New Refined Observations of Climate Change from Spaceborne Gravity Missions (NEROGRAV)
A deep understanding of mass distribution and mass transport in System Earth is needed to answer central questions in hydrology, oceanography, glaciology, geophysics and climate research. The necessary information is primarily derived from satellite mission data as observed by GRACE (Gravity Recovery and Climate Experiment) and GRACE-FO (Follow-on) describing the gravity field of the Earth and its temporal variations.
The research group (RG) „New Refined Observations of Climate Change from Spaceborne Gravity Missions (NEROGRAV)”, funded by the German Research Foundation (DFG), develops since May 2019 new analysis methods and modeling approaches to improve GRACE and GRACE-FO mission data analysis. The central hypothesis of the research group is therefore: 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 order to reach this overarching goal, the RG in particular concentrates on four different objectives:
- Improvement and error quantification of geophysical background models,
- Improvement of spatial-temporal parameterizations,
- Validation of improved background models and gravity field models against independent data, and
- Synthesis of results and recommendations for NGGMs.
which are elaborated in six Individual Projects (IP):
IP 1: Improved Tidal Dynamics and Uncertainty Estimation for Satellite Gravimetry (TIDUS; PIs: Maik Thomas (FU Berlin), Denise Dettmering (DGFI - TU Munich)
IP 2: Next Generation Non-tidal Atmospheric and Oceanic De-aliasing Models (NAODEMO; PI: Henryk Dobslaw (GFZ)
IP 3: High-Resolution Atmospheric-hydrological Background Modelling for GRACE/GRACE-FO – regional refinement and validation (HIRABAM; PIs: Petra Friederichs, Jürgen Kusche, Andreas Hense, Michael Schindelegger (University Bonn)
IP 4: Optimized Space-Time Parameterization for GRACE and GRACE-FO data Analysis (OSTPAGA; PIs: Roland Pail (TU Munich), Frank Flechtner (TU Berlin (Spokesman of RG))
IP 5: Improved Stochastic Modeling in GRACE/GRACE-FO Real data processing (ISTORE; PI: Rolf König (GFZ)
IP 6: Post-process Techniques, Impact on NGGM And Recommendations (POTINAR; PI: Roland Pail (TU Munich)
The final data products of the different IPs will be made available at the end of phase 1 (spring 2022).
Please follow the link on the left hand side.