Surface mass variation monitoring from orbit information of GPS-tracked low-Earth orbiters

Tuesday, 16 December 2014: 9:45 AM
Matthias Luigi Bruno Weigelt1, Oliver Baur2, Norbert Zehentner3, Torsten Mayer-Gürr3 and Tonie M van Dam1, (1)University of Luxembourg, Luxembourg, Luxembourg, (2)Austrian Academy of Sciences, Graz, Austria, (3)Graz University of Technology, Graz, Austria
In the last decade, temporal variations of the gravity field from GRACE inter-satellite observations have become one of the most ubiquitous and valuable sources of information for environmental studies. In order to bridge the likely gap between the present GRACE and the upcoming GRACE follow-on projects, we investigate the potential of gravity field information derived from orbit analysis for surface mass variation detection. The Swarm mission - launched on November 22, 2013 - is the most promising candidate to directly acquire large-scale mass variation information on the Earth's surface in the absence of GRACE. Although the magnetometry mission Swarm has not been designed for gravity field purposes, its three satellites have the appropriate orbit characteristics for such an endeavour. Hence, from an orbit analysis point of view the Swarm satellites are comparable to the CHAMP, GRACE and GOCE spacecraft.

In a first study, we assess the stand-alone capability of the Swarm mission for mass variation detection in a real-case environment. For this purpose, we ''approximate'' the Swarm scenario by the GRACE+CHAMP constellation. In a second study, we incorporate tracking observations from a series of additional satellites (e.g., GOCE, MetOp, TanDEM-X, Swarm) and extend the length of the time series according to data availability. We will demonstrate to what extent these measures improve the inference of time-variable features from orbit information. For both studies, in the first step, kinematic orbits of the individual satellites are derived from GPS observations. From these orbits, we compute monthly combined time-variable gravity fields. Finally, we infer mass variation in selected areas from the gravity signal. These results are compared to the findings obtained from mass variation detection exploiting CSR-RL05 gravity fields (the latter serve as ''benchmark solutions'').