The aim of the geo-Q (Relativistic Geodesy and Gravimetry with Quantum Sensors) program is to explore new frontiers of the determination of the Earth’s gravitational field and of monitoring the global and regional mass redistribution at a new level of accuracy.
We are participating in the global gravity field parameter estimation project (project C01), as a key research area in the geo-Q program, which will cover the global gravity field recovery from satellite data providing improvements needed for the GRACE and GRACE-FO data analysis. The general objective of this project is to improve the estimation of gravity field results from inter-satellite ranging data and to reduce the magnitude of postfit residuals as far as possible towards the limitations given by the combined sensor noise and by the spatial-temporal sampling. By close collaboration with the Institute of Geodesy, Leibniz University of Hanover, two parallel and related approaches will be investigated:
1. Understanding how systematic errors and variable noise that originate from the sensors, from the measurement system, and from geophysical aliasing affect the gravity field parameter estimation and postfit residuals, starting on the one hand from available knowledge on systematic errors, and on the other hand from the wealth of available postfit residuals data.
2. Developing an advanced covariance stochastic modelling that reflects the error characteristics for proper weighting in the estimation, and to achieve a physically meaningful parameterization of sensor effects.
Mayer-Gürr T. (2006), Gravitationsfeldbestimmung aus der Analyse kurzer Bahnbögen am Beispiel der Satelliten- missionen CHAMP und GRACE. D 98, Dissertation Univ. Bonn.
Mayer-Gürr, T., Kurtenbach, E., Eicker A. (2012), Different representations of the time variable gravity field to reduce the aliasing problem in GRACE data analysis. In Nico Sneeuw, Pavel Novak, Mattia Crespi, and Fernando Sanso (eds.), VII Hotine-Marussi Symposium on Mathematical Geodesy, volume 137 of International Association of Geodesy Symposia pages 285-290. Springer Berlin Heidelberg, doi: 10.1007/978-3-642-22078-4 43.
Kurtenbach, E., Mayer-Gürr, T., and Eicker A., (2009) Deriving daily snapshots of the Earth’s gravity field from GRACE L1B data using Kalman filtering, Geophys Res Lett, 36(17), doi: 10.1029/2009GL039564.
Kurtenbach, E., Eicker, A., Mayer-Gürr T., Holschneider, M., Hayn, M., Fuhrmann, M., and Kusche J. (2012) Improved daily GRACE gravity field solutions using a Kalman smoother, J Geodyn, 59-60(0):39-48, doi: 10.1016/j.jog.2012.02.006.
Mayer-Güurr, T. (2013), Estimation of error covariance functions in satellite gravimetry, IAG General Assembly Potsdam (presentation).