Improved STOchastic modelling in GRACE/GRACE-FO REal data processing (ISTORE)

• Applicant: Dr.-Ing. Rolf König
• Subject Area: Geodesy, Photogrammetry, Remote Sensing, Geoinformatics, Cartography
• Term: from 2019 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 388296632

One of the main goals of the RU is the assessment of an improved stochastic modelling inGRACE and GRACE-FO temporal gravity field determination. The objective for this IP is to take into account extensive stochastic error characteristics of the central GRACE/GRACE-FO observation types for inter-satellite ranging and accelerometer measurements, and to utilize wide-ranging co-variance information of atmospheric, oceanic and hydrologic background models. With an improved a-priori stochastic model of the estimation process, the ambition is to improve the weighting of all input data (observations and background models) and herewith the estimates of the gravity field parameters and their formal errors. The task will be tackled with a combination of Monte Carlo simulations and linear error propagation theory. Procedures and outcome will be tested and validated using 3 years of GRACE/GRACE-FO real data.

• DFG Programme: Research Units
• Subproject of: FOR 2736: New Refined Observations of Climate Change from Spaceborne Gravity Missions (NEROGRAV)
• Co-Investigator: Dr. Karl Hans Neumayer