Time variable gravity from kinematic orbits of LEO satellites – A 15+ years series of monthly solutions without gaps

  • Norbert Zehentner (Speaker)
  • Mayer-Gürr, T. (Contributor)
  • Sebastian Strasser (Contributor)

Activity: Talk or presentationTalk at conference or symposiumScience to science

Description

Gravity field recovery from high-low satellite to satellite tracking has been applied successfully to former gravity missions like CHAMP and GOCE. The process to derive gravity field estimates from GNSS observations is separated into two steps. First kinematic orbits for the LEO satellite are derived from the GNSS measurements. Subsequently the kinematic orbit positions are introduced as pseudo-observations estimate the gravity field. We make use of a precise point positioning approach based on raw GNSS observations to retrieve kinematic orbits with accuracies of a few centimeters. Some special aspects of the approach are: antenna center variations for phase and code observations, azimuth and nadir angle dependent antenna center variations for transmitters, and azimuth and nadir angle dependent accuracy information for each observation type. In this contribution we will show the impact of these specific processing aspects on the orbit quality and on derived gravity field estimates. The method has been applied to a number of LEO missions, including non-gravity missions like Swarm, Terra-SAR-X, TanDEM-X, MetOp, or Jason 1&2. Based on kinematic orbits from more than 10 satellite missions a time series of individual and unconstrained monthly gravity field solutions has been produced. The series starts in January 2002 and spans more than 15 years without gaps. We demonstrate that it is possible to observe mass variations for regions like Greenland, the Antarctic, the amazon basin, and other large river basins, down to areas as small as the Caspian Sea.
Period3 Aug 2017
Event titleIAG-IASPEI Joint Scientific Assembly 2017
Event typeConference
LocationKobe, JapanShow on map
Degree of RecognitionInternational

Fields of Expertise

  • Sustainable Systems