No abstract

The primary objective of the Gravity Recovery and Climate Experiment follow-on (GRACE-FO) satellite mission, due for launch in August 2017, is to continue the GRACE time series of global monthly gravity field models. For this, evolved versions of the GRACE microwave instrument (MWI), GPS-receiver, and accelerometer will be used. A secondary objective is to demonstrate the effectiveness of a laser ranging interferometer (LRI) in improving the satellite-to-satellite tracking measurement performance. In order to investigate the expected enhancement for Earth science applications we have performed a full-scale simulation over the nominal mission lifetime of five years using a realistic orbit scenario and error assumptions both for instrument and background model errors.Unfiltered differences between the synthetic input and the finally recovered time-variable monthly gravity models show notable improvements with the LRI, on global scale, of the order of 23%. The gain is realized for wavelengths smaller than 240 km in case of Gaussian filtering but decreases to just a few percent when anisotropic filtering is applied. This is also confirmed for some typical regional Earth science applications which show randomly distributed patterns of small improvements but also degradations when using DDK4 filtered LRI based models.Analysis of applied error models indicates that accelerometer noise followed by ocean tide and non-tidal mass variation errors are the main contributors to the overall GRACE-FO gravity model error. Improvements in these fields are therefore necessary, besides optimized constellations, to make use of the increased LRI accuracy and to significantly improve gravity field models from Next Generation Gravity Missions.

The main objective of the US-German twin-satellite mission GRACE (Gravity Recovery and Climate Experiment), launched in March 2002, is a precise survey of the Earth's time-variable gravity field at unprecedented temporal and spatial scales. Temporal changes in the gravity field are related to continuous mass redistributions near the Earth's surface which are caused by various geophysical and climatologically driven processes. Vice versa, transferring the GRACE-based gravity variations into time series of the spatial variability of surface mass anomalies, the mission allows for the first time for a quantification of the ongoing mass transport. Such data is of unique importance for a comprehensive modeling, understanding and interplay of these processes. In this contribution we give an overview of the basic features of the GRACE satellite mission, the gravity recovery process and the derived gravity products at GeoForschungsZentrum Potsdam (GFZ), as well as the interpretation of the GRACE gravity data with the focus on the detection of hydrological signals. This includes a description of the evolution and present status of the quality of GFZ's GRACE-based global gravity models on the actual fourth model generation (called GFZ-RL04), and an overview of recent findings using GRACE data in hydrological applications.

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.

The primary objective of the Gravity Recovery and Climate Experiment follow-on (GRACE-FO) satellite mission, due for launch in August 2017, is to continue the GRACE time series of global monthly gravity field models. For this, evolved versions of the GRACE microwave instrument (MWI), GPS-receiver, and accelerometer will be used. A secondary objective is to demonstrate the effectiveness of a laser ranging interferometer (LRI) in improving the satellite-to-satellite tracking measurement performance. In order to investigate the expected enhancement for Earth science applications we have performed a full-scale simulation over the nominal mission lifetime of five years using a realistic orbit scenario and error assumptions both for instrument and background model errors.Unfiltered differences between the synthetic input and the finally recovered time-variable monthly gravity models show notable improvements with the LRI, on global scale, of the order of 23%. The gain is realized for wavelengths smaller than 240 km in case of Gaussian filtering but decreases to just a few percent when anisotropic filtering is applied. This is also confirmed for some typical regional Earth science applications which show randomly distributed patterns of small improvements but also degradations when using DDK4 filtered LRI based models.Analysis of applied error models indicates that accelerometer noise followed by ocean tide and non-tidal mass variation errors are the main contributors to the overall GRACE-FO gravity model error. Improvements in these fields are therefore necessary, besides optimized constellations, to make use of the increased LRI accuracy and to significantly improve gravity field models from Next Generation Gravity Missions.