 0.7 mm geoid effect for periods longer than 3 months and to less than 0.4 mm for periods shorter than 3 months. The long-period geoid hydrology signal is at a level of 4.5 mm, while the short-period hydrology is at 0.25 mm. The long-period ocean bottom pressure (OBP) signal maps at 0.8 mm and for short periods it is 0.4 mm. We conclude that short-period effects are difficult to observe by GRACE and that long-period effects, like hydrology, are easier to recover than OBP variations.     

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.     

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.     

The unexpected signal in GRACE estimates of $$C_{20}$$

For science applications of the gravity recovery and climate experiment (GRACE) monthly solutions, the GRACE estimates of \(C_{20}\) (or \(J_{2}\)) are typically replaced by the value determined from satellite laser ranging (SLR) due to an unexpectedly strong, clearly non-geophysical, variation at a period of \(\sim \)160 days. This signal has sometimes been referred to as a tide-like variation since the period is close to the perturbation period on the GRACE orbits due to the spherical harmonic coefficient pair \(C_{22}/S_{22}\) of S2 ocean tide. Errors in the S2 tide model used in GRACE data processing could produce a significant perturbation to the GRACE orbits, but it cannot contribute to the \(\sim \)160-day signal appearing in \(C_{20}\). Since the dominant contribution to the GRACE estimate of \(C_{20}\) is from the global positioning system tracking data, a time series of 138 monthly solutions up to degree and order 10 (\(10\times 10\)) were derived along with estimates of ocean tide parameters up to degree 6 for eight major tides. The results show that the \(\sim \)160-day signal remains in the \(C_{20}\) time series. Consequently, the anomalous signal in GRACE \(C_{20}\) cannot be attributed to aliasing from the errors in the S2 tide. A preliminary analysis of the cross-track forces acting on GRACE and the cross-track component of the accelerometer data suggests that a temperature-dependent systematic error in the accelerometer data could be a cause. Because a wide variety of science applications relies on the replacement values for \(C_{20}\), it is essential that the SLR estimates are as reliable as possible. An ongoing concern has been the influence of higher degree even zonal terms on the SLR estimates of \(C_{20}\), since only \(C_{20}\) and \(C_{40}\) are currently estimated. To investigate whether a better separation between \(C_{20}\) and the higher-degree terms could be achieved, several combinations of additional SLR satellites were investigated. In addition, a series of monthly gravity field solutions (\(60\times 60\)) were estimated from a combination of GRACE and SLR data. The results indicate that the combination of GRACE and SLR data might benefit the resonant orders in the GRACE-derived gravity fields, but it appears to degrade the recovery of the \(C_{20}\) variations. In fact, the results suggest that the poorer recovery of \(C_{40}\) by GRACE, where the annual variation is significantly underestimated, may be affecting the estimates of \(C_{20}\). Consequently, it appears appropriate to continue using the SLR-based estimates of \(C_{20}\), and possibly also \(C_{40}\), to augment the existing GRACE mission.     

重力场恢复与气候实验的石羊河流域水储量变化

为了更好地从空间尺度显示石羊河流域水储量的变化情况,该文利用2003年1月至2014年12月GRACE RL06重力场数据计算其陆地水储量变化,对数据进行预处理以及去相关滤波和300km高斯平滑处理,并利用流域内4个气象站的降水平均数据与GRACE、GLDAS的结果进行对比分析。结果表明,GRACE反演结果与GLDAS水文模型变化趋势基本一致,时间上呈现明显季节性变化,研究区水储量整体呈现0.93mm/a的上升趋势,期间水储量变化波动较大主要与季节性降水有关。     

Evaluation and validation of mascon recovery using GRACE KBRR data with independent mass flux estimates in the Mississippi Basin

The direct recovery of surface mass anomalies using GRACE KBRR data processed in regional solutions provides mass variation estimates with 10-day temporal resolution. The approach undertaken herein uses a tailored orbit estimation strategy based solely on the KBRR data and directly estimates mass anomalies from the GRACE data. We introduce a set of temporal and spatial correlation constraints to enable high resolution mass flux estimates. The Mississippi Basin, with its well understood surface hydrological modelling available from the Global Land Data Assimilation System (GLDAS), which uses advanced land surface modeling and data assimilation techniques, and a wealth of groundwater data, provides an opportunity to quantitatively compare GRACE estimates of the mass flux in the entire hydrological column with those available from independent and reliable sources. Evaluating GRACE’s performance is dependent on the accuracy ascribed to the hydrological information, which in and of itself is a complex challenge (Rodell in Hydrogeol J, doi:, 2007). Nevertheless, the Mississippi Basin is one of the few regions having a large hydrological signal that can support a meaningful GRACE comparison on the spatial scale resolved by GRACE. The isolation of the hydrological signal is dependent on the adequacy of the forward mass flux modeling for tides and atmospheric pressure variations. While these models have non-uniform global performance they are excellent in the Mississippi Basin. Through comparisons with the independent hydrology, we evaluate the effect on the solution of changing correlation times and distances in the constraints, altering the parameter recovery for areas external to the Mississippi Basin, and changing the relative strength of the constraints with respect to the KBRR data. The accuracy and stability of the mascon solutions are thereby assessed, especially with regard to the constraints used to stabilize the solution. We show that the mass anomalies, as represented by surface layer of water within regional cells have accuracy estimates of ±2–3 cm on par with the best hydrological estimates and consistent with our accuracy estimates for GRACE mass anomaly estimates. These solutions are shown to be very stable, especially for the recovery of semi-annual and longer period trends, where for example, the phase agreement for the dominant annual signal agrees at the 10-day level of resolution provided by GRACE. This validation confirms that mascons provide critical environmental data records for a wide range of applications including monitoring ground water mass changes.     

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.     

ENSO影响下的西太平洋地区海陆水储量变化分析

利用2005-01-2016-12的GRACE卫星数据，结合测高、ARGO（array for real-time geostrophic oceanography）、TRMM（tropical rainfall measurement mission）降水数据和MEI（multivariate ENSO index），从海平面、海水质量、海水比容和陆地水储量的非季节性变化分析了厄尔尼诺-南方涛动（El Ni?o/Southern Oscillation，ENSO）对西太平洋及其沿岸地区的影响。在GRACE数据处理过程中考虑了地震构造信号的影响，并采用正演模型法来恢复时变信号。结果表明，西太平洋地区平均海平面（western Pacific mean sea level，WPMSL）变化对ENSO的响应表现为:厄尔尼诺期间海平面下降，拉尼娜期间海平面上升；尤其在2014-2016年厄尔尼诺期间，WPMSL下降了近26.2 mm。比容变化为影响WPMSL非季节性变化的主导因素。澳大利亚和中南半岛水储量异常在年际变化上也较好响应了ENSO，与MEI的相关系数分别为-0.61（滞后3个月）和-0.65（滞后8个月）。长江流域对ENSO的响应主要在中下游区域，2014-2016年厄尔尼诺造成了该时期长江流域水储量达到近几年的极大值。     

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.