An Optimized Short‐Arc Approach: Methodology and Application to Develop Refined Time Series of Tongji‐Grace2018 GRACE Monthly Solutions

Abstract

Considering the unstable inversion of ill‐conditioned intermediate matrix required in each integral arc in the short‐arc approach presented in Chen et al. (2015, https://doi.org/10.1002/2014JB011470), an optimized short‐arc method via stabilizing the inversion is proposed. To account for frequency‐dependent noise in observations, a noise whitening technique is implemented in the optimized short‐arc approach. Our study shows that the optimized short‐arc method is able to stabilize the inversion and eventually prolong the arc length to 6 hr. In addition, the noise whitening method is able to mitigate the impacts of low‐frequency noise in observations. Using the optimized short‐arc approach, a refined time series of Gravity Recovery and Climate Experiment (GRACE) monthly models called Tongji‐Grace2018 has been developed. The analyses allow us to derive the following conclusions: (a) During the analyses over the river basins (i.e., Amazon, Mississippi, Irrawaddy, and Taz) and Greenland, the correlation coefficients of mass changes between Tongji‐Grace2018 and others (i.e., CSR RL06, GFZ RL06, and JPL RL06 Mascon) are all over 92% and the corresponding amplitudes are comparable; (b) the signals of Tongji‐Grace2018 agree well with those of CSR RL06, GFZ RL06, ITSG‐Grace2018, and JPL RL06 Mascon, while Tongji‐Grace2018 and ITSG‐Grace2018 are less noisy than CSR RL06 and GFZ RL06; (c) clearer global mass change trend and less striping noise over oceans can be observed in Tongji‐Grace2018 even only using decorrelation filtering; and (d) for the tests over Sahara, over 36% and 19% of noise reductions are achieved by Tongji‐Grace2018 relative to CSR RL06 in the cases of using decorrelation filtering and combined filtering, respectively.

Next-Generation Gravity Missions: Sino-European Numerical Simulation Comparison Exercise

“…Tongji: The simulations were carried out by using the Satellite Gravimetry Analysis Software (SAGAS) developed by Tongji University [32][33][34][35], which has been successfully applied to determine gravity field models from GRACE Level-1b observations. The simulation environment is based on numerical orbit integration, where Adams and Kiogh-Shampine-Gordon (KSG) numerical integration methods are jointly used.…”

“…Non-conservation acceleration observation errors are estimated together with the gravity field coefficients according to [33,34]. Variance-covariance matrices for both orbit and range-rate observations are constructed from residuals of the instrument errors on the basis of [35].…”

The GFZ GRACE RL06 Monthly Gravity Field Time Series: Processing Details and Quality Assessment

“…Apart from the SDS, recent GRACE gravity field time series are provided by other processing centers, e.g., ITSG-Grace2018 [14], CNES/GRGS RL04 [15], AIUB RL02 [16], or Tongji-Grace2018 [17].…”

High‐Resolution GRACE Monthly Spherical Harmonic Solutions

“…To determine monthly geopotential coefficients u from GRACE observations (i.e., orbit, intersatellite range‐rate, attitude, and acceleration data), we briefly review the optimized short‐arc approach presented in Chen et al. (2019), where the observation equations for both orbits and intersatellite range‐rates are summarized in the following form: in which denotes the vector of parameters to be estimated, containing the geopotential coefficients and accelerometer calibration parameters as well as boundary parameters ; is the correction vector to the measurements of both orbits (GRACE A and GRACE B) and intersatellite range‐rates; A is the design matrix regarding x ; and y is the residual vector by subtracting reference orbits and range‐rates from their observations. Using the weighted least squares method by minimizing the criterion , we can easily derive the normal equation regarding the parameters to be solved as follows: in which P is the weight matrix for measurements (orbits and range‐rates) constructed according to the postfit residuals of measurements (Chen et al.…”