GRACE时变重力位系数扇形滤波算法分析

卫星重力探测技术为监测全球陆地水储量变化提供了新的技术手段。采用Level-2 Release-05版本GRACE时变重力场模型数据计算了2010年全球陆地水储量的月变化;着重研究了扇形滤波对反演结果的影响;并结合GLDAS水文模型数据对反演结果进行了验证分析。实验结果表明:GRACE反演结果 GLDAS水文模型结果在时空分布上符合较好;扇形滤波能够削弱GRACE时变重力场模型的高阶项误差影响,有效去除反演结果中的条带状噪声。     

利用GRACE数据探测长江流域水储量变化

利用2003年1月至2012年4月间109个月的GRACE时变卫星重力数据,反演得到了长江流域的陆地水储量变化,并对三个典型区域的水储量变化做了分析。结果显示GRACE数据能有效揭示长江流域水储量变化的季节性变化及其长期的变化趋势,流域内的水储量变化受气候因素的影响较大。     

利用GRACE卫星Level-1B数据反演陆地水储量变化的方法研究

卫星重力探测技术为监测陆地水储量变化提供了新的技术手段。对利用GRACE卫星Level-1B数据反演地球陆地水储量变化的重力位差法和Mascon方法的数学模型作了详细推导分析,总结两种方法的特点和解算处理步骤。推导过程表明:重力位差法和Mascon方法在反演时只采用卫星飞临研究区域上空时的观测数据,能够提高反演结果的空间分辨率,比传统的球谐系数法更具优势;Mascon方法在解算时还引入了时空约束方程,进一步提高了反演结果的时空分辨率。     

基于GRACE/GRACE-FO反演华北平原2002—2021年水储量变化

针对华北平原水资源分布不均的问题，该文利用2002年4月—2021年12月共237个月的重力恢复和气候实验(GRACE)卫星、GRACE-FO卫星重力数据对华北平原的水储量变化情况进行了研究，采用奇异谱插值填补GRACE与GRACE-FO间的空白期数据，并联合3家Mascon产品、全球陆面同化系统水文模型与全球降水气候中心降水数据进行综合性比较和分析，实现了对华北地区水储量时空变化情况的探究。结果表明，华北地区陆地水储量整体呈下降趋势，亏损速率为-0.927 6 cm/a,且具有明显的季节特征，与降水量的变化情况一致，经过相关性分析，GRACE、GRACE-FO与3个Mascon产品反演的水储量变化存在较高的相关性，相关系数均在0.89以上。     

联合GRACE与TRMM探测阿富汗水储量能力及其发生洪水的可能性

联合重力恢复和气候探测任务(gravity recovery and climate experiment,GRACE)确定的陆地水储量变化以及降水测量卫星任务(tropical rainfall measuring mission satellite,TRMM)提供的降水观测数据,探测局部地区发生洪水的可能性,是一种非常有用的遥测方法。本文提出了一种改进的方法来探测阿富汗陆地水储量能力及其发生洪水的可能性。首先,根据GRACE数据确定的陆地水储量变化获取改进的水储量不足,进而估计阿富汗水储量能力;其次,联合TRMM降水数据,建立阿富汗洪水因子模型;最后,将阿富汗洪水因子结果与中国气象局国家气候中心观测图进行对比。结果表明,洪水因子与中国气象局国家气候中心观测结果基本吻合,并从时间和空间角度真实地反应了阿富汗地区发生的洪水。因此,联合GRACE和TRMM卫星观测数据可探测阿富汗发生洪水的可能性,并为研究区域洪水预警提供了新的有利工具。     

利用独立成分分析法研究新疆地区陆地水储量及其地壳垂向变化

中国新疆地区水文气候变化复杂,其水储量变化及其负荷形变特征的精确提取极为重要。采用卫星重力数据GRACE(gravity recovery and climate experiment）反演新疆地区2010—2014年陆地水储量变化,利用独立成分分析法（independent component analysis,ICA）分解时空模式,提取时空特征信号。在此基础上,反演陆地水负荷迁移引起的地壳垂向变化,引入重力位系数与负荷勒夫数一阶项改正,回加非潮汐大气与海洋信号,结合尺度因子法校正GRACE反演结果,引入全球降水气候计划月降水资料分析形变影响,将其与测区12座连续运行参考站形变位移进行定量比较,重点分析各测站陆地水负荷信号与全球导航卫星系统（global navigation satellite system,GNSS）垂直位移的相关关系。结果表明,经ICA方法分解的新疆地区陆地水储量呈现多时间尺度特征,表现为明显的周年与长期变化;周年信号在西部帕米尔高原附近尤为显著;长期变化以逐年减少为主,在乌鲁木齐西部、天山一带信号较强;总体上,陆地水负荷垂直形变的时间序列波动幅度相对较小,幅值...     

全球陆地水储量对检测同震重力变化的影响

以2011年日本Mw9.0地震为例,探讨了同震重力变化理论模拟计算所涉及到的几个关键问题,并利用GLDAS全球陆地水储量模型对GRACE卫星检测到的同震重力变化进行了修正。结果表明,水文效应变化振幅达4μGal,该影响不可忽略。     

SWARM监测松辽流域陆地水储量变化的适用性分析

针对GRACE与GRACE-FO卫星存在衔接空白且卫星加速度计已出现受损的情况，SWARM卫星监测可作为一种有效补充的技术手段。本文选择ASU、IGG和COST-G等机构的SWARM时变模型监测松辽流域陆地水储量变化，并与GRACE、GRACE-FO时变模型进行比较。结果表明：(1)各SWARM时变模型的前10阶位系数与GRACE模型精度接近，其中IGG-SWARM模型经1200 km高斯滤波后的信噪比，相较于ASU和COST-G模型分别高62.47%、55.99%;(2)IGG-SWARM时变模型可探测松辽流域大尺度陆地水储量的时空变化特征，识别流域内的显著旱涝事件，与GRACE、GRACE-FO时变模型均反映出松辽流域在2015年7月—2020年12月的陆地水储量整体呈上升趋势，两者在数据重叠时段的相关系数可达0.6以上。因此，SWARM时变模型可适用于监测松辽流域的陆地水储量变化研究。     

利用GRACE、GPS和绝对重力数据监测斯堪的纳维亚陆地水储量变化

重力卫星GRACE(gravity recovery and climate experiment)监测斯堪的纳维亚半岛陆地水储量变化会受到冰川均衡调整(GIA)信号的严重影响。首先根据该地区绝对重力和GPS并址观测数据计算了GIA重力和垂直位移的实测线性比值,利用该比值和GPS网观测的垂直位移速度场得到了GIA重力。然后,对GRACE观测的重力变化速率进行GIA重力改正,进而可分离陆地水储量变化趋势,避免了使用GIA模型所带来的巨大不确定性,并根据观测数据完整估计了所得结果的不确定性。最后与水文模型作对比分析。结果表明,实测的GIA重力-垂直位移线性比值为0.148±0.020μGal/mm(1Gal=10-2 m/s2),该结果检验了Wahr的理论近似值且与北美实测的结果非常接近。2003年1月至2011年3月期间,斯堪的纳维亚半岛陆地水储量存在明显的增加趋势,信号的主体位于半岛南端的维纳恩湖附近,总的水量增加速率为4.6±2.1km3/a,数据观测期间的累积增加水量为38±17km3。研究结果与WGHM水文模型的结果有较好的一致性,相关系数达到0.69,而与GLDAS水文模型的相关性略小。     

GRACE与GRACE Follow-On重力卫星数据揭示出的黄河流域2002—2020年干旱特征

研究黄河流域干旱时空变化特征,对认知黄河流域水资源演化规律具有重要意义。本文充分利用GRACE(gravity recovery and climate experiment)与GRACE-FO(GRACE Follow-On)重力卫星在大尺度范围下监测水文信息变化中的优势,基于2002年4月至2020年7月GRACE和GRACE-FO RL06 Mascon数据,计算了黄河流域陆地水储量异常(terrestrial water storage anomaly, TWSA)及对应的水储量亏损赤字(water storage deficit index, WSDI),据此分析了黄河流域上游、中下游干旱事件及其严重性、干旱持续时间、平均与最大水储量赤字等干旱特征,并与其他4种常用干旱指数,标准降水蒸散发指数(standardized precipitation evaporation index, SPEI)、自矫正帕尔默干旱指数(self correct-Palmer drought severity index, sc-PDSI)、标准化降水指数(standardized precip...     

联合GRACE和GLDAS数据的河南省地下水储量反演与时空变化分析

针对利用传统监测手段难以高效获取地下水储量观测数据的问题,基于GRACE重力卫星的大尺度水资源储量反演已成为当前水资源调查的研究热点。本文利用2012-2016年CSR机构发布的GRACE RL06月解数据,通过等效水高反演得到河南省陆地水储量时序结果,扣除由同期GLDAS水文模型计算得到的地表水储量时序数据,从而得到河南省地下水储量时序变化数据结果。经与地下水位监测井实测数据进行对比验证,相关系数显著性水平达0.01,表明本文算法流程具有较高的可靠性。进一步的统计分析结果表明,河南省北部地区的地下水储量呈亏损态势,最大变化率超过26 mm/a;河南省中部和东部地区地下水储量有一定盈余,最大变化率超过16 mm/a,相关结果数据与河南省水利局公布的全省主要地下水超采区范围吻合。本文旨在利用GRACE重力卫星数据与GLDAS水文模型反演获取河南省地下水储量空间分布差异及演变趋势,相关算法流程可为广域地下水储量调查监测提供技术支撑;研究数据可为该区域地下水资源的合理利用与保护提供参考。     

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.     

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。     

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.     

GRACE时变重力数据后处理方法评价

针对GRACE Level2卫星时变重力数据后处理方法如何评价的问题,该文以中国数字地震观测网络获得的青藏高原地区地面重力变化图像为参考,基于平均结构相似性等图像相似度指标,研究了与该区域地面重力观测同期、不同后处理方法得到的GRACE卫星重力变化图像的可靠性。结果显示,GRACE卫星重力和地面重力观测结果具有一定的可比性,滑动窗口去相关滤波和高斯400 km滤波的组合方法可以获得最优的处理效果。本文的方法和结论对GRACE及GRACE Follow-On卫星重力数据应用中后处理方法和参数的选取有一定的借鉴意义。     

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。     

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.     

Localized spectral analysis of global satellite gravity fields for recovering time-variable mass redistributions

A spatiospectral localization method is discussed for processing the global geopotential coefficients from satellite mission data to investigate time-variable gravity. The time-variable mass variation signal usually appears associated with a particular geographical area yielding inherently regional structure, while the dependence of the satellite gravity errors on a geographical region is not so evident. The proposed localization amplifies the signal-to-noise ratio of the (non-stationary) time-variable signals in the geopotential coefficient estimates by localizing the global coefficients to the area where the signal is expected to be largest. The results based on localization of the global satellite gravity coefficients such as Gravity Recovery And Climate Experiment (GRACE) and Gravity and Ocean Circulation Explorer (GOCE) indicate that the coseismic deformation caused by great earthquakes such as the 2004 Sumatra–Andaman earthquake can be detected by the low-low tracking and the gradiometer data within the bandwidths of spherical degrees 15–30 and 25–100, respectively. However, the detection of terrestrial water storage variation by GOCE gradiometer is equivocal even after localization.