New Generation Stochastic Data-driven Calibration of the Accelerometers and Modelling of the Non-gravitational Accelerations in GRACE missions

The Gravity Recovery and Climate Experiment (GRACE) and its successor, GRACE Follow-On (GRACE-FO), have significantly advanced our understanding of Earth's gravity field and its temporal changes by measuring subtle gravity variations caused by mass redistribution on and beneath Earth's surface. A key component of these missions is the use of geodetic-quality GPS receivers for precise orbit determination and 3D accelerometers, which measure non-gravitational forces like atmospheric drag and solar radiation pressure. However, challenges in using accelerometers must be addressed to ensure data and modeling accuracy.

A primary challenge is the calibration of accelerometers, as inaccuracies can lead to significant errors in gravity field modeling and thermospheric density estimates of up to 10%, depending on the levels of solar activity. This study introduces a calibration method using matched filter techniques applied to accelerometer measurements and GPS-derived accelerations. The estimated calibration parameters show high stability with values close to 1, as expected from the ultra-sensitive electrostatic space accelerometers and proposed by other studies.

Error assessment of GRACE and future mass change missions must consider accelerometer measurements as stochastic quantities with realistic error estimates. This involves identifying and quantifying measurement errors stemming from instrument noise, thermal effects, correlations and transient effects. This study generates a stochastic (weighted) 1B accelerometer dataset to investigate systematic errors from various sources like geomagnetic storms, temperature changes, and terminator crossings. Contrastingly to the official accuracy which is 〖0.1 nm/s〗^2 for the along-track and radial direction and 〖1 nm/s〗^2 in the cross-track, the proposed dataset being clean from spikes has an accuracy of 〖 10^(-3) nm/s〗^2.

Accurate modeling of non-gravitational forces is essential for isolating gravitational signals and estimating drag, which is crucial for determining thermospheric densities. This study proposes a data-driven model for the dominant forces of solar and thermal radiation pressure and drag on the GRACE-C satellite, using the new 1B dataset produced in this study. A comprehensive analysis of residuals which are up to 〖2 nm/s〗^2 in the along-track, 〖0.5 nm/s〗^2 in the cross-track and up to 〖5 nm/s〗^2 in the radial direction, reveals disturbances with latitudinal dependency, especially during high geomagnetic activity.