GOCE卫星数据确定的全球稳态海面地形和海表地转流

利用GOCE卫星235天的观测数据恢复了200阶次的重力场模型SWJTU-GO01S,结合欧空局提供的最新GOCE重力场模型和CNES-CLS 2011平均海面高模型,计算了全球稳态海面地形和海表地转流,并采用GRACE模型、多源数据同化模型和海洋浮标观测数据对GOCE模型的计算结果进行对比分析.结果表明:由于重力场模型精度和分辨率较高,GOCE计算结果所需的滤波半径小于GRACE结果;GOCE和GRACE模型的计算结果与CNES-CLS09稳态海面地形差异的RMS分别为6 cm和7 cm左右;与海洋浮标实测数据对比发现,GOCE和GRACE的计算结果与实测数据差异明显,但GOCE的计算结果优于GRACE结果,而SWJTU-GO01S与DIR-R4和TIM-R4模型在全球范围内具有较好的一致性.整体而言,GOCE比GRACE数据的计算结果可以反映更小尺度地转流,且计算的精度更高;海洋环流结果和水准数据的对比表明SWJTU-GO01S与DIR-R4和TIM-R4模型的精度符合性较好,三者计算的地转流精度基本相当.     

由GOCE引力场模型和CNES-CLS2010平均海面高计算的稳态海面地形

利用欧空局发布的三组GOCE引力场模型及CNES-CLS 2010平均海面高数据,计算得到了全球的稳态海面地形,进而得到了全球地转流速度图.在此基础上重点对黑潮进行了对比分析.结果表明:GOCE不同组解的稳定性较好,所计算的稳态海面地形的差异基本在厘米量级内,这间接表明了GOCE引力场模型提供的大地水准面的精度达到了厘米量级.此外,通过将GOCE与GRACE相应结果进行对比发现,GOCE可提供更多的局部信息,特别是对于流速快、水流窄的边界流,如黑潮、墨西哥湾流等,GOCE所得结果更加清晰,速度也更精确.     

利用卫星测量技术和小波滤波方法探测表层地转流

根据海面地形的空域频谱特征, 提出用小波滤波器对海面地形进行滤波降噪的方法. 通过对全球及黑潮流系区域的海面地形进行小波滤波和高斯低通滤波降噪后所确定的地转流的比较, 显示前者较之后者更能表现地转流的局部特征. 依据CG01C卫星重力场模型和EGM96重力场模型, 分别联合由卫星测高确定的KMSS04平均海面高模型构造海面地形. 将据小波滤波降噪后所推算出的全球平均地转流、黑潮和热带太平洋区域地转流与海洋学结果的比较, 以及据此两不同重力场模型推算的大地水准面误差对计算地转流流速精度的对比都表明: 重力卫星确定的地球重力场模型较之以前存在的重力场模型在长波部分精度有较大提高. 联合现有卫星重力和卫星测高数据探测的全球平均地转流, 在大、中尺度上与海洋学结果相一致, 这表明从大地测量(空间)角度来研究洋流已达到较高的精度.     

利用多年卫星测高资料研究南海上层环流季节特征

利用10年高精度卫星测高海面高异常网格资料,联合EGM96稳态海面地形模型,构成南海海域合成海面地形的时间序列,并计算了各个时期的南海表层地转流场. 利用卫星跟踪漂流浮标观测结果与相应时期南海地转流场进行对比验证,结果显示本文结果可以很好地反映南海海域一些中小尺度的环流特征. 根据南海各季节多年平均表层环流场结构,对南海环流周年变化规律和季节特征进行了初步的探讨. 研究结果表明,南海表层环流始终处在不断演变过程之中,在时间和空间上都表现出明显的多尺度特征.     

利用GOCE和GRACE卫星观测数据确定静态重力场模型

高精度静态卫星重力场模型在全球海洋环流研究、全球/区域数字高程基准面确定等领域有重要应用,本文研究仅利用GOCE卫星和联合GRACE卫星观测数据确定高精度高阶次静态重力场模型.利用GOCE卫星全周期高精度引力梯度分量(V_xx、V_yy、V_zz和V_xz)观测值基于直接最小二乘法构建300阶次的SGG(Satellite Gravity Gradiometry)法方程,并利用卫星跟踪卫星观测值基于点域加速度法构建130阶SST(Satellite-to-Satellite Tracking)法方程,然后利用方差分量估计联合SGG和SST法方程确定300阶次纯GOCE卫星重力场模型GOSG02S.利用全周期GRACE观测数据由动力学方法解算了180阶次的SWPU-GRACE2021S模型,并将其对应法方程与GOCE卫星法方程联合解算了GRACE和GOCE的联合模型WHU-SWPU-GOGR2022S.分别基于XGM2019模型和GPS水准数据对本文解算的三个模型GOSG02S、SWPU-GRACE2021S...     

利用卫星大地测量技术研究海面动力地形及地转流的进展

随着卫星大地测量技术的发展,平均海平面高度与大地水准面资料的分辨率和精度得到大幅提高,这为确定高精度高分辨率的海面动力地形提供了条件,进而也促进了海面动力地形及地转流研究的发展.本文从数据资料、计算方法、空间尺度分析、误差分析及多源数据融合五个方面总结了目前利用卫星大地测量技术研究海面动力地形及地转流的进展.在此基础上,对目前该研究中存在的问题进行了分析,并对该研究今后的重点发展方向进行了展望.     

GRACE/GOCE扩展重力场模型确定我国1985高程基准重力位的精度分析

高精度高程基准重力位的确定往往依赖于高精度全球重力场模型,其对全球和区域高程基准的高精度统一非常关键,GRACE、GOCE卫星重力计划极大地提高了全球重力场模型中长波的精度.本文首先对GRACE/GOCE卫星重力场模型的内符合和外符合精度进行讨论分析,结果说明卫星重力模型的截断误差影响可达到分米级水平,在确定高程基准重力位时该影响不可忽略.利用EGM2008模型扩展GRACE/GOCE卫星重力场模型至2190阶,可有效减弱卫星重力模型的截断误差影响,但不同模型扩展时的最优拼接阶次不同,其中DIR-1、DIR-5模型对应的最优拼接阶次分别为180阶和220阶,以GPS水准数据检验,扩展模型在中国区域的精度均优于18cm.最后,基于最优拼接阶次获得的扩展重力场模型对我国1985高程基准重力位进行了估计,DIR-5和TIM-5模型对应数值分别为62636853.47m~2·s~(-2)和62636853.49m~2·s~(-2),精度均为1.51m~2·s~(-2);发现在中国区域模型大地水准面与GPS/水准数据的差值存在微弱的系统性倾斜,东西向倾斜约为9cm,南北向倾斜约为1.4cm,考虑倾斜改正后基于DIR-5和TIM-5模型估计我国1985高程基准重力位的精度提高了0.16m~2·s~(-2).     

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,将信号能量集中在研究区域内部,是构建球面局部重力场模型的理想方法.本文根据Slepian方法的特点给出了区域重力场建模及参数优化的步骤,以我国华北地区为例,基于2011-2013多期地面观测确定了区域时变重力场模型,并与同区域由Slepian方法和GRACE卫星数据确定的重力变化进行了对比分析.结果表明:(1)贝叶斯信息量准则可作为确定Slepian展开最佳截断数的有效手段;(2)基于研究区域内现有重复测点数据,能够恢复120阶时变重力场,空间分辨率(半波长)约150km;(3) 2011-2013年间研究区域内GRACE估计结果与120阶地面结果在时空分布的显著趋势上存在较好的对应,证明了本文利用Slepian方法和地面观测所得时变重力场模型的可靠性.本文研究结果可为区域重力场建模提供新的参考,也可为华北地区水资源变化监测、构造活动分析以及地震风险性评估等研究提供高分辨率的时变重力场模型支撑.     

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.     

全球水储量变化的GRACE卫星检测

利用GRACE月尺度变化的地球重力场反演了全球水储量变化,并与陆地水文资料、卫星测高资料及海洋模式得到的结果进行了比对.通过对SOURE台站重力变化的陆地水储量变化计算结果和GRACE重力场系数截断为15阶得到的结果比较,发现两者比较接近,且年周期变化特征明显.对于亚马逊流域,当重力场系数截断为15阶且平滑半径使用106 m时,GRACE反演的区域平均水储量厚度的周年变化振幅为15.6×10-2m,小于使用平滑半径为4×105m的23.7×10-2m.在研究长江流域时,本文对水文资料做球谐系数展开,并与GRACE数据做同样的截断和平滑处理,结果发现GRACE反演的水厚度变化与水文资料结果基本上符合.对于纬度±66°之间的海洋区域,GRACE反演的海水质量变化接近于结合卫星测高和海洋模式得到的结果,但对于2°×2°网格,则在一些区域差异明显,最大超过了0.2 m,中误差为3.8×10-2m.可见,当前GRACE卫星时变重力场只能确定出上千公里及以上尺度区域的水储量变化.     

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.     

Improving Surface Geostrophic Current from a GOCE-Derived Mean Dynamic Topography Using Edge-Enhancing Diffusion Filtering

With increased geoid resolution provided by the gravity and steady-state ocean circulation explorer (GOCE) mission, the ocean’s mean dynamic topography (MDT) can be now estimated with an accuracy not available prior to using geodetic methods. However, an altimetric-derived MDT still needs filtering in order to remove short wavelength noise unless integrated methods are used in which the three quantities are determined simultaneously using appropriate covariance functions. We studied nonlinear anisotropic diffusive filtering applied to the ocean´s MDT and a new approach based on edge-enhancing diffusion (EED) filtering is presented. EED filters enable controlling the direction and magnitude of the filtering, with subsequent enhancement of computations of the associated surface geostrophic currents (SGCs). Applying this method to a smooth MDT and to a noisy MDT, both for a region in the Northwestern Pacific Ocean, we found that EED filtering provides similar estimation of the current velocities in both cases, whereas a non-linear isotropic filter (the Perona and Malik filter) returns results influenced by local residual noise when a difficult case is tested. We found that EED filtering preserves all the advantages that the Perona and Malik filter have over the standard linear isotropic Gaussian filters. Moreover, EED is shown to be more stable and less influenced by outliers. This suggests that the EED filtering strategy would be preferred given its capabilities in controlling/preserving the SGCs.     

Detecting surface geostrophic currents using wavelet filter from satellite geodesy

According to the features of spatial spectrum of the dynamic ocean topography (DOT),wavelet filter is proposed to reduce short-wavelength and noise signals in DOT. The surface geostrophic currents calculated from the DOT models filtered by wavelet filter in global and Kuroshio regions show more detailed information than those from the DOT models filtered by Gaussian filter. Based on a satellite gravity field model (CG01C) and a gravity field model (EGM96),combining an altimetry-derived mean sea surface height model (KMSS04),two mean DOT models are estimated. The short-wavelength and noise signals of these two DOT models are removed by using wavelet filter,and the DOT models asso-ciated global mean surface geostrophic current fields are calculated separately. Comparison of the surface geostrophic currents from CG01C and EGM96 model in global,Kuroshio and equatorial Pacific regions with that from oceanography,and comparison of influences of the two gravity models errors on the precision of the surface geostrophic currents velocity show that the accuracy of CG01C model has been greatly improved over pre-existing models at long wavelengths. At large and middle scale,the surface geostrophic current from satellite gravity and satellite altimetry agrees well with that from oceanography,which indicates that ocean currents detected by satellite measurement have reached relatively high precision.     

应用平滑先验信息方法移除GRACE数据中相关误差

由于GRACE卫星数据解算的时变重力场模型中高阶位系数存在误差,这些误差在重力异常图中表现为南北向的条带噪声,在应用GRACE时变重力场数据时必须进行滤波.本文在空间域引入了一种有效消除GRACE时变重力场条带噪声的平滑先验信息方法,并将其与目前常用的高斯滤波和去相关误差等滤波方法分别应用于合成的质量变化趋势数字模型,检测不同滤波方法消除条带噪声的能力及其对真实信号的影响.滤波结果显示,与目前常用的高斯滤波和去相关误差滤波器相比,本文滤波方法在有效移除条带噪声的同时,具有有效信号幅度衰减小、有效信号形变小以及保存了更多的短波长细节信息等优势;此外,统计结果显示,本文滤波结果在信号最大值、最小值以及残差均方根等方面均与模拟真实信号最为接近.相比300km高斯平滑和组合滤波结果,有效信号振幅的极小值和极大值分别提高了约18%和6%,残差均方根分别降低了25%和33%.说明本文滤波方法移除GRACE相关误差的同时,在保留有效信号方面具有明显的优势.     

Assimilation of geodetic dynamic ocean topography using ensemble based Kalman filter

Estimation of ocean circulation is investigated via assimilation of satellite measurements of the dynamic ocean topography (DOT) into the global finite-element ocean model (FEOM). The DOT was obtained by means of a geodetic approach from carefully cross-calibrated multi-mission altimeter data and GRACE gravity fields. The spectral consistency was achieved by consistently filtering both, the sea surface and the geoid. The filter length is determined by the spatial resolution of the gravity field and corresponds to approximately 241 km half width for the GRACE-based gravity field model ITG-Grace03s.The assimilation of the geodetic DOT was performed by employing a local singular evolutive interpolated Kalman (SEIK) filter in combination with the method of weighting of observations. It is shown that this approach leads to a successful assimilation technique that reduced the RMS difference between the model and the data from 16 cm to 5 cm during one year of assimilation. The ocean model returns an optimized mean dynamic ocean topography. The effects of assimilation on transport estimates across several hydrographic World Ocean Circulation Experiment (WOCE) sections show improvements compared to the FEOM run without data assimilation. As a result of the assimilation, DOT estimates are available in the polar or coastal regions where the geodetic estimates from satellite data alone are not adequate. Furthermore, more realistic features of the ocean can be seen in these areas compared to those obtained using the filtered data fields.     

GOCE, Satellite Gravimetry and Antarctic Mass Transports

In 2009 the European Space Agency satellite mission GOCE (Gravity Field and Steady-State Ocean Circulation Explorer) was launched. Its objectives are the precise and detailed determination of the Earth’s gravity field and geoid. Its core instrument, a three axis gravitational gradiometer, measures the gravity gradient components V _xx , V _yy , V _zz and V _xz (second-order derivatives of the gravity potential V) with high precision and V _xy , V _yz with low precision, all in the instrument reference frame. The long wavelength gravity field is recovered from the orbit, measured by GPS (Global Positioning System). Characteristic elements of the mission are precise star tracking, a Sun-synchronous and very low (260 km) orbit, angular control by magnetic torquing and an extremely stiff and thermally stable instrument environment. GOCE is complementary to GRACE (Gravity Recovery and Climate Experiment), another satellite gravity mission, launched in 2002. While GRACE is designed to measure temporal gravity variations, albeit with limited spatial resolution, GOCE is aiming at maximum spatial resolution, at the expense of accuracy at large spatial scales. Thus, GOCE will not provide temporal variations but is tailored to the recovery of the fine scales of the stationary field. GRACE is very successful in delivering time series of large-scale mass changes of the Antarctic ice sheet, among other things. Currently, emphasis of respective GRACE analyses is on regional refinement and on changes of temporal trends. One of the challenges is the separation of ice mass changes from glacial isostatic adjustment. Already from a few months of GOCE data, detailed gravity gradients can be recovered. They are presented here for the area of Antarctica. As one application, GOCE gravity gradients are an important addition to the sparse gravity data of Antarctica. They will help studies of the crustal and lithospheric field. A second area of application is ocean circulation. The geoid surface from the gravity field model GOCO01S allows us now to generate rather detailed maps of the mean dynamic ocean topography and of geostrophic flow velocities in the region of the Antarctic Circumpolar Current.     

Joint altimetric and in-situ data assimilation using the GRACE mean dynamic topography: a 1993–1998 hindcast experiment in the Tropical Pacific Ocean

The altimetric satellite signal is the sum of the geoid and the dynamic topography, but only the latter is relevant to oceanographic applications. Poor knowledge of the geoid has prevented oceanographers from fully exploiting altimetric measurements through its absolute component, and applications have concentrated on ocean variability through analyses of sea level anomalies. Recent geodetic missions like CHAMP, GRACE and the forthcoming GOCE are changing this perspective. In this study, data assimilation is used to reconstruct the Tropical Pacific Ocean circulation during the 1993–1996 period. Multivariate observations are assimilated into a primitive equation ocean model (OPA) using a reduced order Kalman filter (the Singular Evolutive Extended Kalman filter). A 6-year (1993–1998) hindcast experiment is analyzed and validated by comparison with observations. In this experiment, the new capability offered by an observed absolute dynamic topography (built using the GRACE geoid to reference the altimetric data) is used to assimilate, in an efficient way, the in-situ temperature profiles from the TAO/TRITON moorings together with the T/P and ERS1&2 altimetric signal. GRACE data improves compatibility between both observation data sets. The difficulties encountered in this regard in previous studies such as Parent et al. (J Mar Syst 40–41:381–401, 2003) are now circumvented. This improvement helps provide more efficient data assimilation, as evidenced, by assessing the results against independent data. This leads in particular to significantly more realistic currents and vertical thermal structures.     

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.