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

Abstract

Time-variable gravity field models derived from observations of the Gravity Recovery and Climate Experiment (GRACE) mission, whose science operations phase ended in June 2017 after more than 15 years, enabled a multitude of studies of Earth’s surface mass transport processes and climate change. The German Research Centre for Geosciences (GFZ), routinely processing such monthly gravity fields as part of the GRACE Science Data System, has reprocessed the complete GRACE mission and released an improved GFZ GRACE RL06 monthly gravity field time series. This study provides an insight into the processing strategy of GFZ RL06 which has been considerably changed with respect to previous GFZ GRACE releases, and modifications relative to the precursor GFZ RL05a are described. The quality of the RL06 gravity field models is analyzed and discussed both in the spectral and spatial domain in comparison to the RL05a time series. All results indicate significant improvements of about 40% in terms of reduced noise. It is also shown that the GFZ RL06 time series is a step forward in terms of consistency, and that errors of the gravity field coefficients are more realistic. These findings are confirmed as well by independent validation of the monthly GRACE models, as done in this work by means of ocean bottom pressure in situ observations and orbit tests with the GOCE satellite. Thus, the GFZ GRACE RL06 time series allows for a better quantification of mass changes in the Earth system.

Evaluating Gravimetric Polar Motion Excitation Estimates from the RL06 GRACE Monthly-Mean Gravity Field Models

“…Regarding to the series from GFZ, it is now officially recommended to replace C 21 /S 21 coefficients for GFZ RL06 with SLR estimates [49]. These coefficients are estimated from a GRACE and SLR combination on the level of normal equations.…”

Drift of the Earth’s Principal Axes of Inertia from GRACE and Satellite Laser Ranging Data

“…The difference in the C 21 and S 21 derived rotation time series might be caused by the different handling of the mean pole in the CSR RL06 and the DGFI-TUM solution. Using different mean pole model could provoke a systematic long-term difference in the C 21 and S 21 time series [28][29][30][31]. The CSR RL06 solution is processed based on the new linear mean pole model, whereas the DGFI-TUM SLR time series is based on the conventional (cubic polynomial) mean pole model [26].…”

A New Coupled Modeling Approach to Simulate Terrestrial Water Storage in Southern California

“…Global-gridded TWS estimates derived from temporal gravity field variations measured by the Gravity Recovery and Climate Experiment (GRACE) were used to validate the models [34]. GRACE TWS anomaly estimates are available at https://grace.jpl.nasa.gov [35] in three distinct datasets, each of which are obtained through different filtering and geophysical correction algorithms [36][37][38]. The data is available on a 1 • × 1 • latitude-longitude geographical resolution grid and represents the latest versions of GRACE estimates up to date.…”