Temporal Gravity Field Research Articles

HUST-Grace2024: a new GRACE-only gravity field time series based on more than 20 years of satellite geodesy data and a hybrid processing chain

Abstract. To improve the accuracy of monthly temporal gravity field models for the Gravity Recovery and Climate Experiment (GRACE) and the GRACE Follow-On (GRACE-FO) missions, a new series named HUST-Grace2024 is determined based on the updated L1B datasets (GRACE L1B RL03 and GRACE-FO L1B RL04) and the newest atmosphere and ocean de-aliasing product (AOD1B RL07). Compared to the previous HUST temporal gravity field model releases, we have made the following improvements related to updating the background models and the processing chain: (1) during the satellite onboard events, the inter-satellite pointing angles are calculated to pinpoint outliers in the K-band ranging (KBR) range-rate and accelerometer observations. To exclude outliers, the advisable threshold is 50 mrad for KBR range rates and 20 mrad for accelerations. (2) To relieve the impacts of KBR range-rate noise at different frequencies, a hybrid data-weighting method is proposed. Kinematic empirical parameters are used to reduce the low-frequency noise, while a stochastic model is designed to relieve the impacts of random noise above 10 mHz. (3) A fully populated scale factor matrix is used to improve the quality of accelerometer calibration. Analyses in the spectral and spatial domains are then implemented, which demonstrate that HUST-Grace2024 yields a noticeable reduction of 10 % to 30 % in noise level and retains consistent amplitudes of signal content over 48 river basins compared with the official GRACE and GRACE-FO solutions. These evaluations confirm that our aforementioned efforts lead to a better temporal gravity field series. This data set is identified with the following DOI: https://doi.org/10.5880/ICGEM.2024.001 (Zhou et al., 2024).

A spatial-varying non-isotropic Gaussian-based convolution filter for smoothing GRACE-like temporal gravity fields

A spatial-varying non-isotropic Gaussian-based convolution filter for smoothing GRACE-like temporal gravity fields

Gravity field recovery of inter-satellite links between Beidou navigation satellite system (BDS) and LEO based on geodesy and time reference in space (GETRIS)

The goal of this contribution is to construct the inter-satellite links (ISLs) between Global Navigation Satellite System (GNSS) and Low Earth Orbit (LEO) satellite to recover the Earth’s gravity field based on the concept of Geodesy and Time Reference in Space (GETRIS). Taking the constellation of the Beidou Navigation Satellite System (BDS) as an example, several types of high-low satellite-to-satellite tracking (H-L SST) modes combining BDS and GETRIS are used to research the tracking mode of high orbit satellites and the distribution of LEO satellite constellations to explore the optimal mode for gravity field recovery. The effects of multiple H-L SST modes on the accuracy of gravity field recovery are studied. In addition, the contribution of each error source is also analyzed. Finally, this study varies LEO satellite constellations to show reduced errors in the temporal gravity field solutions for the improved ISLs. The results showed that the Inclined GeoSynchronous Orbit (IGSO) satellite greatly improved the Geosynchronous orbit (GEO) satellite tracking LEO satellite mode in the high latitude regions. Compared with the Medium Earth Orbit (MEO) satellite tracking LEO satellite, the error of gravity field recovered by combining with GEO, IGSO and MEO can be reduced by 16 %. The largest error is the non-tidal signal, followed by the ocean tidal model difference, and the smallest is the instrument error. For a single LEO satellite, the combination model is more sensitive to the satellite orbital altitude, the cumulative error was decreased from 5.08 mm (550 km) to 0.33 mm (250 km). For LEO constellations, adding inclined orbit satellites can improve the accuracy of the solution to some extent. But the optimal solution can be obtained by the constellation composed of polar orbit satellites with different Right Ascension of Ascending Node (RAAN), the cumulative errors are 0.27 mm (two satellites), 0.19 mm (three satellites), and 0.19 mm (four satellites).

High-resolution temporal gravity field data products: Monthly mass grids and spherical harmonics from 1994 to 2021

Since April 2002, Gravity Recovery and Climate Experiment (GRACE) and GRACE-FO (FollowOn) satellite gravimetry missions have provided precious data for monitoring mass variations within the hydrosphere, cryosphere, and oceans with unprecedented accuracy and resolution. However, the long-term products of mass variations prior to GRACE-era may allow for a better understanding of spatio-temporal changes in climate-induced geophysical phenomena, e.g., terrestrial water cycle, ice sheet and glacier mass balance, sea level change and ocean bottom pressure (OBP). Here, climate-driven mass anomalies are simulated globally at 1.0° × 1.0° spatial and monthly temporal resolutions from January 1994 to January 2021 using an in-house developed hybrid Deep Learning architecture considering GRACE/-FO mascon and SLR-inferred gravimetry, ECMWF Reanalysis-5 data, and normalized time tag information as training datasets. Internally, we consider mathematical metrics such as RMSE, NSE and comparisons to previous studies, and externally, we compare our simulations to GRACE-independent datasets such as El-Nino and La-Nina indexes, Global Mean Sea Level, Earth Orientation Parameters-derived low-degree spherical harmonic coefficients, and in-situ OBP measurements for validation.

Optimal Design of a Third Pair of Gravity Satellites to Augment Two Existing Polar Pairs to Enhance Earth's Temporal Gravity Field Recovery

Optimal Design of a Third Pair of Gravity Satellites to Augment Two Existing Polar Pairs to Enhance Earth's Temporal Gravity Field Recovery

A detailed analysis of stochastic models applied to temporal gravity field recovery with GRACE observations

Summary In this study, we analyzed the impacts of errors in background force models and observed non-gravitational forces on the pseudo-observations (pre-fits) during gravity field recovery based on the GRACE satellite gravity mission. To reduce these effects, we introduced the stochastic parameters into the functional model of the variational equation integration approach to absorb this type of noise contribution. Simultaneously, the prior variances of observed orbits and K-Band range rates used in traditional method are re-estimated with least-square variance component estimation (LS-VCE) after considering these stochastic parameters. To improve the computing efficiency, a modified method of the calculation of sensitivity matrices related to the introduced stochastic parameters is proposed. Compared to the method of variation of constants widely used in the precise orbit determination and gravity field recovery, the modified method decreases the computational time of these matrices by about four times. Furthermore, an efficient LS-VCE algorithm is derived in a more generalized case. The efficient algorithm only costs 1% of the time of the unoptimized method. With the GRACE data, we analyzed the benefits of these refinements in gravity field recovery, and the results show that these improvements can mitigate the impacts of errors in background force models and accelerometer data on recovered gravity field models, especially in the high degree signals. Furthermore, the quality of results has less dependence on parameterization.

A New GRACE Filtering Approach Based on Iterative Image Convolution

AbstractThe Gravity Recovery and Climate Experiment (GRACE) mission and its successor GRACE Follow‐On (GRACE‐FO) mission provide humans with a unique perspective on mass distribution through accurate temporal gravity field models. However, these models suffer from unavoidable stripe errors in the spatial domain. A new approach based on image processing has been developed for filtering GRACE and GRACE‐FO spherical harmonic solutions. In this approach, the gravity fields are treated as noise‐contaminated images, and the stripe errors are expected to be suppressed by convolving the input with an appropriate kernel. To verify the effectiveness of the proposed approach, a closed‐loop simulation environment over the nominal mission lifetime of 5 years is designed. Image processing indicators and geophysical information evaluation results demonstrate the superior performance of the new approach in suppressing stripe errors. In the context of real GRACE data processing, our new approach still yields better results as follows: (a) The comprehensive ability of de‐striping and retaining details has slight advantages over some commonly used filters, as demonstrated through spatial distributions, amplitude spectra, and coefficient spectra. (b) The equivalent water height time series at the basin scale is comparable to the results derived from other filters or Level‐3 products. (c) The estimated signal amplitude of the Mw9.1 2004 Sumatra earthquake co‐seismic gravity change is 52.7% larger than that derived from the Gaussian 300 km filter, which is much closer to the theoretical value derived from the dislocation theory.

Small satellite formations and constellations for observing sub-daily mass changes in the Earth system

SUMMARY Satellite gravity missions so far are medium size satellites consisting of one or a pair of satellites flying in near-polar or sun-synchronous orbital planes. Due to the limited observation geometry and the related space–time sampling, high-frequency non-tidal mass variation signals from atmosphere and ocean cannot be observed and cause temporal aliasing. For current single-pair satellite gravimetry missions as GRACE and GRACE Follow-On (GRACE-FO) temporal aliasing is the limiting factor and represents the major error source in the gravity field time-series. Adding a second inclined satellite pair to a GRACE-like polar pair (Bender constellation) currently is the most promising solution to increase the spatio-temporal resolution and to significantly reduce the temporal aliasing error. This shall be implemented with the MAGIC mission in future. With the ongoing developments in miniaturization of satellites and gravity-relevant instruments (accelerometers and intersatellite ranging), in future constellations of multiple small satellite pairs may solve this problem even beyond the capabilities of a Bender constellation. Therefore, in this study the capabilities of such constellations flying in specific formations are investigated in order to enable a retrieval of the temporal gravity field on short time scales. We assess the performance of up to 18 satellite pairs. The satellite configurations cover satellite pairs in polar and inclined orbits flying in pair-wise or pearl-string formation with varying mean anomalies and right ascensions of the ascending node (RAAN). As future potential miniaturized instruments optomechanical accelerometers with similar performance as those flying on GRACE-FO are a candidate, while for the intersatellite ranging instrument still some technological development is required. Therefore, in this study a microwave ranging system equivalent to the GRACE and GRACE-FO instruments performance is taken as baseline assuming that such instruments can be miniaturized in future as well. In numerical closed-loop simulations, up to nine different satellite configurations with up to 18 satellite pairs are evaluated based on the retrieval of the non-tidal temporal gravity field on a monthly basis. From the simulation results it is concluded that the best-performing satellite constellation of 18 polar satellite pairs already is outperformed by a typical Bender-like constellation of 1 polar and 1 inclined pair. In general, we identify that increasing the number of satellite pairs leads to an improved gravity field retrieval, either at low spherical harmonic degree and order (d/o) by the shift in RAAN or at high d/o by the shift in mean anomaly. By a two-step simulation approach, co-estimating also (sub-)daily gravity fields for selected configurations with a large number of satellite pairs distributed equally over the globe, it is possible to retrieve stand-alone gravity fields at 24, 12 and 6 hr temporal resolution. Ultimately it is concluded that a network of miniaturized satellites with instrument performances similar to GRACE-FO and flying in a well-defined constellation has the potential to observe (sub-)daily mass variations and therefore could drastically reduce the problem of temporal aliasing due to high frequency mass variations in the Earth system.

Assessment of a near-polar pair mission for detecting the Earth's temporal gravity field

SUMMARYTo ensure the global observability of next generation gravimetric mission (NGGM), different agencies have to repeatedly launch satellites to about 89.0° orbit inclination. However, due to the poor isotropy of observation system, only minor improvement in terms of temporal gravity field estimation can be obtained via these repeatedly launched polar pair missions. To ensure the global observability as well as the isotropy of observation system, a near-polar pair mission rather than a polar mission is likely an optimal selection, especially considering that the Gravity Recovery and Climate Experiment (GRACE) Follow-On mission has been already in operation. In this study, for the upcoming NGGMs (for instance, the Chinese NGGM), we design a closed-loop simulation to assess the performance of a near-polar mission at a near-circular orbit with about 500 km altitude for detecting the Earth's temporal gravity field, and the main conclusions are summarized as follows. (1) Based on the statistic results, 85.0° is selected as the optimal orbit inclination for the near-polar mission, which provides 37 per cent noise reduction in terms of cumulative geoid height error in spectral domain, but also 31 per cent noise reduction in terms of mean oceanic root-mean-square (RMS) error in spatial domain when compared to the 89.0° polar mission (89-PM). (2) To figure out the reason of these noise reductions, we also compare the contribution of single error components [including instrument error, atmospheric and oceanic (AO) aliasing error, ocean tide error]. It indicates that the outperformance of the 85.0° near-polar mission (85-NPM) is mainly derived from the relatively smaller non-tidal atmospheric and oceanic mass variation error. (3) Although there are inevitable 5.0° polar gaps in the 85-NPM, the analysis result (including the comparison via in-orbit observations and simulated retrieved solutions) still demonstrates a comparable performance of the 85-NPM in tracking mass variations over the Antarctic, and even an outperformance with 12 per cent noise reduction over the Greenland when compared to the 89-PM. The result confirms the feasibility of implementing a near-polar mission as a stand-alone mission or a complementary observation system for the repeatedly launched polar missions, which offers an alternative option of launching the Chinese NGGM satellites to an 85.0° inclination orbit instead of 89.0°.

Filtering GRACE temporal gravity field solutions using ensemble empirical mode decomposition approach

Due to the strong noise that exists in GRACE (Gravity Recovery and Climate Experiment) temporal gravity field solutions, geophysical signals are normally drowned which need many effective filtering approaches. Considering the advantage of the ensemble empirical mode decomposition (EEMD) approach, we used the EEMD to filter the noise in this study together with the empirical mode decomposition (EMD) for comparisons. EMD method is a spectrum analysis method, which is very effective for non-stationary signals. EMD process is essentially a means to process non-stationary signals. It has been applied in many fields in recent years. Considering the characteristics of the spherical harmonic coefficient model that the noise level higher with the increasing degree, we divided the gravity field solutions into two parts (degrees 2–28 and degrees 29–60) based on the ratios of the latitude-weighted root mean square (RMS) over the land and ocean signals when adopting different truncated degrees. For the real GRACE solution experiments, the results show that the fitting errors of EEMD approach are always smaller than those of EMD approach, and the mean RMS ratio of EEMD is 3.45, larger than 3.40 of EMD. The simulation results show that the latitude weighted root mean square errors for EEMD approach are smaller than those of EMD, indicating that EEMD can extract the geophysical signals more accurately. Therefore, it is reasonable to conclude that EEMD performs better than EMD for filtering GRACE solutions.

Impacts of frequency-dependent instrument noise for next-generation gravimetric mission on determining temporal gravity field model

Impacts of frequency-dependent instrument noise for next-generation gravimetric mission on determining temporal gravity field model

The impacts of reducing atmospheric and oceanic de-aliasing model error on temporal gravity field model determination

SUMMARYThe Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE Follow-On mission have been estimating temporal gravity field models for various geoscience applications since 2002. While the errors in atmospheric and oceanic de-aliasing (AOD) model are still the key limitation for GRACE-type missions especially taking advantages of improved laser ranging interferometer (LRI), this paper explores the realistic assumption of continuously reducing AOD model error in global scale and regional scale (e.g. ocean, Greenland, Qinghai-Tibet plateau and South America) in the anticipated future. For this, using a realistic orbit scenario and error assumptions both for instrument and background model errors, the 5-yr full-scale simulations are implemented in the context of 26 scenarios with different AOD model errors. Our overall simulation results demonstrate that: (1) when the AOD model errors are reduced in the global scale, the corresponding gain in temporal gravity field determination is significant, with the cumulative geoid height error decrease from 11.28 to 6.25 mm in spectral domain, as well as 26.3–65.2 per cent noise reduction in terms of mean RMS residuals over ocean in spatial domain. (2) When the AOD model errors are reduced in the regional scale, the improvements of temporal gravity field estimations are diverse in different simulation scenarios. The most notable noise reduction, with 22.9–43.9 per cent noise reduction in spatial domain, is observed when the AOD model error decreases in ocean. The limited noise reductions (0.1 per cent and 1.3 per cent respectively in spectral and spatial domain) are observed in the temporal gravity field estimations if the AOD model is refined in other typical regions such as the Qinghai-Tibet plateau, the Greenland and the South America. (3) However, when the satellites passing over the AOD model refined regions, the along-orbit range rate analysis indicates that, there are visible differences by about 50.0 nm s−1 in terms of range rate residuals as well as 11.0–48.5 nm s−1 in terms of the mean RMS of range rate residuals. These results reflect the benefits of reducing AOD model error in both global and regional scale for improving GRACE-type temporal gravity estimation, especially considering the development of LRI technology.

Improving Spatial Resolution of GRACE-Derived Water Storage Changes Based on Geographically Weighted Regression Downscaled Model

Obtaining high-resolution products that can accurately estimate the spatiotemporal changes in regional water resources is essential for the rational utilization of water resources. The temporal gravity field model derived from the Gravity Recovery and Climate Experiment (GRACE) satellite can effectively monitor the regional terrestrial water storage (TWS) changes. Nevertheless, the main of GRACE products is their coarse spatial resolution, which limits their applicability to small-scale regions. Herein, we propose a geographically weighted regression downscaled model (GWRDM) to improve the spatial resolution of TWS from 0.5° to 0.1° and validate it against the downscaled results provided by the spatial global regression downscaled model (SGRDM) and temporal grid regression downscaled model (TGRDM). The results show that the downscaled products based on GWRDM outperform those based on SGRDM and TGRDM. The GWRDM not only effectively improves the spatial resolution of GRACE products but also maintains the intensity of the original signal. Similarly, the GWRDM is further used to downscale groundwater storage (GWS) and validated against the in situ observations. The downscaled GWS based on GWRDM agrees well with in situ observations. On the monthly scale, the average correlation coefficient (CC) for both is 0.53 and above 0.70 for some in situ observations. On the annual scale, 81.25% and 37.50% of the in situ observations have CC values larger than 0.60 and 0.90, respectively, which further verifies the reliability of GWRDM. Consequently, the GWRDM provides a practical algorithm for obtaining high-resolution water storage estimates, which is expected to provide a reference for small-scale regional water resources management.

Interplay of Altitude, Ground Track Coverage, Noise, and Regularization in the Spatial Resolution of GRACE Gravity Field Models

AbstractModels of the temporal gravity field derived from space gravity missions are typically produced with monthly temporal resolution and ∼300‐km spatial resolution. However, variations in instrument performance and altitude of the Gravity Recovery and Climate Experiment (GRACE) mission impact the spatial resolution that can be achieved month‐to‐month. As the altitude of the orbits of the twin spacecraft vary throughout the mission, so does the ability of the observations to recover certain components of the temporal gravity field. The spatial resolution of GRACE observations should increase as the altitude decreases throughout the mission because the reduced altitude intensifies the gravity signals acting on the satellites. Simulations using actual GRACE altitude and ground track coverage and realistic noise levels confirm this predicted influence of the altitude of the satellites on the accuracy of the estimated solutions. Solutions with larger mass concentration elements (mascons) are more numerically stable as the satellite altitude decreases but they suffer from greater error caused by the inability to properly represent spatial variations of signals within mascons, referred to as intramascon variability. Mascons as small as ∼150 × 150 km (i.e., ∼1.5 arc‐degree) reduce the intramascon variability and, with appropriate regularization, yield the most accurate solutions, especially during the low‐altitude periods of the GRACE mission. Importantly, unlike spherical harmonic solutions, regularized mascon solutions are not degraded during resonant orbit months, and are of comparable quality to months with full ground track coverage.

Terrestrial Water Storage Component Changes Derived from Multisource Data and Their Responses to ENSO in Nicaragua

Approximately 3.5 million people in Nicaragua have experienced food insecurity due to the El Niño-Southern Oscillation (ENSO)-induced drought from 2014 to 2016. It is essential to study terrestrial water storage component (TWSC) changes and their responses to ENSO to prevent the water crisis in Nicaragua influenced by ENSO. In this paper, we investigate the TWSC changes in Nicaragua and its sub-basins derived from the Gravity Recovery and Climate Experiment (GRACE)’s temporal gravity field, hydrological model, and water level data, and then determine the connection between the TWSC and ENSO from April 2002 to April 2021 by time series analysis. The research results show that: (1) The estimated TWSC changes in Nicaragua are in good agreement with the variation of precipitation and evaporation, and precipitation is the main cause of TWSC variation. (2) According to the cross-correlation analysis, there is a significant negative peak correlation between the interannual TWSC and ENSO in western Nicaragua, especially for interannual soil moisture (−0.80). The difference in peak correlation between the western and eastern sub-basins may be due to the topographic hindrance of the ENSO-inspired precipitation process. (3) The cross-wavelet analysis indicates that the resonance periods between TWSC and ENSO are primarily 2 and 4 years. These resonance periods are related to the two ENSO modes (the central Pacific (CP) mode with a quasi-2-year period and the eastern Pacific (EP) mode with a quasi-4-year period). Furthermore, their resonance phase variation may be due to the transition to ENSO mode. This study revealed the relationship between ENSO and TWSC in Nicaragua, which can provide a certain reference for water resources regulation.

Hybrid Electrostatic–Atomic Accelerometer for Future Space Gravity Missions

Long-term observation of Earth’s temporal gravity field with enhanced temporal and spatial resolution is a major objective for future satellite gravity missions. Improving the performance of the accelerometers present in such missions is one of the main paths to explore. In this context, we propose to study an original concept of a hybrid accelerometer associating a state-of-the-art electrostatic accelerometer (EA) and a promising quantum sensor based on cold atom interferometry. To assess the performance potential of such an instrument, numerical simulations were performed to determine its impact in terms of gravity field retrieval. Taking advantage of the long-term stability of the cold atom interferometer (CAI), it is shown that the reduced drift of the hybrid sensor could lead to improved gravity field retrieval. Nevertheless, this gain vanishes once temporal variations of the gravity field and related aliasing effects are taken into account. Improved de-aliasing models or some specific satellite constellations are then required to maximize the impact of the accelerometer performance gain. To evaluate the achievable acceleration performance in-orbit, a numerical simulator of the hybrid accelerometer was developed and preliminary results are given. The instrument simulator was in part validated by reproducing the performance achieved with a hybrid lab prototype operating on the ground. The problem of satellite rotation impact on the CAI was also investigated both with instrument performance simulations and experimental demonstrations. It is shown that the proposed configuration, where the EA’s proof-mass acts as the reference mirror for the CAI, seems a promising approach to allow the mitigation of satellite rotation. To evaluate the feasibility of such an instrument for space applications, a preliminary design is elaborated along with a preliminary error, mass, volume, and electrical power consumption budget.

Adaptive DDK Filter for GRACE Time-Variable Gravity Field with a Novel Anisotropic Filtering Strength Metric

Filtering for GRACE temporal gravity fields is a necessary step before calculating surface mass anomalies. In this study, we propose a new denoising and decorrelation kernel (DDK) filtering scheme called adaptive DDK filter. The involved error covariance matrix (ECM) adopts nothing but the monthly time-variable released by several data centers. The signal covariance matrix (SCM) involved is monthly time-variable also. Specifically, it is parameterized into two parameters, namely the regularization coefficient and the power index of signal covariances, which are adaptively determined from the data themselves according to the generalized cross validation (GCV) criterion. The regularization coefficient controls the global constraint on the signal variances of all degrees, while the power index adjusts the attenuation of the signal variances from low to high degrees, namely local constraint. By tuning these two parameters for the monthly SCM, the adaptability to the data and the optimality of filtering strength can be expected. In addition, we also devise a half-weight polygon area (HWPA) of the filter kernel to measure the filtering strength of the anisotropic filter more reasonably. The proposed adaptive DDK filter and filtering strength metric are tested based on CSR GRACE temporal gravity solutions with their ECMs from January 2004 to December 2010. Results show that the selected optimal power indices range from 3.5 to 6.9, with the corresponding regularization parameters range from 1 × 1014 to 5 × 1019. The adaptive DDK filter can retain comparable/more signal amplitude and suppress more high-degree noise than the conventional DDK filters. Compared with the equivalent smoothing radius (ESR) of filtering strength, the HWPA has stronger a distinguishing ability, especially when the filtering strength is similar.

ANU GRACE Data Analysis: Orbit Modeling, Regularization and Inter‐satellite Range Acceleration Observations

AbstractSeveral different basis functions have been used to represent the Earth's gravity field in order to generate estimates of mass variations on Earth from the analysis of data of the Gravity Recovery and Climate Experiment (grace) and its successor grace Follow‐On missions, including spherical harmonics, mass concentration elements (mascons) and slepian functions. Each approach depends inherently upon accurate modeling of the orbits of the pair of satellites as they revolve around the Earth, so that the observations of inter‐satellite changes in range (or, more specifically, range rate) can be exploited to identify mass variations. We have developed software using a classical orbit modeling approach, mascons and 24‐hr orbit integration, to estimate simultaneously corrections to orbital parameters and the temporal gravity field from grace data. Rather than using the range rate, we use the range acceleration as the inter‐satellite observable as it aids in localizing the mass variations. Level‐1 B range acceleration observations contain high levels of high‐frequency noise that inhibits their usefulness for this purpose. Instead, we generate range acceleration observations by numerical differentiation of the Level‐1B range rate prefit residuals. Simulations show that the gravity signal is not attenuated in this process. Our monthly estimates of mass anomalies from grace data (2003–2016) agree well with previous studies, both spatially and temporally. When converted to spherical harmonics our time series of C2,0, derived from grace data alone, are close to the independent estimates from satellite laser ranging, but the overall solution is improved by substituting the SLR C2,0.

ANU GRACE Data Analysis: Characteristics and Benefits of Using Irregularly Shaped Mascons

AbstractThe estimation of mass anomalies using Gravity Recovery and Climate Experiment (GRACE) data involves parameterizing the temporal gravity field using basis functions. In this study, we show that the use of irregularly shaped mass concentration (mascon) tiles that follow land/ocean boundaries reduces the leakage of land signals into ocean regions and vice versa. Leakage of signal from continents to oceans in mascons that cross the coastline affect the integrated mass changes at a regional scale. For example, the calculated mass loss in 2016 is ∼5% greater for Greenland when using mascons that follow coastlines. We describe efficient algorithms for computing the accelerations acting on the satellites caused by mass changes on mascons, along with the partial derivatives relating the mass changes to the inter‐satellite observations. Through simulation, we quantify the impact of different mascon geometries, spatial resolution and regularization. The variations of mass change signals within mascons, which we call “intra‐mascon variability,” contribute to errors in estimates of mass variation from GRACE data. While this can be mitigated through the regularization of the inversions, it cannot be removed entirely. The use of irregularly shaped mascons that follow land/ocean boundaries reduces the “intra‐mascon leakage” of land signals into ocean regions and vice versa. This approach can also be applied to hydrological basins for calculating integrated mass changes on catchment scales.

Mitigation of thermal noise in GRACE accelerometer observations

The precise calculation of GRACE and GRACE-FO satellite orbits is reliant on knowledge of accurate non-gravitational accelerations acting on the spacecraft. These are measured by the on-board accelerometers that require a thermal environment stabilised to ∼±0.1 °C per revolution. However, during periods of the GRACE mission with reduced thermal control, internal temperature variations reached up to 10 °C within a revolution, causing low-frequency and non-linear drifts in the accelerometer observations. Additionally, accelerometer bias drifts occurred throughout the GRACE mission as changes in the orientation of the orbital plane with respect to the Earth-to-Sun vector caused the satellites to absorb more or less solar energy. These temperature-induced drifts degrade the quality of mass change estimates, particularly during the latter half of the GRACE mission after thermal control of the satellites was terminated. We filter (in the frequency domain) the accelerometer observations to remove these low-frequency components (f<0.045 mHz). The bias drift removed from the cross-track is then scaled to derive a thermally-based correction for the highly sensitive along-track observations. We then estimate temporal gravity fields using the ANU GRACE software, our filtered accelerometer observations and the range acceleration as the inter-satellite observation. The use of our thermally-corrected accelerometer measurements significantly improves the accuracy of both orbit modelling and gravity field estimation.