Advanced processing strategies for a future GFZ GRACE/GRACE-FO Level-2 data release

The central hypothesis of the Research Unit (RU) New Refined Observations of Climate Change from Spaceborne Gravity Missions (NEROGRAV), funded for the second three years phase by the German Research Foundation DFG, reads: only by concurrently improving and better understanding of sensor data, background models, and processing strategies of satellite gravimetry, the resolution, accuracy, and long-term consistency of mass transport series from satellite gravimetry can be significantly increased; and only in that case the potential of future technological sensor developments can be fully exploited.

In continuation of the first RU phase, the individual project Improved Stochastic Modeling in GRACE/GRACE-FO Real Data Processing (ISTORE) 2 works towards the completion of the optimized stochastic modeling for GRACE and GRACE-FO gravity field determination. This includes three main tasks: (1) the extension of the stochastic instrument error models of the first phase including Global Navigation Satellite System (GNSS) observations; (2) the optimization of the combination of the different observations; (3) the inclusion of tidal and temporally changing non-tidal background model error variance-covariance matrices in the adjustment process. Based on recent developments within NEROGRAV we also work on a future GFZ GRACE/GRACE-FO Level-2 data release.

This presentation provides an overview of the main outcomes of the advanced processing strategies. We will discuss details on stochastic modeling of accelerometer, inter-satellite ranging, and GNSS observations, and of ocean tide and non-tidal atmospheric-oceanic background models. We present Level-2 results based on the monthly solutions within the three test years 2007, 2014 and 2019 in the spectral and spatial domain in comparison with the standard GFZ GRACE/GRACE-FO RL06 time series.