基于多源数据分析维多利亚湖流域水储量变化

本文利用CSR发布的GRACE RL06时变重力场模型,结合两种水文模式、卫星测高、降雨和蒸散等多源数据,从多个角度综合系统地分析维多利亚湖流域2003-01—2017-06的陆地水储量变化.比较了正向建模方法和单一尺度因子对泄漏误差的改正效果,经对比采用正向建模方法在此流域效果更好.基于多源数据得出以下三点与此前研究不同的结论:(1)GRACE RL06版本数据探测到流域内的水储量在2003-01—2017-06呈增加趋势,球谐位系数和Mascon产品得到的变化速率分别为14.9 mm·a^-1和16.7 mm·a^-1,观测误差小于RL05版本的结果,RL05版本低估了流域水储量的变化速率;(2)2013-01—2016-02期间GRACE和测高探测到湖泊水量增长,而水文模式探测到流域内水储量减少,推测这一现象由大坝蓄水造成;(3)受El Ni1o事件影响,2016-03—2017-06流域降雨减少,流域水储量减少,GRACE球谐位系数和Mascon探测到的变化速率分别为-100.3 mm·a^-1和-129.7 mm·a...     

卫星重力反演的短弧长积分法研究

给出了统一求解球谐位系数、弧段边界轨道改正向量、有偏距离改正及加速度计偏差的短弧长积分法,通过对力模型梯度改正减弱了轨道误差对反演地球重力场的影响.采用GRACE卫星1个月的实测轨道及星间距离数据计算表明,短弧长积分法加了梯度改正的精度比不加梯度改正整体提高了近一倍,且该方法在高阶次位系数的精度优于动力学法.基于GRA...     

基于Slepian方法和地面重力观测确定时变重力场模型:以2011-2013年华北地区数据为例

时变重力场是研究地球系统内部物质运动和时空演化过程的有效途径.目前广泛使用的GRACE时变重力场模型受限于其空间分辨率(约400 km),难以探测较小空间尺度的重力变化.本文首次尝试利用Slepian局部谱分析方法和多期地面重力观测确定更高空间分辨率的时变重力场模型.Slepian方法通过构建研究区域内的正交基函数,将...     

利用GRACE空间重力测量监测长江流域水储量的季节性变化

2002年3月成功发射的美德合作重力卫星计划GRACE(Gravity Recovery And Climate Experiment)已经开始提供阶次数达到120、时间分辨率为约1个月的地球重力场模型时变序列. GRACE的星座由两颗相距约220 km, 高度保持300~500 km, 而倾角保持约90°的近极轨卫星组成. 由于采用星载GPS和非保守力加速度计等高精度定轨技术以及高精度的星-星跟踪数据反演地球重力场, 在几百公里和更大空间尺度上, GRACE重力场的精度大大超过此前的卫星重力观测. 根据GRACE时变重力场反演的地球系统质量重新分布对固体地球物理、海洋物理、气候学以及大地测量等应用有重要的意义. 在长期时间尺度上, GRACE的结果可用于研究北极冰的变化, 并进而研究极冰融化对全球气候变化, 特别是对海平面长期变化的影响. 在季节性时间尺度上, 利用GRACE重力场的精度足以揭示平均小于1 cm的地表水变化或小于1 mbar的海底压强变化. 除了巨大的社会和经济效益外, 这些变化对了解地球系统的物质循环(主要是水循环)和能量循环有非常重要的意义. 利用2002年4月至2003年12月之间共15个月的GRACE时变重力场揭示了全球水储量的明显季节性变化, 并重点分析了中国长江流域水储量的变化. 结果表明长江流域水储量周年变化幅度可达到3.4 cm等效水高, 其最大值出现在春季和初秋. 根据GRACE时变重力场反演的水储量变化与两个目前最好的全球水文模型的符合相当好, 其差别小于1 cm等效水高. 研究表明现代空间重力测量技术在监测一些大流域的水储量变化(如长江流域)、全球水循环和气候变化上有巨大的应用潜力.     

卫星跟踪卫星技术反演局部地表物质迁移的MASCON方法研究

MASCON方法是直接利用GRACE任务的卫星跟踪卫星技术研究地表浅层物质运动的一种有效技术手段.该方法相较Stokes球谐系数法在一定程度上克服了时变信号的滤波问题,能有效解决该方法时变重力场的南北条带效应.本文在对现有MASCON方法深入研究的基础上对其进行了改进,提出引入卫星精密轨道作为观测值,联合高低跟踪和低低跟踪两类观测数据,实现MASCON参数及有关动力学模型参数求解的思路,在不影响时变信号主要由星间距离变率观测值提供的前提下,采用方差分量估计方法合理定权,充分利用轨道数据的绝对基准作用,用一种改进的途径实现了MASCON方法.利用2008年GRACE的卫星重力观测数据,获得了亚马逊地区的地表物质迁移结果,并与GLDAS水文模型、CSR RL05球谐系数和JPL MASCON方法计算的水储量变化进行比较,表明一致性较好,验证了本文所提MASCON方法解算思路的可靠性,该方法为研究局部地区的地表物质迁移提供了一种可行手段.     

一种反演地幔横向密度差异的方法

重力位球谐系数及板块运动速度是两种独立的地球物理观测资料,但二者同时又是地幔内横向密度差异及与之相联系的地幔流动的结果,从而,中长波重力异常与板块运动的观测提供了探索地幔横向非均匀的一条途径。本文根据适合于低雷诺流动的最小粘滞损耗原理,利用张量场及矢量场的标量分解与传播子解的数学方法,将观测的重力位球谐系数和板块运动速度作为约束条件,发展了一种反演地幔横向密度差异的方法。     

CHAMP卫星时代全球岩石圈磁场模型的近似误差估计

岩石圈磁场模型的误差估计是地磁导航、定量地球物理与地质解释的重要基础.本文基于统计学观点,将由CHAMP卫星磁测数据构建的系列具有代表性的全球岩石圈磁场模型视为随机观测信号,对其在球谐域与空间域分别进行平均值与标准差的统计分析,得到CHAMP卫星时代全球岩石圈磁场模型的球谐域与空间域近似误差水平、误差分布特征、不同类型磁场分量之间的误差比例关系以及全球岩石圈磁场能量与误差水平随高度的衰减特征.本文所提的误差估计方法与结果,尽管存在一定的近似,但是可以为估计与了解岩石圈磁场模型在球谐域与空间域的误差水平与分布特征提供参考资料与定量依据.     

区域面波群速度反演的球谐函数法

一个定义在球面局部区域的复杂的面波速度函数如果直接利用球谐函数拟合可能需要展开到很高阶的球谐系数．通过保角变换，把一个球面局部区域扩展到球面上更大的区域上，变换过程中面波速度保持不变，在变换后的球面域上用球谐函数来拟合速度函数，达到降低球谐系数阶数的目的，使面波群速度的反演变成了球谐系数的线性化反演.通过球谐系数分析，可得到反演的分辨率.该方法不仅适用于面波群速度反演，同样适用于各种球面区域场的分析.     

Sq电流体系的反演与地磁日变模型的建立

地磁场的标量位满足拉普拉斯方程.在球坐标系中,拉普拉斯方程的解可以写成球谐级数的形式.借助球谐分析的方法,地磁场可以被分为起源于地球内部的内源场和起源于地球外部的外源场.本文的内容主要包括:(1)阐述了利用球谐分析来反演Sq电流体系的方法.反演了1997年各月的Sq空间等效电流体系,并重点分析了南北半球Sq空间等效电流体系的位形和强度随季节的变化情况.(2)基于1997年的地磁观测数据建立各月静日期间中国地区地磁日变随纬度和AE指数变化的模型.将模型的计算结果与地磁台站的观测数据进行了对比分析.     

在地磁学与地球重力学中的球谐分析

球谐分析在地磁学与地球重力学中得到广泛的应用.由于地球磁场与地球引力场的不同,球谐表述有所不同.地磁场的高斯分析（球谐分析）的结果表明,地磁场没有单极子,而引力场有,地磁场有内外源场之分,而地球引力场只有内源场,地磁场的球谐级数收敛快,地磁场高斯级数所用的蒂合勒让德函数是Schmidt半标准化的,而地球引力场中用的是全标准化的,地磁场的高斯系数随时间变化快,每5年产生一个IGRF（国际地磁参考场）, 而引力场的变化是与地质变化有关,相对于地磁场来说,是缓慢的. 地磁场的高斯分析还存在一个唯一性问题.     

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.     

Calibration/Data Assimilation Approach for Integrating GRACE Data into the WaterGAP Global Hydrology Model (WGHM) Using an Ensemble Kalman Filter: First Results

We introduce a new ensemble-based Kalman filter approach to assimilate GRACE satellite gravity data into the WaterGAP Global Hydrology Model. The approach (1) enables the use of the spatial resolution provided by GRACE by including the satellite observations as a gridded data product, (2) accounts for the complex spatial GRACE error correlation pattern by rigorous error propagation from the monthly GRACE solutions, and (3) allows us to integrate model parameter calibration and data assimilation within a unified framework. We investigate the formal contribution of GRACE observations to the Kalman filter update by analysis of the Kalman gain matrix. We then present first model runs, calibrated via data assimilation, for two different experiments: the first one assimilates GRACE basin averages of total water storage and the second one introduces gridded GRACE data at \(5^\circ\) resolution into the assimilation. We finally validate the assimilated model by running it in free mode (i.e., without adding any further GRACE information) for a period of 3 years following the assimilation phase and comparing the results to the GRACE observations available for this period.     

Improved daily GRACE gravity field solutions using a Kalman smoother

Different GRACE data analysis centers provide temporal variations of the Earth's gravity field as monthly, 10-daily or weekly solutions. These temporal mean fields cannot model the variations occurring during the respective time span. The aim of our approach is to extract as much temporal information as possible out of the given GRACE data. Therefore the temporal resolution shall be increased with the goal to derive daily snapshots. Yet, such an increase in temporal resolution is accompanied by a loss of redundancy and therefore in a reduced accuracy if the daily solutions are calculated individually. The approach presented here therefore introduces spatial and temporal correlations of the expected gravity field signal derived from geophysical models in addition to the daily observations, thus effectively constraining the spatial and temporal evolution of the GRACE solution. The GRACE data processing is then performed within the framework of a Kalman filter and smoother estimation procedure.The approach is at first investigated in a closed-loop simulation scenario and then applied to the original GRACE observations (level-1B data) to calculate daily solutions as part of the gravity field model ITG-Grace2010. Finally, the daily models are compared to vertical GPS station displacements and ocean bottom pressure observations.From these comparisons it can be concluded that particular in higher latitudes the daily solutions contain high-frequent temporal gravity field information and represent an improvement to existing geophysical models.     

Performance of GOCE and GRACE-derived mean dynamic topographies in resolving Antarctic Circumpolar Current fronts

Presently, two satellite missions, Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady-state Ocean Circulation Explorer (GOCE), are making detailed measurements of the Earth’s gravity field, from which the geoid can be obtained. The mean dynamic topography (MDT) is the difference between the time-averaged sea surface height and the geoid. The GOCE mission is aimed at determining the geoid with superior accuracy and spatial resolution, so that a more accurate MDT can be estimated. In this study, we determine the mean positions of the Antarctic Circumpolar Current fronts using the purely geodetic estimates of the MDT constructed from an altimetric mean sea surface and GOCE and GRACE geoids. Overall, the frontal positions obtained from the GOCE and GRACE MDTs are close to each other. This means that these independent estimates are robust and can potentially be used to validate frontal positions obtained from sparse and irregular in situ measurements. The geodetic frontal positions are compared to earlier estimates as well as to those derived from MDTs based on satellite and in situ measurements and those obtained from an ocean data synthesis product. The position of the Sub-Antarctic Front identified in the GOCE MDT is found to be in better agreement with the previous estimates than that identified in the GRACE MDT. The geostrophic velocities derived from the GOCE MDT are also closer to observations than those derived from the GRACE MDT. Our results thus show that the GOCE mission represents an improvement upon GRACE in terms of the time-averaged geoid.     

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.     

Groundwater Monitoring Using GRACE and GLDAS Data after Downscaling Within Basaltic Aquifer System

Gravity Recovery and Climate Experiment (GRACE) satellite mission is ground-breaking information hotspot for the evaluation of groundwater storage. The present study aims at validating the sensitivity of GRACE data to groundwater storage variation within a basaltic aquifer system after its statistical downscaling on a regional scale. The basaltic aquifer system which covers 82.06% area of Maharashtra state in India, is selected as the study area. Five types of basaltic aquifer systems with varying groundwater storage capacities, based on hydrologic characteristics, have been identified within the study area. The spatial and seasonal trend analysis of observed in situ groundwater storage anomalies (ΔGWSano) computed from groundwater level data of 983 wells from the year 2002 to 2016, has been performed to analyze the variation in groundwater storages in the different basaltic aquifer system. The groundwater storage anomalies (ΔGWSDano) have been derived from GRACE Release 05 (RL05) after removing the soil moisture anomaly (ΔSMano) and canopy water storage anomaly (ΔCNOano) obtained from Global Land Data Assimilation System (GLDAS) land surface models (NOAH, MOSAIC, CLM and VIC). The artificial neural network technique has been used to downscale the GRACE and GLDAS data at a finer spatial resolution of 0.125°. The study shows that downscaled GRACE and GLDAS data at a finer spatial resolution is sensitive to seasonal groundwater storage variability in different basaltic aquifer systems and the regression coefficient R has been found satisfactory in the range of 0.696 to 0.818.     

Seismologic applications of GRACE time-variable gravity measurements

The Gravity Recovery and Climate Experiment (GRACE) has been measuring temporal and spatial variations of mass redistribution within the Earth system since 2002. As large earthquakes cause significant mass changes on and under the Earth’s surface, GRACE provides a new means from space to observe mass redistribution due to earthquake deformations. GRACE serves as a good complement to other earthquake measurements because of its extensive spatial coverage and being free from terrestrial restriction. During its over 10 years mission, GRACE has successfully detected seismic gravitational changes of several giant earthquakes, which include the 2004 Sumatra–Andaman earthquake, 2010 Maule (Chile) earthquake, and 2011 Tohoku-Oki (Japan) earthquake. In this review, we describe by examples how to process GRACE time-variable gravity data to retrieve seismic signals, and summarize the results of recent studies that apply GRACE observations to detect co- and post-seismic signals and constrain fault slip models and viscous lithospheric structures. We also discuss major problems and give an outlook in this field of GRACE application.     

一种新的综合物理指数构建及其在强降水预报中的应用

强降水是洪灾及相关衍生灾害的最主要原因之一,而过去单靠某一种变量诊断预报强降水,具有较大难度.本文在已有研究的基础上,根据强降水发生发展的物理机制,将引起降水的热力、动力和水汽条件综合考虑,尝试性地构建了一个新的综合指数THP(Temperature,Helicity and Precipitable water).然后针对两次强降水过程,利用NCEP/NCAR 1°×1°的再分析资料和地面常规观测资料,对THP指数进行了诊断分析,并选用2012年7月1日—8月15日的降水实况,对该指数进行了普适性检验.结果表明:(1)THP指数的变化可以有效表征强降水过程的发展和移动.对于降水落区的预报,THP指数的大值区与未来6h的降水中心基本对应;对于降水发生时刻的预报,THP指数的位相变化超前于地面降水的变化,具有较好的指示性;(2)对于高空槽前型降水,THP指数对降水强度也有一定的诊断意义,且普适性检验表明,该指数在我国中东部地区的盛夏期间具有良好的适用性;(3)基于配料法的思想,THP指数将有利于强降水出现的、具有清晰物理意义的信号进行了集成,相比于表征单一物理量的指数,其稳定性得到了增强.     

海潮误差对GRACE时变重力场解算的影响研究

海潮误差是GRACE时变重力场反演中重要的误差源,目前发布的海潮模型中主要包含振幅较大的主潮波分量模型,在时变重力场反演中次潮波的影响也是不可忽略的,因此,GRACE时变重力场反演中的海潮误差主要包括受限于海潮模型误差和次潮波影响.本文利用轨道模拟方法检测了短周期潮波的混频周期以及次潮波对ΔC20,ΔC30的时序特征,并进一步通过轨道模拟结果分析了海潮误差对时变重力场反演的影响,然后通过实测数据解算分析了海潮误差对当前GRACE时变重力场解算的影响,研究发现:(1)利用轨道模拟能够有效地检测短周期潮波的混频周期;(2)时变重力场解算过程中,次潮波的影响大于海潮模型误差的影响;(3)海潮模型误差以及次潮波影响是当前GRACE没有达到基准精度的重要因素之一.