Oct 2026· GRACE/GRACE-FO Science Team Meeting 2026· 0 citations
Abstract
GFZ aims to distribute a reprocessed and improved RL07 Level-2 gravity field time series in the last quarter of 2026. Most of these improvements have been developed within the Research Unit “New Refined Observations of Climate Change from Spaceborne Gravity Missions” (NEROGRAV) funded by the German Research Foundation DFG.When developing the new GFZ RL07 processing standards, the main focus was on an optimized stochastic modeling during the GRACE/GRACE-FO gravity field determination. This includes the extension of the stochastic instrument error models, the optimization of the combination of the different observations in terms of relative weighting, and the inclusion of non-tidal background model error variance-covariance information in the adjustment process. Further changes compared to GFZ RL06 comprise the parameterization as well as the applied background models, e.g., the ocean tide model and the static gravity field model.This presentation provides an overview of the GFZ RL07 performance compared to RL06 with focus at specific processing aspects and its impact on the gravity field solution, such as the ocean tide model update or the influence of stochastic modelling of observation and background model errors. Improvements stemming from the applied advanced processing strategy led to a significant reduction of noise (> 30% relative to GFZ RL06), as well as more realistic formal uncertainties of the estimated gravity field parameters. In addition, a short outlook on the expected performance of LRI-based GRACE-FO gravity field performance is presented.
The central hypothesis of the Research Unit (RU) New Refined Observations of Climate Change from Spaceborne Gravity Missions (NEROGRAV) reads: only by concurrently improving and better understanding of sensor data, background models, and processing strategies of satellite gravimetry, the resolution, accuracy, and long-...
M. Murböck, C. Dahle, Natalia Panafidina et al.· GRACE/GRACE-FO Science Team...· 0 citations
Within the framework of the Research Unit NEROGRAV (New Refined Observations of Climate Change from Spaceborne Gravity Missions), we focus on the computation of daily gravity field solutions using a Kalman filter approach. We use the RL07p GRACE/GRACE-FO daily normal equations, which incorporate refined stochastic mode...
Natalia Panafidina, M. Murböck, C. Dahle et al.· GRACE/GRACE-FO Science Team...· 0 citations
GRACE/GRACE-FO missions recover gravity field from orbits observed by GPS and variations in inter-satellite distances obtained by the inter-satellite ranging systems. Compared to GRACE, GRACE-FO is also equipped with a laser ranging interferometer (LRI), a more precise inter-satellite ranging technology and the preferr...
Zi-Tong Zhu, V. Müller, Chang-Qing Wang et al.· Journal of Geodesy· 0 citations
Temporal aliasing of sub-monthly gravimetric signals originating from the Earth's fluid envelope is a major source of error in time-variable gravity field models derived from the GRACE and GRACE Follow-On missions. Minimizing these errors to detect gravimetric signals providing information on solid Earth dynamics and t...
Fabien Gachet, A. Couhert, J. Lemoine et al.· GRACE/GRACE-FO Science Team...· 0 citations
So far, the operational combination of the monthly GRACE, or GRACE-FO gravity field solutions by the Combination Service of Time-variable Gravity fields (COST-G) has been performed on the solution level. The originally foreseen combination on the normal equation (NEQ) level suffered from the very diverse and not realis...
Ulrich Meyer, M. Lasser, C. Dahle et al.· GRACE/GRACE-FO Science Team...· 0 citations
GRACE and GRACE-FO satellite missions measure the spatial and temporal variations in the Earth’s gravity field at a spatial resolution of around 300 kilometers. Unlike most gravity field products available at monthly resolutions, the CNES produces a 10-day Level 2 solution constrained by Satellite Laser Ranging using...